=======================================================   RESTART [11-16 03:23:50]   =======================================================
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
wandb: Currently logged in as: kaiqiu. Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.18.3
wandb: Run data is saved locally in /home/user/VAR/wandb/run-20241115_112515-mqxravb6
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run faithful-plasma-403
wandb:  View project at https://wandb.ai/kaiqiu/VAR
wandb:  View run at https://wandb.ai/kaiqiu/VAR/runs/mqxravb6
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_7 0.0261 ms 100.0%
  triton_mm_8 0.0262 ms 99.8%
  triton_mm_11 0.0264 ms 99.0%
  triton_mm_12 0.0269 ms 97.0%
  triton_mm_6 0.0270 ms 96.6%
  triton_mm_9 0.0272 ms 96.1%
  triton_mm_4 0.0275 ms 94.9%
  triton_mm_2 0.0279 ms 93.7%
  triton_mm_13 0.0283 ms 92.4%
  triton_mm_14 0.0284 ms 92.0%
SingleProcess AUTOTUNE benchmarking takes 2.0815 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2198 ms 100.0%
  triton_mm_51 0.2259 ms 97.3%
  triton_mm_52 0.2531 ms 86.9%
  triton_mm_45 0.2624 ms 83.8%
  triton_mm_47 0.2710 ms 81.1%
  triton_mm_43 0.2744 ms 80.1%
  bias_addmm 0.2988 ms 73.6%
  triton_mm_44 0.3044 ms 72.2%
  triton_mm_48 0.3089 ms 71.1%
  addmm 0.3217 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 2.6613 seconds and 0.0538 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0890 ms 100.0%
  triton_mm_69 0.0904 ms 98.4%
  bias_addmm 0.0964 ms 92.2%
  triton_mm_66 0.0975 ms 91.2%
  triton_mm_64 0.0986 ms 90.2%
  triton_mm_71 0.0996 ms 89.3%
  triton_mm_62 0.1019 ms 87.3%
  addmm 0.1107 ms 80.4%
  triton_mm_63 0.1113 ms 79.9%
  triton_mm_67 0.1125 ms 79.1%
SingleProcess AUTOTUNE benchmarking takes 2.5198 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2921 ms 100.0%
  triton_mm_89 0.2945 ms 99.2%
  bias_addmm 0.3247 ms 90.0%
  triton_mm_90 0.3322 ms 87.9%
  triton_mm_83 0.3417 ms 85.5%
  triton_mm_81 0.3609 ms 80.9%
  triton_mm_85 0.3638 ms 80.3%
  triton_mm_82 0.3979 ms 73.4%
  triton_mm_86 0.4102 ms 71.2%
  addmm 0.4165 ms 70.1%
SingleProcess AUTOTUNE benchmarking takes 2.6088 seconds and 0.0126 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2944 ms 100.0%
  triton_mm_108 0.3074 ms 95.8%
  triton_mm_107 0.3162 ms 93.1%
  triton_mm_109 0.3267 ms 90.1%
  addmm 0.3308 ms 89.0%
  triton_mm_102 0.3563 ms 82.6%
  triton_mm_104 0.3565 ms 82.6%
  triton_mm_103 0.3679 ms 80.0%
  triton_mm_100 0.3705 ms 79.5%
  triton_mm_105 0.4081 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.6695 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1632 0.5574 ms 100.0%
  triton_mm_1631 0.5611 ms 99.3%
  triton_mm_1633 0.6281 ms 88.7%
  bias_addmm 0.6484 ms 86.0%
  triton_mm_1626 0.6519 ms 85.5%
  addmm 0.6974 ms 79.9%
  triton_mm_1624 0.7009 ms 79.5%
  triton_mm_1628 0.7531 ms 74.0%
  triton_mm_1629 0.7714 ms 72.3%
  triton_mm_1625 0.7738 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 11.4727 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5593 ms 100.0%
  triton_mm_1670 0.5777 ms 96.8%
  mm 0.5852 ms 95.6%
  triton_mm_1671 0.6011 ms 93.0%
  triton_mm_1664 0.6715 ms 83.3%
  triton_mm_1666 0.6825 ms 81.9%
  triton_mm_1662 0.6835 ms 81.8%
  triton_mm_1665 0.7261 ms 77.0%
  triton_mm_1667 0.7330 ms 76.3%
  triton_mm_1663 0.7424 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 9.5596 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2906 ms 100.0%
  triton_mm_1742 0.2974 ms 97.7%
  triton_mm_1741 0.2991 ms 97.1%
  triton_mm_1743 0.3022 ms 96.2%
  triton_mm_1736 0.3506 ms 82.9%
  triton_mm_1734 0.3584 ms 81.1%
  triton_mm_1738 0.3656 ms 79.5%
  triton_mm_1737 0.3813 ms 76.2%
  triton_mm_1739 0.4011 ms 72.4%
  triton_mm_1735 0.4031 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 9.8124 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0153 ms 100.0%
  mm 0.0169 ms 90.9%
  triton_mm_1680 0.0171 ms 89.4%
  triton_mm_1684 0.0207 ms 74.2%
  triton_mm_1675 0.0228 ms 67.4%
  triton_mm_1688 0.0234 ms 65.6%
  triton_mm_1674 0.0242 ms 63.3%
  triton_mm_1679 0.0257 ms 59.7%
  triton_mm_1683 0.0263 ms 58.2%
  triton_mm_1673 0.0266 ms 57.7%
SingleProcess AUTOTUNE benchmarking takes 2.2246 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5444 ms 100.0%
  triton_mm_1650 0.5713 ms 95.3%
  triton_mm_1651 0.5804 ms 93.8%
  triton_mm_1652 0.5962 ms 91.3%
  triton_mm_1647 0.6659 ms 81.7%
  triton_mm_1643 0.6725 ms 81.0%
  triton_mm_1645 0.6746 ms 80.7%
  triton_mm_1646 0.7051 ms 77.2%
  triton_mm_1644 0.7328 ms 74.3%
  triton_mm_1648 0.7397 ms 73.6%
SingleProcess AUTOTUNE benchmarking takes 2.6066 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2784 ms 100.0%
  mm 0.2796 ms 99.6%
  triton_mm_1723 0.2808 ms 99.1%
  triton_mm_1724 0.3187 ms 87.3%
  triton_mm_1715 0.3414 ms 81.5%
  triton_mm_1717 0.3438 ms 81.0%
  triton_mm_1719 0.3482 ms 79.9%
  triton_mm_1716 0.3652 ms 76.2%
  triton_mm_1720 0.3884 ms 71.7%
  triton_mm_1718 0.4236 ms 65.7%
SingleProcess AUTOTUNE benchmarking takes 2.5346 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2254 ms 100.0%
  triton_mm_1836 0.2313 ms 97.4%
  triton_mm_1838 0.2422 ms 93.0%
  mm 0.2573 ms 87.6%
  triton_mm_1833 0.2583 ms 87.2%
  triton_mm_1831 0.2617 ms 86.1%
  triton_mm_1829 0.2630 ms 85.7%
  triton_mm_1832 0.2863 ms 78.7%
  triton_mm_1830 0.2911 ms 77.4%
  triton_mm_1834 0.2969 ms 75.9%
SingleProcess AUTOTUNE benchmarking takes 9.8902 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2913 ms 100.0%
  mm 0.2937 ms 99.2%
  triton_mm_1780 0.2972 ms 98.0%
  triton_mm_1781 0.3030 ms 96.1%
  triton_mm_1776 0.3476 ms 83.8%
  triton_mm_1772 0.3547 ms 82.1%
  triton_mm_1774 0.3589 ms 81.2%
  triton_mm_1775 0.3846 ms 75.8%
  triton_mm_1777 0.3934 ms 74.1%
  triton_mm_1773 0.4021 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5378 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2249 ms 100.0%
  triton_mm_1855 0.2785 ms 80.8%
  triton_mm_1852 0.2818 ms 79.8%
  triton_mm_1850 0.2825 ms 79.6%
  triton_mm_1848 0.2837 ms 79.3%
  triton_mm_1856 0.2848 ms 79.0%
  triton_mm_1857 0.2882 ms 78.0%
  triton_mm_1851 0.3101 ms 72.5%
  triton_mm_1853 0.3240 ms 69.4%
  triton_mm_1849 0.3284 ms 68.5%
SingleProcess AUTOTUNE benchmarking takes 9.7924 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0964 ms 100.0%
  triton_mm_1819 0.0982 ms 98.2%
  triton_mm_1812 0.1048 ms 92.0%
  triton_mm_1818 0.1077 ms 89.5%
  triton_mm_1809 0.1186 ms 81.3%
  triton_mm_1810 0.1194 ms 80.8%
  triton_mm_1814 0.1204 ms 80.1%
  triton_mm_1817 0.1222 ms 78.9%
  triton_mm_1813 0.1261 ms 76.4%
  triton_mm_1815 0.1311 ms 73.6%
SingleProcess AUTOTUNE benchmarking takes 2.4242 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3016 ms 100.0%
  triton_mm_1760 0.3054 ms 98.8%
  triton_mm_1761 0.3119 ms 96.7%
  triton_mm_1762 0.3236 ms 93.2%
  triton_mm_1757 0.3463 ms 87.1%
  triton_mm_1755 0.3514 ms 85.8%
  triton_mm_1753 0.3530 ms 85.4%
  triton_mm_1756 0.3666 ms 82.3%
  triton_mm_1754 0.3881 ms 77.7%
  triton_mm_1758 0.3963 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.5392 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0839 ms 100.0%
  mm 0.0844 ms 99.5%
  triton_mm_1798 0.0855 ms 98.2%
  triton_mm_1795 0.0930 ms 90.2%
  triton_mm_1800 0.0935 ms 89.8%
  triton_mm_1791 0.0954 ms 88.0%
  triton_mm_1793 0.0958 ms 87.6%
  triton_mm_1792 0.1031 ms 81.4%
  triton_mm_1796 0.1047 ms 80.1%
  triton_mm_1794 0.1222 ms 68.6%
SingleProcess AUTOTUNE benchmarking takes 2.4214 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2750 ms 100.0%
  mm 0.2762 ms 99.6%
  triton_mm_1909 0.2796 ms 98.3%
  triton_mm_1910 0.3161 ms 87.0%
  triton_mm_1901 0.3403 ms 80.8%
  triton_mm_1903 0.3435 ms 80.1%
  triton_mm_1905 0.3478 ms 79.1%
  triton_mm_1902 0.3649 ms 75.4%
  triton_mm_1906 0.3874 ms 71.0%
  triton_mm_1904 0.4231 ms 65.0%
SingleProcess AUTOTUNE benchmarking takes 2.5348 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3020 ms 100.0%
  triton_mm_1946 0.3054 ms 98.9%
  triton_mm_1947 0.3130 ms 96.5%
  triton_mm_1948 0.3225 ms 93.6%
  triton_mm_1943 0.3462 ms 87.2%
  triton_mm_1941 0.3514 ms 85.9%
  triton_mm_1939 0.3524 ms 85.7%
  triton_mm_1942 0.3666 ms 82.4%
  triton_mm_1940 0.3882 ms 77.8%
  triton_mm_1944 0.3966 ms 76.2%
SingleProcess AUTOTUNE benchmarking takes 2.5438 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2911 ms 100.0%
  triton_mm_1928 0.2987 ms 97.5%
  triton_mm_1927 0.2995 ms 97.2%
  triton_mm_1929 0.3032 ms 96.0%
  triton_mm_1922 0.3554 ms 81.9%
  triton_mm_1920 0.3589 ms 81.1%
  triton_mm_1924 0.3655 ms 79.6%
  triton_mm_1923 0.3833 ms 75.9%
  triton_mm_1925 0.4016 ms 72.5%
  triton_mm_1921 0.4077 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 2.5501 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2931 ms 100.0%
  triton_mm_1965 0.2937 ms 99.8%
  triton_mm_1966 0.2974 ms 98.5%
  triton_mm_1967 0.3035 ms 96.6%
  triton_mm_1962 0.3491 ms 84.0%
  triton_mm_1958 0.3563 ms 82.3%
  triton_mm_1960 0.3600 ms 81.4%
  triton_mm_1961 0.3857 ms 76.0%
  triton_mm_1963 0.3965 ms 73.9%
  triton_mm_1959 0.4039 ms 72.6%
SingleProcess AUTOTUNE benchmarking takes 2.5506 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2253 ms 100.0%
  triton_mm_2041 0.2802 ms 80.4%
  triton_mm_2036 0.2848 ms 79.1%
  triton_mm_2038 0.2857 ms 78.9%
  triton_mm_2042 0.2861 ms 78.8%
  triton_mm_2034 0.2887 ms 78.1%
  triton_mm_2043 0.2910 ms 77.4%
  triton_mm_2037 0.3131 ms 72.0%
  triton_mm_2039 0.3271 ms 68.9%
  triton_mm_2035 0.3321 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5146 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0973 ms 100.0%
  triton_mm_2005 0.0991 ms 98.2%
  triton_mm_1998 0.1050 ms 92.7%
  triton_mm_2004 0.1084 ms 89.7%
  triton_mm_1995 0.1181 ms 82.4%
  triton_mm_1996 0.1199 ms 81.1%
  triton_mm_2000 0.1203 ms 80.9%
  triton_mm_2003 0.1228 ms 79.2%
  triton_mm_1999 0.1263 ms 77.0%
  triton_mm_2001 0.1310 ms 74.3%
SingleProcess AUTOTUNE benchmarking takes 2.4195 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1985 0.0833 ms 100.0%
  mm 0.0835 ms 99.7%
  triton_mm_1984 0.0848 ms 98.2%
  triton_mm_1981 0.0923 ms 90.2%
  triton_mm_1986 0.0942 ms 88.4%
  triton_mm_1977 0.0955 ms 87.2%
  triton_mm_1979 0.0958 ms 86.9%
  triton_mm_1978 0.1036 ms 80.4%
  triton_mm_1982 0.1053 ms 79.1%
  triton_mm_1980 0.1229 ms 67.7%
SingleProcess AUTOTUNE benchmarking takes 2.4069 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2094 0.2755 ms 100.0%
  mm 0.2765 ms 99.6%
  triton_mm_2095 0.2793 ms 98.6%
  triton_mm_2096 0.3148 ms 87.5%
  triton_mm_2087 0.3410 ms 80.8%
  triton_mm_2089 0.3439 ms 80.1%
  triton_mm_2091 0.3482 ms 79.1%
  triton_mm_2088 0.3651 ms 75.4%
  triton_mm_2092 0.3871 ms 71.2%
  triton_mm_2090 0.4243 ms 64.9%
SingleProcess AUTOTUNE benchmarking takes 2.5317 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3028 ms 100.0%
  triton_mm_2132 0.3047 ms 99.4%
  triton_mm_2133 0.3126 ms 96.9%
  triton_mm_2134 0.3226 ms 93.8%
  triton_mm_2129 0.3460 ms 87.5%
  triton_mm_2127 0.3512 ms 86.2%
  triton_mm_2125 0.3537 ms 85.6%
  triton_mm_2128 0.3676 ms 82.3%
  triton_mm_2126 0.3884 ms 78.0%
  triton_mm_2130 0.3977 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.5346 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2930 ms 100.0%
  triton_mm_2114 0.2986 ms 98.1%
  triton_mm_2113 0.2996 ms 97.8%
  triton_mm_2115 0.3035 ms 96.5%
  triton_mm_2108 0.3558 ms 82.4%
  triton_mm_2106 0.3594 ms 81.5%
  triton_mm_2110 0.3672 ms 79.8%
  triton_mm_2109 0.3832 ms 76.5%
  triton_mm_2111 0.4035 ms 72.6%
  triton_mm_2107 0.4084 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.5370 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2940 ms 100.0%
  triton_mm_2151 0.2946 ms 99.8%
  triton_mm_2152 0.2980 ms 98.7%
  triton_mm_2153 0.3043 ms 96.6%
  triton_mm_2148 0.3486 ms 84.3%
  triton_mm_2144 0.3566 ms 82.4%
  triton_mm_2146 0.3607 ms 81.5%
  triton_mm_2147 0.3864 ms 76.1%
  triton_mm_2149 0.3965 ms 74.1%
  triton_mm_2145 0.4049 ms 72.6%
SingleProcess AUTOTUNE benchmarking takes 2.5331 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2249 ms 100.0%
  triton_mm_2227 0.2798 ms 80.4%
  triton_mm_2222 0.2849 ms 78.9%
  triton_mm_2224 0.2859 ms 78.7%
  triton_mm_2228 0.2866 ms 78.5%
  triton_mm_2220 0.2885 ms 78.0%
  triton_mm_2229 0.2913 ms 77.2%
  triton_mm_2223 0.3135 ms 71.7%
  triton_mm_2225 0.3276 ms 68.7%
  triton_mm_2221 0.3319 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5233 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0974 ms 100.0%
  triton_mm_2191 0.0989 ms 98.5%
  triton_mm_2184 0.1059 ms 92.0%
  triton_mm_2190 0.1085 ms 89.8%
  triton_mm_2181 0.1182 ms 82.4%
  triton_mm_2182 0.1199 ms 81.2%
  triton_mm_2186 0.1210 ms 80.5%
  triton_mm_2189 0.1229 ms 79.3%
  triton_mm_2185 0.1272 ms 76.6%
  triton_mm_2187 0.1302 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 2.4131 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2171 0.0834 ms 100.0%
  mm 0.0836 ms 99.7%
  triton_mm_2170 0.0850 ms 98.2%
  triton_mm_2167 0.0925 ms 90.2%
  triton_mm_2172 0.0944 ms 88.3%
  triton_mm_2163 0.0953 ms 87.5%
  triton_mm_2165 0.0953 ms 87.5%
  triton_mm_2164 0.1031 ms 80.9%
  triton_mm_2168 0.1056 ms 79.0%
  triton_mm_2166 0.1230 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.4109 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2280 0.2766 ms 100.0%
  mm 0.2769 ms 99.9%
  triton_mm_2281 0.2805 ms 98.6%
  triton_mm_2282 0.3163 ms 87.5%
  triton_mm_2273 0.3415 ms 81.0%
  triton_mm_2275 0.3446 ms 80.3%
  triton_mm_2277 0.3476 ms 79.6%
  triton_mm_2274 0.3671 ms 75.4%
  triton_mm_2278 0.3874 ms 71.4%
  triton_mm_2276 0.4243 ms 65.2%
SingleProcess AUTOTUNE benchmarking takes 2.5383 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3030 ms 100.0%
  triton_mm_2318 0.3072 ms 98.6%
  triton_mm_2319 0.3144 ms 96.4%
  triton_mm_2320 0.3233 ms 93.7%
  triton_mm_2315 0.3476 ms 87.2%
  triton_mm_2313 0.3533 ms 85.8%
  triton_mm_2311 0.3537 ms 85.7%
  triton_mm_2314 0.3688 ms 82.2%
  triton_mm_2312 0.3898 ms 77.8%
  triton_mm_2316 0.3980 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.5371 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2928 ms 100.0%
  triton_mm_2300 0.2993 ms 97.8%
  triton_mm_2299 0.3001 ms 97.6%
  triton_mm_2301 0.3048 ms 96.0%
  triton_mm_2294 0.3576 ms 81.9%
  triton_mm_2292 0.3595 ms 81.4%
  triton_mm_2296 0.3678 ms 79.6%
  triton_mm_2295 0.3856 ms 75.9%
  triton_mm_2297 0.4034 ms 72.6%
  triton_mm_2293 0.4090 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.5397 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2337 0.2937 ms 100.0%
  mm 0.2944 ms 99.8%
  triton_mm_2338 0.2977 ms 98.7%
  triton_mm_2339 0.3037 ms 96.7%
  triton_mm_2334 0.3496 ms 84.0%
  triton_mm_2330 0.3572 ms 82.2%
  triton_mm_2332 0.3619 ms 81.2%
  triton_mm_2333 0.3874 ms 75.8%
  triton_mm_2335 0.3972 ms 73.9%
  triton_mm_2331 0.4055 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5400 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2261 ms 100.0%
  triton_mm_2413 0.2795 ms 80.9%
  triton_mm_2408 0.2860 ms 79.1%
  triton_mm_2414 0.2863 ms 79.0%
  triton_mm_2410 0.2877 ms 78.6%
  triton_mm_2406 0.2892 ms 78.2%
  triton_mm_2415 0.2915 ms 77.6%
  triton_mm_2409 0.3148 ms 71.8%
  triton_mm_2411 0.3275 ms 69.0%
  triton_mm_2407 0.3329 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.5192 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0968 ms 100.0%
  triton_mm_2377 0.0991 ms 97.6%
  triton_mm_2370 0.1060 ms 91.3%
  triton_mm_2376 0.1085 ms 89.2%
  triton_mm_2367 0.1182 ms 81.9%
  triton_mm_2368 0.1199 ms 80.7%
  triton_mm_2372 0.1204 ms 80.4%
  triton_mm_2375 0.1229 ms 78.7%
  triton_mm_2371 0.1272 ms 76.0%
  triton_mm_2373 0.1310 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.4199 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0837 ms 100.0%
  triton_mm_2357 0.0842 ms 99.4%
  triton_mm_2356 0.0856 ms 97.8%
  triton_mm_2353 0.0936 ms 89.5%
  triton_mm_2358 0.0937 ms 89.3%
  triton_mm_2349 0.0951 ms 88.0%
  triton_mm_2351 0.0955 ms 87.7%
  triton_mm_2350 0.1027 ms 81.5%
  triton_mm_2354 0.1050 ms 79.7%
  triton_mm_2352 0.1223 ms 68.5%
SingleProcess AUTOTUNE benchmarking takes 2.4116 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2916 ms 100.0%
  triton_mm_2486 0.2992 ms 97.4%
  triton_mm_2485 0.2995 ms 97.3%
  triton_mm_2487 0.3048 ms 95.7%
  triton_mm_2480 0.3569 ms 81.7%
  triton_mm_2478 0.3589 ms 81.2%
  triton_mm_2482 0.3674 ms 79.4%
  triton_mm_2481 0.3844 ms 75.8%
  triton_mm_2483 0.4027 ms 72.4%
  triton_mm_2479 0.4091 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 2.5470 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2523 0.2935 ms 100.0%
  mm 0.2948 ms 99.6%
  triton_mm_2524 0.2983 ms 98.4%
  triton_mm_2525 0.3044 ms 96.4%
  triton_mm_2520 0.3511 ms 83.6%
  triton_mm_2516 0.3576 ms 82.1%
  triton_mm_2518 0.3618 ms 81.1%
  triton_mm_2519 0.3882 ms 75.6%
  triton_mm_2521 0.3968 ms 74.0%
  triton_mm_2517 0.4039 ms 72.7%
SingleProcess AUTOTUNE benchmarking takes 2.5434 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0842 ms 100.0%
  triton_mm_2543 0.0843 ms 100.0%
  triton_mm_2542 0.0856 ms 98.4%
  triton_mm_2539 0.0932 ms 90.4%
  triton_mm_2544 0.0937 ms 89.9%
  triton_mm_2535 0.0950 ms 88.7%
  triton_mm_2537 0.0956 ms 88.1%
  triton_mm_2536 0.1026 ms 82.1%
  triton_mm_2540 0.1050 ms 80.2%
  triton_mm_2538 0.1220 ms 69.0%
SingleProcess AUTOTUNE benchmarking takes 2.4107 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2729 0.0833 ms 100.0%
  mm 0.0835 ms 99.8%
  triton_mm_2728 0.0849 ms 98.2%
  triton_mm_2725 0.0930 ms 89.6%
  triton_mm_2730 0.0942 ms 88.4%
  triton_mm_2721 0.0954 ms 87.3%
  triton_mm_2723 0.0960 ms 86.8%
  triton_mm_2722 0.1032 ms 80.7%
  triton_mm_2726 0.1048 ms 79.5%
  triton_mm_2724 0.1228 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.4218 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2915 0.0833 ms 100.0%
  mm 0.0841 ms 99.1%
  triton_mm_2914 0.0854 ms 97.5%
  triton_mm_2911 0.0929 ms 89.7%
  triton_mm_2916 0.0942 ms 88.5%
  triton_mm_2907 0.0946 ms 88.1%
  triton_mm_2909 0.0952 ms 87.5%
  triton_mm_2908 0.1025 ms 81.3%
  triton_mm_2912 0.1048 ms 79.5%
  triton_mm_2910 0.1220 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 2.4213 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0276 ms 100.0%
  triton_mm_4879 0.0501 ms 55.2%
  triton_mm_4872 0.0509 ms 54.3%
  triton_mm_4870 0.0565 ms 48.9%
  triton_mm_4871 0.0639 ms 43.3%
  triton_mm_4878 0.0668 ms 41.4%
  triton_mm_4875 0.0696 ms 39.7%
  triton_mm_4883 0.0735 ms 37.6%
  triton_mm_4884 0.0736 ms 37.5%
  triton_mm_4877 0.0781 ms 35.4%
SingleProcess AUTOTUNE benchmarking takes 6.2858 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_6 0.0263 ms 100.0%
  triton_mm_7 0.0265 ms 99.4%
  triton_mm_9 0.0265 ms 99.4%
  triton_mm_8 0.0274 ms 96.1%
  triton_mm_12 0.0274 ms 96.1%
  triton_mm_11 0.0275 ms 95.8%
  triton_mm_4 0.0279 ms 94.4%
  triton_mm_5 0.0280 ms 93.9%
  triton_mm_13 0.0284 ms 92.7%
  triton_mm_14 0.0287 ms 91.6%
SingleProcess AUTOTUNE benchmarking takes 2.0880 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2184 ms 100.0%
  triton_mm_51 0.2246 ms 97.3%
  triton_mm_52 0.2526 ms 86.5%
  triton_mm_45 0.2623 ms 83.3%
  triton_mm_47 0.2713 ms 80.5%
  triton_mm_43 0.2753 ms 79.3%
  bias_addmm 0.2994 ms 73.0%
  triton_mm_44 0.3063 ms 71.3%
  triton_mm_48 0.3083 ms 70.9%
  addmm 0.3220 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5895 seconds and 0.0172 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0892 ms 100.0%
  triton_mm_69 0.0902 ms 98.9%
  bias_addmm 0.0964 ms 92.6%
  triton_mm_64 0.0972 ms 91.8%
  triton_mm_66 0.0977 ms 91.3%
  triton_mm_71 0.1001 ms 89.1%
  triton_mm_62 0.1005 ms 88.7%
  addmm 0.1098 ms 81.3%
  triton_mm_63 0.1106 ms 80.7%
  triton_mm_67 0.1121 ms 79.6%
SingleProcess AUTOTUNE benchmarking takes 2.5036 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2892 ms 100.0%
  triton_mm_89 0.2960 ms 97.7%
  bias_addmm 0.3250 ms 89.0%
  triton_mm_90 0.3342 ms 86.5%
  triton_mm_83 0.3420 ms 84.6%
  triton_mm_81 0.3585 ms 80.7%
  triton_mm_85 0.3638 ms 79.5%
  triton_mm_82 0.4008 ms 72.2%
  triton_mm_86 0.4130 ms 70.0%
  addmm 0.4174 ms 69.3%
SingleProcess AUTOTUNE benchmarking takes 2.5865 seconds and 0.0042 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2883 ms 100.0%
  triton_mm_108 0.3002 ms 96.0%
  triton_mm_107 0.3088 ms 93.4%
  triton_mm_109 0.3211 ms 89.8%
  addmm 0.3233 ms 89.2%
  triton_mm_102 0.3496 ms 82.5%
  triton_mm_104 0.3514 ms 82.0%
  triton_mm_100 0.3652 ms 78.9%
  triton_mm_103 0.3658 ms 78.8%
  triton_mm_105 0.4030 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 2.6649 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1606 0.0141 ms 100.0%
  triton_mm_1602 0.0147 ms 95.9%
  triton_mm_1610 0.0162 ms 87.0%
  mm 0.0168 ms 84.0%
  triton_mm_1614 0.0169 ms 83.2%
  triton_mm_1605 0.0175 ms 80.3%
  triton_mm_1600 0.0176 ms 79.9%
  triton_mm_1599 0.0179 ms 78.9%
  triton_mm_1601 0.0180 ms 78.0%
  triton_mm_1612 0.0197 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 2.1691 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5535 ms 100.0%
  triton_mm_1631 0.5538 ms 99.9%
  triton_mm_1632 0.5950 ms 93.0%
  triton_mm_1626 0.6619 ms 83.6%
  triton_mm_1628 0.6849 ms 80.8%
  addmm 0.6852 ms 80.8%
  triton_mm_1624 0.7114 ms 77.8%
  triton_mm_1633 0.7278 ms 76.1%
  triton_mm_1629 0.7766 ms 71.3%
  triton_mm_1625 0.7843 ms 70.6%
SingleProcess AUTOTUNE benchmarking takes 11.7238 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5476 ms 100.0%
  triton_mm_1670 0.5666 ms 96.6%
  mm 0.5851 ms 93.6%
  triton_mm_1671 0.5954 ms 92.0%
  triton_mm_1664 0.6637 ms 82.5%
  triton_mm_1666 0.6900 ms 79.4%
  triton_mm_1662 0.6906 ms 79.3%
  triton_mm_1667 0.7163 ms 76.5%
  triton_mm_1665 0.7248 ms 75.5%
  triton_mm_1663 0.7387 ms 74.1%
SingleProcess AUTOTUNE benchmarking takes 2.5582 seconds and 0.0013 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2848 ms 100.0%
  triton_mm_1742 0.2897 ms 98.3%
  triton_mm_1741 0.2919 ms 97.6%
  triton_mm_1743 0.2950 ms 96.5%
  triton_mm_1736 0.3457 ms 82.4%
  triton_mm_1734 0.3474 ms 82.0%
  triton_mm_1738 0.3557 ms 80.1%
  triton_mm_1737 0.3737 ms 76.2%
  triton_mm_1739 0.3973 ms 71.7%
  triton_mm_1735 0.3996 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 9.6656 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1698 0.0111 ms 100.0%
  triton_mm_1700 0.0111 ms 100.0%
  triton_mm_1694 0.0112 ms 99.4%
  triton_mm_1699 0.0116 ms 96.4%
  triton_mm_1695 0.0116 ms 96.1%
  triton_mm_1702 0.0117 ms 94.8%
  triton_mm_1704 0.0118 ms 94.6%
  triton_mm_1697 0.0124 ms 89.6%
  triton_mm_1701 0.0125 ms 89.0%
  triton_mm_1692 0.0127 ms 87.9%
SingleProcess AUTOTUNE benchmarking takes 2.2353 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1680 0.0164 ms 100.0%
  triton_mm_1676 0.0168 ms 97.1%
  mm 0.0172 ms 95.3%
  triton_mm_1684 0.0201 ms 81.4%
  triton_mm_1688 0.0234 ms 69.9%
  triton_mm_1675 0.0234 ms 69.8%
  triton_mm_1674 0.0238 ms 68.6%
  triton_mm_1679 0.0253 ms 64.5%
  triton_mm_1683 0.0267 ms 61.2%
  triton_mm_1673 0.0272 ms 60.0%
SingleProcess AUTOTUNE benchmarking takes 2.2269 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5355 ms 100.0%
  triton_mm_1650 0.5588 ms 95.8%
  triton_mm_1651 0.5676 ms 94.4%
  triton_mm_1652 0.5829 ms 91.9%
  triton_mm_1647 0.6577 ms 81.4%
  triton_mm_1645 0.6639 ms 80.7%
  triton_mm_1643 0.6674 ms 80.2%
  triton_mm_1646 0.6822 ms 78.5%
  triton_mm_1644 0.7228 ms 74.1%
  triton_mm_1648 0.7346 ms 72.9%
SingleProcess AUTOTUNE benchmarking takes 9.8123 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2710 ms 100.0%
  triton_mm_1723 0.2777 ms 97.6%
  mm 0.2778 ms 97.5%
  triton_mm_1724 0.3164 ms 85.6%
  triton_mm_1715 0.3384 ms 80.1%
  triton_mm_1717 0.3393 ms 79.9%
  triton_mm_1719 0.3462 ms 78.3%
  triton_mm_1716 0.3601 ms 75.2%
  triton_mm_1720 0.3823 ms 70.9%
  triton_mm_1718 0.4228 ms 64.1%
SingleProcess AUTOTUNE benchmarking takes 2.5348 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2197 ms 100.0%
  triton_mm_1836 0.2258 ms 97.3%
  triton_mm_1838 0.2377 ms 92.4%
  triton_mm_1833 0.2527 ms 86.9%
  mm 0.2570 ms 85.5%
  triton_mm_1829 0.2613 ms 84.1%
  triton_mm_1831 0.2620 ms 83.8%
  triton_mm_1830 0.2900 ms 75.8%
  triton_mm_1834 0.2908 ms 75.5%
  triton_mm_1832 0.2921 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5016 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2853 ms 100.0%
  mm 0.2866 ms 99.5%
  triton_mm_1780 0.2904 ms 98.2%
  triton_mm_1781 0.2939 ms 97.1%
  triton_mm_1776 0.3400 ms 83.9%
  triton_mm_1772 0.3453 ms 82.6%
  triton_mm_1774 0.3508 ms 81.3%
  triton_mm_1775 0.3802 ms 75.0%
  triton_mm_1777 0.3839 ms 74.3%
  triton_mm_1773 0.3995 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 9.8068 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2215 ms 100.0%
  triton_mm_1855 0.2737 ms 80.9%
  triton_mm_1850 0.2780 ms 79.7%
  triton_mm_1852 0.2801 ms 79.1%
  triton_mm_1856 0.2805 ms 78.9%
  triton_mm_1848 0.2810 ms 78.8%
  triton_mm_1857 0.2837 ms 78.1%
  triton_mm_1851 0.3043 ms 72.8%
  triton_mm_1853 0.3158 ms 70.1%
  triton_mm_1849 0.3210 ms 69.0%
SingleProcess AUTOTUNE benchmarking takes 9.8725 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0986 ms 100.0%
  mm 0.1014 ms 97.2%
  triton_mm_1812 0.1056 ms 93.3%
  triton_mm_1818 0.1093 ms 90.2%
  triton_mm_1809 0.1186 ms 83.1%
  triton_mm_1810 0.1201 ms 82.1%
  triton_mm_1814 0.1203 ms 81.9%
  triton_mm_1817 0.1241 ms 79.4%
  triton_mm_1813 0.1266 ms 77.8%
  triton_mm_1815 0.1306 ms 75.5%
SingleProcess AUTOTUNE benchmarking takes 9.6699 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2931 ms 100.0%
  triton_mm_1760 0.2982 ms 98.3%
  triton_mm_1761 0.3060 ms 95.8%
  triton_mm_1762 0.3165 ms 92.6%
  triton_mm_1757 0.3392 ms 86.4%
  triton_mm_1753 0.3449 ms 85.0%
  triton_mm_1755 0.3464 ms 84.6%
  triton_mm_1756 0.3640 ms 80.5%
  triton_mm_1754 0.3841 ms 76.3%
  triton_mm_1758 0.3899 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5369 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0828 ms 100.0%
  mm 0.0848 ms 97.7%
  triton_mm_1798 0.0852 ms 97.2%
  triton_mm_1795 0.0913 ms 90.7%
  triton_mm_1800 0.0942 ms 87.9%
  triton_mm_1791 0.0946 ms 87.6%
  triton_mm_1793 0.0948 ms 87.3%
  triton_mm_1792 0.1015 ms 81.6%
  triton_mm_1796 0.1054 ms 78.5%
  triton_mm_1794 0.1229 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 2.4119 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2670 ms 100.0%
  mm 0.2709 ms 98.5%
  triton_mm_1909 0.2728 ms 97.9%
  triton_mm_1910 0.3147 ms 84.8%
  triton_mm_1901 0.3375 ms 79.1%
  triton_mm_1903 0.3399 ms 78.6%
  triton_mm_1905 0.3448 ms 77.4%
  triton_mm_1902 0.3630 ms 73.6%
  triton_mm_1906 0.3846 ms 69.4%
  triton_mm_1904 0.4231 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.5323 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2931 ms 100.0%
  triton_mm_1946 0.2972 ms 98.6%
  triton_mm_1947 0.3048 ms 96.2%
  triton_mm_1948 0.3153 ms 92.9%
  triton_mm_1943 0.3405 ms 86.1%
  triton_mm_1939 0.3475 ms 84.3%
  triton_mm_1941 0.3478 ms 84.3%
  triton_mm_1942 0.3655 ms 80.2%
  triton_mm_1940 0.3856 ms 76.0%
  triton_mm_1944 0.3902 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5395 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2849 ms 100.0%
  triton_mm_1928 0.2925 ms 97.4%
  triton_mm_1927 0.2929 ms 97.3%
  triton_mm_1929 0.2998 ms 95.0%
  triton_mm_1922 0.3489 ms 81.7%
  triton_mm_1920 0.3520 ms 80.9%
  triton_mm_1924 0.3616 ms 78.8%
  triton_mm_1923 0.3779 ms 75.4%
  triton_mm_1925 0.3974 ms 71.7%
  triton_mm_1921 0.4031 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.5490 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2839 ms 100.0%
  mm 0.2862 ms 99.2%
  triton_mm_1966 0.2921 ms 97.2%
  triton_mm_1967 0.2970 ms 95.6%
  triton_mm_1962 0.3452 ms 82.2%
  triton_mm_1958 0.3511 ms 80.9%
  triton_mm_1960 0.3525 ms 80.5%
  triton_mm_1961 0.3811 ms 74.5%
  triton_mm_1963 0.3895 ms 72.9%
  triton_mm_1959 0.3975 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 2.5364 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2206 ms 100.0%
  triton_mm_2041 0.2744 ms 80.4%
  triton_mm_2036 0.2784 ms 79.2%
  triton_mm_2042 0.2794 ms 79.0%
  triton_mm_2038 0.2816 ms 78.3%
  triton_mm_2043 0.2832 ms 77.9%
  triton_mm_2034 0.2836 ms 77.8%
  triton_mm_2037 0.3065 ms 72.0%
  triton_mm_2039 0.3179 ms 69.4%
  triton_mm_2035 0.3232 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 2.5182 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2005 0.0986 ms 100.0%
  mm 0.1015 ms 97.1%
  triton_mm_1998 0.1049 ms 94.0%
  triton_mm_2004 0.1088 ms 90.6%
  triton_mm_1995 0.1178 ms 83.7%
  triton_mm_1996 0.1208 ms 81.6%
  triton_mm_2000 0.1212 ms 81.3%
  triton_mm_2003 0.1235 ms 79.8%
  triton_mm_1999 0.1266 ms 77.8%
  triton_mm_2001 0.1307 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.4186 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1985 0.0837 ms 100.0%
  mm 0.0842 ms 99.5%
  triton_mm_1984 0.0844 ms 99.1%
  triton_mm_1981 0.0922 ms 90.8%
  triton_mm_1986 0.0934 ms 89.6%
  triton_mm_1977 0.0947 ms 88.4%
  triton_mm_1979 0.0949 ms 88.2%
  triton_mm_1978 0.1015 ms 82.4%
  triton_mm_1982 0.1044 ms 80.1%
  triton_mm_1975 0.1236 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.4097 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2184 ms 100.0%
  triton_mm_2023 0.2202 ms 99.2%
  triton_mm_2022 0.2266 ms 96.4%
  triton_mm_2024 0.2395 ms 91.2%
  triton_mm_2019 0.2539 ms 86.0%
  triton_mm_2017 0.2593 ms 84.2%
  triton_mm_2015 0.2603 ms 83.9%
  triton_mm_2016 0.2865 ms 76.2%
  triton_mm_2018 0.2879 ms 75.8%
  triton_mm_2020 0.2942 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.5128 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2094 0.2703 ms 100.0%
  mm 0.2725 ms 99.2%
  triton_mm_2095 0.2759 ms 98.0%
  triton_mm_2096 0.3141 ms 86.1%
  triton_mm_2087 0.3371 ms 80.2%
  triton_mm_2089 0.3404 ms 79.4%
  triton_mm_2091 0.3412 ms 79.2%
  triton_mm_2088 0.3674 ms 73.6%
  triton_mm_2092 0.3834 ms 70.5%
  triton_mm_2090 0.4225 ms 64.0%
SingleProcess AUTOTUNE benchmarking takes 2.5352 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2922 ms 100.0%
  triton_mm_2132 0.2976 ms 98.2%
  triton_mm_2133 0.3064 ms 95.3%
  triton_mm_2134 0.3162 ms 92.4%
  triton_mm_2129 0.3402 ms 85.9%
  triton_mm_2127 0.3466 ms 84.3%
  triton_mm_2125 0.3487 ms 83.8%
  triton_mm_2128 0.3670 ms 79.6%
  triton_mm_2126 0.3890 ms 75.1%
  triton_mm_2130 0.3916 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.5324 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2849 ms 100.0%
  triton_mm_2113 0.2935 ms 97.0%
  triton_mm_2114 0.2936 ms 97.0%
  triton_mm_2115 0.2995 ms 95.1%
  triton_mm_2108 0.3488 ms 81.7%
  triton_mm_2106 0.3532 ms 80.7%
  triton_mm_2110 0.3611 ms 78.9%
  triton_mm_2109 0.3780 ms 75.4%
  triton_mm_2111 0.4002 ms 71.2%
  triton_mm_2107 0.4019 ms 70.9%
SingleProcess AUTOTUNE benchmarking takes 2.5366 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2151 0.2854 ms 100.0%
  mm 0.2860 ms 99.8%
  triton_mm_2152 0.2901 ms 98.4%
  triton_mm_2153 0.2959 ms 96.4%
  triton_mm_2148 0.3458 ms 82.5%
  triton_mm_2144 0.3512 ms 81.3%
  triton_mm_2146 0.3535 ms 80.7%
  triton_mm_2147 0.3818 ms 74.8%
  triton_mm_2149 0.3911 ms 73.0%
  triton_mm_2145 0.3972 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.5395 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2191 0.0985 ms 100.0%
  mm 0.1013 ms 97.2%
  triton_mm_2184 0.1044 ms 94.4%
  triton_mm_2190 0.1084 ms 90.8%
  triton_mm_2181 0.1187 ms 83.0%
  triton_mm_2182 0.1193 ms 82.5%
  triton_mm_2186 0.1208 ms 81.6%
  triton_mm_2189 0.1224 ms 80.5%
  triton_mm_2185 0.1262 ms 78.1%
  triton_mm_2187 0.1306 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.4173 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2171 0.0828 ms 100.0%
  mm 0.0830 ms 99.8%
  triton_mm_2170 0.0852 ms 97.2%
  triton_mm_2167 0.0921 ms 89.9%
  triton_mm_2172 0.0940 ms 88.1%
  triton_mm_2163 0.0947 ms 87.5%
  triton_mm_2165 0.0947 ms 87.4%
  triton_mm_2164 0.1014 ms 81.7%
  triton_mm_2168 0.1045 ms 79.2%
  triton_mm_2161 0.1236 ms 67.0%
SingleProcess AUTOTUNE benchmarking takes 2.4085 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2181 ms 100.0%
  triton_mm_2209 0.2202 ms 99.1%
  triton_mm_2208 0.2266 ms 96.3%
  triton_mm_2210 0.2381 ms 91.6%
  triton_mm_2205 0.2548 ms 85.6%
  triton_mm_2201 0.2588 ms 84.3%
  triton_mm_2203 0.2589 ms 84.2%
  triton_mm_2202 0.2889 ms 75.5%
  triton_mm_2204 0.2894 ms 75.4%
  triton_mm_2206 0.2938 ms 74.3%
SingleProcess AUTOTUNE benchmarking takes 2.5091 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2718 ms 100.0%
  triton_mm_2280 0.2718 ms 100.0%
  triton_mm_2281 0.2765 ms 98.3%
  triton_mm_2282 0.3127 ms 86.9%
  triton_mm_2273 0.3387 ms 80.3%
  triton_mm_2275 0.3388 ms 80.2%
  triton_mm_2277 0.3410 ms 79.7%
  triton_mm_2274 0.3652 ms 74.4%
  triton_mm_2278 0.3833 ms 70.9%
  triton_mm_2276 0.4242 ms 64.1%
SingleProcess AUTOTUNE benchmarking takes 2.5404 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2909 ms 100.0%
  triton_mm_2318 0.2976 ms 97.7%
  triton_mm_2319 0.3058 ms 95.1%
  triton_mm_2320 0.3159 ms 92.1%
  triton_mm_2315 0.3394 ms 85.7%
  triton_mm_2313 0.3457 ms 84.1%
  triton_mm_2311 0.3473 ms 83.8%
  triton_mm_2314 0.3665 ms 79.4%
  triton_mm_2312 0.3859 ms 75.4%
  triton_mm_2316 0.3904 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.5494 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2849 ms 100.0%
  triton_mm_2299 0.2919 ms 97.6%
  triton_mm_2300 0.2930 ms 97.2%
  triton_mm_2301 0.2984 ms 95.5%
  triton_mm_2294 0.3495 ms 81.5%
  triton_mm_2292 0.3526 ms 80.8%
  triton_mm_2296 0.3603 ms 79.1%
  triton_mm_2295 0.3794 ms 75.1%
  triton_mm_2297 0.3990 ms 71.4%
  triton_mm_2293 0.4040 ms 70.5%
SingleProcess AUTOTUNE benchmarking takes 2.5495 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2848 ms 100.0%
  triton_mm_2337 0.2871 ms 99.2%
  triton_mm_2338 0.2895 ms 98.4%
  triton_mm_2339 0.2968 ms 95.9%
  triton_mm_2334 0.3439 ms 82.8%
  triton_mm_2330 0.3487 ms 81.7%
  triton_mm_2332 0.3545 ms 80.3%
  triton_mm_2333 0.3813 ms 74.7%
  triton_mm_2335 0.3883 ms 73.3%
  triton_mm_2331 0.4006 ms 71.1%
SingleProcess AUTOTUNE benchmarking takes 2.5494 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2377 0.0993 ms 100.0%
  mm 0.1007 ms 98.6%
  triton_mm_2370 0.1044 ms 95.2%
  triton_mm_2376 0.1085 ms 91.6%
  triton_mm_2367 0.1187 ms 83.7%
  triton_mm_2368 0.1192 ms 83.4%
  triton_mm_2372 0.1208 ms 82.2%
  triton_mm_2375 0.1224 ms 81.2%
  triton_mm_2371 0.1262 ms 78.7%
  triton_mm_2373 0.1305 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.4425 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0830 ms 100.0%
  triton_mm_2357 0.0836 ms 99.3%
  triton_mm_2356 0.0846 ms 98.1%
  triton_mm_2353 0.0921 ms 90.1%
  triton_mm_2358 0.0933 ms 88.9%
  triton_mm_2349 0.0946 ms 87.7%
  triton_mm_2351 0.0947 ms 87.6%
  triton_mm_2350 0.1014 ms 81.8%
  triton_mm_2354 0.1045 ms 79.4%
  triton_mm_2347 0.1236 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 2.4283 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2181 ms 100.0%
  triton_mm_2395 0.2190 ms 99.6%
  triton_mm_2394 0.2262 ms 96.4%
  triton_mm_2396 0.2380 ms 91.6%
  triton_mm_2391 0.2533 ms 86.1%
  triton_mm_2387 0.2580 ms 84.5%
  triton_mm_2389 0.2588 ms 84.3%
  triton_mm_2388 0.2883 ms 75.6%
  triton_mm_2390 0.2908 ms 75.0%
  triton_mm_2392 0.2941 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.5215 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2848 ms 100.0%
  triton_mm_2523 0.2871 ms 99.2%
  triton_mm_2524 0.2904 ms 98.1%
  triton_mm_2525 0.2958 ms 96.3%
  triton_mm_2520 0.3423 ms 83.2%
  triton_mm_2516 0.3510 ms 81.2%
  triton_mm_2518 0.3523 ms 80.9%
  triton_mm_2519 0.3822 ms 74.5%
  triton_mm_2521 0.3877 ms 73.5%
  triton_mm_2517 0.3971 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.5499 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0829 ms 100.0%
  triton_mm_2543 0.0837 ms 99.0%
  triton_mm_2542 0.0845 ms 98.1%
  triton_mm_2539 0.0922 ms 90.0%
  triton_mm_2544 0.0933 ms 88.8%
  triton_mm_2535 0.0938 ms 88.4%
  triton_mm_2537 0.0948 ms 87.5%
  triton_mm_2536 0.1022 ms 81.1%
  triton_mm_2540 0.1045 ms 79.3%
  triton_mm_2538 0.1244 ms 66.6%
SingleProcess AUTOTUNE benchmarking takes 2.4310 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2180 ms 100.0%
  triton_mm_2581 0.2198 ms 99.2%
  triton_mm_2580 0.2263 ms 96.3%
  triton_mm_2582 0.2381 ms 91.5%
  triton_mm_2577 0.2524 ms 86.3%
  triton_mm_2573 0.2578 ms 84.5%
  triton_mm_2575 0.2579 ms 84.5%
  triton_mm_2574 0.2869 ms 76.0%
  triton_mm_2576 0.2898 ms 75.2%
  triton_mm_2578 0.2935 ms 74.3%
SingleProcess AUTOTUNE benchmarking takes 2.5166 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2709 0.2851 ms 100.0%
  mm 0.2858 ms 99.7%
  triton_mm_2710 0.2893 ms 98.5%
  triton_mm_2711 0.2963 ms 96.2%
  triton_mm_2706 0.3416 ms 83.4%
  triton_mm_2702 0.3490 ms 81.7%
  triton_mm_2704 0.3528 ms 80.8%
  triton_mm_2705 0.3807 ms 74.9%
  triton_mm_2707 0.3876 ms 73.5%
  triton_mm_2703 0.3953 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.5458 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2729 0.0836 ms 100.0%
  mm 0.0838 ms 99.8%
  triton_mm_2728 0.0845 ms 98.9%
  triton_mm_2725 0.0912 ms 91.7%
  triton_mm_2730 0.0943 ms 88.7%
  triton_mm_2721 0.0945 ms 88.5%
  triton_mm_2723 0.0948 ms 88.2%
  triton_mm_2722 0.1014 ms 82.5%
  triton_mm_2726 0.1054 ms 79.3%
  triton_mm_2724 0.1245 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 2.4362 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2163 ms 100.0%
  triton_mm_2767 0.2189 ms 98.8%
  triton_mm_2766 0.2275 ms 95.1%
  triton_mm_2768 0.2383 ms 90.7%
  triton_mm_2763 0.2514 ms 86.0%
  triton_mm_2761 0.2580 ms 83.8%
  triton_mm_2759 0.2581 ms 83.8%
  triton_mm_2762 0.2851 ms 75.9%
  triton_mm_2760 0.2871 ms 75.3%
  triton_mm_2764 0.2932 ms 73.8%
SingleProcess AUTOTUNE benchmarking takes 2.5210 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0278 ms 100.0%
  triton_mm_4879 0.0497 ms 55.8%
  triton_mm_4872 0.0507 ms 54.8%
  triton_mm_4870 0.0567 ms 49.0%
  triton_mm_4871 0.0641 ms 43.3%
  triton_mm_4878 0.0678 ms 41.0%
  triton_mm_4875 0.0697 ms 39.8%
  triton_mm_4884 0.0732 ms 37.9%
  triton_mm_4883 0.0740 ms 37.5%
  triton_mm_4877 0.0775 ms 35.8%
SingleProcess AUTOTUNE benchmarking takes 6.2798 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_7 0.0252 ms 100.0%
  triton_mm_6 0.0261 ms 96.4%
  triton_mm_12 0.0261 ms 96.4%
  triton_mm_8 0.0261 ms 96.3%
  triton_mm_9 0.0264 ms 95.3%
  triton_mm_11 0.0272 ms 92.5%
  triton_mm_4 0.0276 ms 91.3%
  triton_mm_15 0.0278 ms 90.6%
  triton_mm_3 0.0279 ms 90.1%
  triton_mm_5 0.0281 ms 89.5%
SingleProcess AUTOTUNE benchmarking takes 2.0799 seconds and 0.0007 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2208 ms 100.0%
  triton_mm_51 0.2269 ms 97.3%
  triton_mm_52 0.2541 ms 86.9%
  triton_mm_45 0.2646 ms 83.4%
  triton_mm_47 0.2728 ms 80.9%
  triton_mm_43 0.2765 ms 79.8%
  bias_addmm 0.2996 ms 73.7%
  triton_mm_44 0.3072 ms 71.9%
  triton_mm_48 0.3102 ms 71.2%
  addmm 0.3220 ms 68.6%
SingleProcess AUTOTUNE benchmarking takes 2.6830 seconds and 0.0177 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0900 ms 100.0%
  triton_mm_69 0.0905 ms 99.4%
  bias_addmm 0.0969 ms 92.8%
  triton_mm_66 0.0978 ms 92.0%
  triton_mm_64 0.0981 ms 91.7%
  triton_mm_71 0.1001 ms 89.9%
  triton_mm_62 0.1014 ms 88.7%
  addmm 0.1106 ms 81.3%
  triton_mm_63 0.1108 ms 81.1%
  triton_mm_67 0.1130 ms 79.6%
SingleProcess AUTOTUNE benchmarking takes 2.5180 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2941 ms 100.0%
  triton_mm_89 0.2972 ms 98.9%
  bias_addmm 0.3252 ms 90.4%
  triton_mm_90 0.3345 ms 87.9%
  triton_mm_83 0.3442 ms 85.5%
  triton_mm_81 0.3635 ms 80.9%
  triton_mm_85 0.3659 ms 80.4%
  triton_mm_82 0.4016 ms 73.2%
  triton_mm_86 0.4126 ms 71.3%
  addmm 0.4174 ms 70.5%
SingleProcess AUTOTUNE benchmarking takes 2.6072 seconds and 0.0095 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2926 ms 100.0%
  triton_mm_108 0.3049 ms 96.0%
  triton_mm_107 0.3152 ms 92.8%
  triton_mm_109 0.3249 ms 90.1%
  addmm 0.3300 ms 88.7%
  triton_mm_104 0.3568 ms 82.0%
  triton_mm_102 0.3583 ms 81.7%
  triton_mm_100 0.3710 ms 78.9%
  triton_mm_103 0.3712 ms 78.8%
  triton_mm_105 0.4048 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.6653 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_181 0.2911 ms 100.0%
  triton_mm_182 0.2944 ms 98.9%
  bias_addmm 0.3257 ms 89.4%
  triton_mm_183 0.3344 ms 87.0%
  triton_mm_176 0.3399 ms 85.6%
  triton_mm_174 0.3598 ms 80.9%
  triton_mm_178 0.3624 ms 80.3%
  addmm 0.3706 ms 78.5%
  triton_mm_175 0.3994 ms 72.9%
  triton_mm_179 0.4089 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.6382 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_274 0.2908 ms 100.0%
  triton_mm_275 0.2934 ms 99.1%
  bias_addmm 0.3256 ms 89.3%
  triton_mm_276 0.3312 ms 87.8%
  triton_mm_269 0.3401 ms 85.5%
  triton_mm_267 0.3588 ms 81.1%
  triton_mm_271 0.3613 ms 80.5%
  triton_mm_268 0.3969 ms 73.3%
  triton_mm_272 0.4079 ms 71.3%
  addmm 0.4168 ms 69.8%
SingleProcess AUTOTUNE benchmarking takes 2.6479 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_367 0.2900 ms 100.0%
  triton_mm_368 0.2936 ms 98.8%
  bias_addmm 0.3257 ms 89.0%
  triton_mm_369 0.3324 ms 87.2%
  triton_mm_362 0.3399 ms 85.3%
  triton_mm_360 0.3586 ms 80.9%
  triton_mm_364 0.3617 ms 80.2%
  addmm 0.3725 ms 77.9%
  triton_mm_361 0.3990 ms 72.7%
  triton_mm_365 0.4100 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.6533 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1632 0.5570 ms 100.0%
  triton_mm_1631 0.5579 ms 99.8%
  triton_mm_1633 0.6273 ms 88.8%
  bias_addmm 0.6503 ms 85.6%
  triton_mm_1626 0.6579 ms 84.7%
  triton_mm_1628 0.6958 ms 80.0%
  addmm 0.6998 ms 79.6%
  triton_mm_1624 0.7066 ms 78.8%
  triton_mm_1629 0.7782 ms 71.6%
  triton_mm_1625 0.7799 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 11.2849 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5572 ms 100.0%
  triton_mm_1670 0.5751 ms 96.9%
  mm 0.5880 ms 94.8%
  triton_mm_1671 0.5993 ms 93.0%
  triton_mm_1664 0.6676 ms 83.5%
  triton_mm_1662 0.6792 ms 82.0%
  triton_mm_1666 0.6867 ms 81.1%
  triton_mm_1665 0.7232 ms 77.0%
  triton_mm_1667 0.7302 ms 76.3%
  triton_mm_1663 0.7411 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 9.5040 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2922 ms 100.0%
  triton_mm_1742 0.2962 ms 98.6%
  triton_mm_1741 0.2975 ms 98.2%
  triton_mm_1743 0.3013 ms 97.0%
  triton_mm_1736 0.3532 ms 82.7%
  triton_mm_1734 0.3570 ms 81.8%
  triton_mm_1738 0.3652 ms 80.0%
  triton_mm_1737 0.3810 ms 76.7%
  triton_mm_1739 0.3993 ms 73.2%
  triton_mm_1735 0.4056 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 9.6481 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1694 0.0110 ms 100.0%
  triton_mm_1699 0.0115 ms 96.1%
  triton_mm_1702 0.0115 ms 96.1%
  triton_mm_1701 0.0116 ms 94.8%
  triton_mm_1695 0.0117 ms 94.5%
  triton_mm_1700 0.0117 ms 94.0%
  triton_mm_1696 0.0119 ms 93.0%
  triton_mm_1704 0.0119 ms 93.0%
  triton_mm_1698 0.0121 ms 91.3%
  triton_mm_1689 0.0121 ms 91.0%
SingleProcess AUTOTUNE benchmarking takes 2.2232 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0154 ms 100.0%
  triton_mm_1680 0.0163 ms 94.7%
  mm 0.0169 ms 91.1%
  triton_mm_1684 0.0211 ms 73.0%
  triton_mm_1675 0.0221 ms 69.9%
  triton_mm_1688 0.0231 ms 66.7%
  triton_mm_1674 0.0241 ms 63.9%
  triton_mm_1679 0.0250 ms 61.8%
  triton_mm_1673 0.0260 ms 59.4%
  triton_mm_1683 0.0262 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.2192 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5424 ms 100.0%
  triton_mm_1650 0.5685 ms 95.4%
  triton_mm_1651 0.5792 ms 93.6%
  triton_mm_1652 0.5917 ms 91.7%
  triton_mm_1645 0.6663 ms 81.4%
  triton_mm_1647 0.6680 ms 81.2%
  triton_mm_1643 0.6792 ms 79.8%
  triton_mm_1646 0.7039 ms 77.1%
  triton_mm_1644 0.7333 ms 74.0%
  triton_mm_1648 0.7338 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.6050 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2774 ms 100.0%
  mm 0.2777 ms 99.9%
  triton_mm_1723 0.2801 ms 99.0%
  triton_mm_1724 0.3172 ms 87.5%
  triton_mm_1715 0.3400 ms 81.6%
  triton_mm_1717 0.3432 ms 80.9%
  triton_mm_1719 0.3476 ms 79.8%
  triton_mm_1716 0.3643 ms 76.2%
  triton_mm_1720 0.3867 ms 71.7%
  triton_mm_1718 0.4238 ms 65.5%
SingleProcess AUTOTUNE benchmarking takes 2.5350 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2248 ms 100.0%
  triton_mm_1836 0.2309 ms 97.4%
  triton_mm_1838 0.2419 ms 92.9%
  triton_mm_1833 0.2566 ms 87.6%
  mm 0.2577 ms 87.2%
  triton_mm_1831 0.2615 ms 86.0%
  triton_mm_1829 0.2626 ms 85.6%
  triton_mm_1832 0.2867 ms 78.4%
  triton_mm_1830 0.2904 ms 77.4%
  triton_mm_1834 0.2963 ms 75.9%
SingleProcess AUTOTUNE benchmarking takes 9.7022 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2904 ms 100.0%
  mm 0.2937 ms 98.9%
  triton_mm_1780 0.2943 ms 98.7%
  triton_mm_1781 0.3006 ms 96.6%
  triton_mm_1776 0.3467 ms 83.8%
  triton_mm_1772 0.3547 ms 81.9%
  triton_mm_1774 0.3579 ms 81.1%
  triton_mm_1775 0.3840 ms 75.6%
  triton_mm_1777 0.3929 ms 73.9%
  triton_mm_1773 0.4004 ms 72.5%
SingleProcess AUTOTUNE benchmarking takes 2.5345 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2265 ms 100.0%
  triton_mm_1855 0.2786 ms 81.3%
  triton_mm_1852 0.2831 ms 80.0%
  triton_mm_1850 0.2832 ms 80.0%
  triton_mm_1856 0.2856 ms 79.3%
  triton_mm_1848 0.2858 ms 79.3%
  triton_mm_1857 0.2887 ms 78.5%
  triton_mm_1851 0.3113 ms 72.8%
  triton_mm_1853 0.3245 ms 69.8%
  triton_mm_1849 0.3296 ms 68.7%
SingleProcess AUTOTUNE benchmarking takes 9.7759 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0989 ms 100.0%
  mm 0.1009 ms 98.0%
  triton_mm_1812 0.1051 ms 94.1%
  triton_mm_1818 0.1079 ms 91.6%
  triton_mm_1809 0.1192 ms 83.0%
  triton_mm_1810 0.1194 ms 82.8%
  triton_mm_1814 0.1204 ms 82.2%
  triton_mm_1817 0.1224 ms 80.8%
  triton_mm_1813 0.1267 ms 78.1%
  triton_mm_1815 0.1309 ms 75.6%
SingleProcess AUTOTUNE benchmarking takes 2.4138 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3034 ms 100.0%
  triton_mm_1760 0.3042 ms 99.7%
  triton_mm_1761 0.3110 ms 97.5%
  triton_mm_1762 0.3212 ms 94.5%
  triton_mm_1757 0.3436 ms 88.3%
  triton_mm_1755 0.3495 ms 86.8%
  triton_mm_1753 0.3497 ms 86.7%
  triton_mm_1756 0.3669 ms 82.7%
  triton_mm_1754 0.3867 ms 78.5%
  triton_mm_1758 0.3951 ms 76.8%
SingleProcess AUTOTUNE benchmarking takes 2.5339 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0840 ms 100.0%
  mm 0.0843 ms 99.7%
  triton_mm_1798 0.0855 ms 98.2%
  triton_mm_1795 0.0930 ms 90.3%
  triton_mm_1800 0.0942 ms 89.2%
  triton_mm_1791 0.0946 ms 88.8%
  triton_mm_1793 0.0961 ms 87.4%
  triton_mm_1792 0.1022 ms 82.2%
  triton_mm_1796 0.1047 ms 80.2%
  triton_mm_1794 0.1225 ms 68.6%
SingleProcess AUTOTUNE benchmarking takes 2.4110 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2927 ms 100.0%
  triton_mm_1928 0.2973 ms 98.5%
  triton_mm_1927 0.2976 ms 98.3%
  triton_mm_1929 0.3013 ms 97.1%
  triton_mm_1922 0.3533 ms 82.8%
  triton_mm_1920 0.3570 ms 82.0%
  triton_mm_1924 0.3641 ms 80.4%
  triton_mm_1923 0.3820 ms 76.6%
  triton_mm_1925 0.3998 ms 73.2%
  triton_mm_1921 0.4053 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 2.5314 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2904 ms 100.0%
  mm 0.2917 ms 99.5%
  triton_mm_1966 0.2953 ms 98.3%
  triton_mm_1967 0.3016 ms 96.3%
  triton_mm_1962 0.3471 ms 83.6%
  triton_mm_1958 0.3532 ms 82.2%
  triton_mm_1960 0.3583 ms 81.0%
  triton_mm_1961 0.3844 ms 75.5%
  triton_mm_1963 0.3926 ms 74.0%
  triton_mm_1959 0.4009 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5363 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0971 ms 100.0%
  triton_mm_2005 0.0996 ms 97.6%
  triton_mm_1998 0.1055 ms 92.1%
  triton_mm_2004 0.1086 ms 89.5%
  triton_mm_1995 0.1182 ms 82.2%
  triton_mm_1996 0.1197 ms 81.1%
  triton_mm_2000 0.1199 ms 81.0%
  triton_mm_2003 0.1231 ms 78.9%
  triton_mm_1999 0.1271 ms 76.4%
  triton_mm_2001 0.1304 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.4162 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_2023 0.2246 ms 100.0%
  mm 0.2258 ms 99.5%
  triton_mm_2022 0.2313 ms 97.1%
  triton_mm_2024 0.2432 ms 92.4%
  triton_mm_2019 0.2579 ms 87.1%
  triton_mm_2017 0.2626 ms 85.5%
  triton_mm_2015 0.2628 ms 85.5%
  triton_mm_2018 0.2877 ms 78.1%
  triton_mm_2016 0.2911 ms 77.2%
  triton_mm_2020 0.2978 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.5149 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2920 ms 100.0%
  triton_mm_2114 0.2971 ms 98.3%
  triton_mm_2113 0.2978 ms 98.1%
  triton_mm_2115 0.3014 ms 96.9%
  triton_mm_2108 0.3536 ms 82.6%
  triton_mm_2106 0.3566 ms 81.9%
  triton_mm_2110 0.3653 ms 79.9%
  triton_mm_2109 0.3810 ms 76.6%
  triton_mm_2111 0.3987 ms 73.3%
  triton_mm_2107 0.4058 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 2.5460 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2151 0.2889 ms 100.0%
  mm 0.2914 ms 99.1%
  triton_mm_2152 0.2957 ms 97.7%
  triton_mm_2153 0.3013 ms 95.9%
  triton_mm_2148 0.3468 ms 83.3%
  triton_mm_2144 0.3544 ms 81.5%
  triton_mm_2146 0.3581 ms 80.7%
  triton_mm_2147 0.3837 ms 75.3%
  triton_mm_2149 0.3913 ms 73.8%
  triton_mm_2145 0.4019 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.5429 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0972 ms 100.0%
  triton_mm_2191 0.0988 ms 98.4%
  triton_mm_2184 0.1047 ms 92.9%
  triton_mm_2190 0.1078 ms 90.2%
  triton_mm_2181 0.1189 ms 81.8%
  triton_mm_2182 0.1189 ms 81.8%
  triton_mm_2186 0.1204 ms 80.8%
  triton_mm_2189 0.1224 ms 79.5%
  triton_mm_2185 0.1264 ms 77.0%
  triton_mm_2187 0.1302 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4149 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2229 ms 100.0%
  triton_mm_2209 0.2244 ms 99.3%
  triton_mm_2208 0.2312 ms 96.4%
  triton_mm_2210 0.2432 ms 91.7%
  triton_mm_2205 0.2581 ms 86.4%
  triton_mm_2203 0.2627 ms 84.8%
  triton_mm_2201 0.2633 ms 84.7%
  triton_mm_2204 0.2876 ms 77.5%
  triton_mm_2202 0.2909 ms 76.6%
  triton_mm_2206 0.2982 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 2.5058 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2930 ms 100.0%
  triton_mm_2300 0.2973 ms 98.5%
  triton_mm_2299 0.2976 ms 98.5%
  triton_mm_2301 0.3028 ms 96.8%
  triton_mm_2294 0.3538 ms 82.8%
  triton_mm_2292 0.3592 ms 81.6%
  triton_mm_2296 0.3657 ms 80.1%
  triton_mm_2295 0.3817 ms 76.8%
  triton_mm_2297 0.4000 ms 73.2%
  triton_mm_2293 0.4062 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.5449 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2337 0.2899 ms 100.0%
  mm 0.2924 ms 99.1%
  triton_mm_2338 0.2968 ms 97.6%
  triton_mm_2339 0.3022 ms 95.9%
  triton_mm_2334 0.3491 ms 83.0%
  triton_mm_2330 0.3555 ms 81.5%
  triton_mm_2332 0.3589 ms 80.8%
  triton_mm_2333 0.3848 ms 75.3%
  triton_mm_2335 0.3931 ms 73.7%
  triton_mm_2331 0.4018 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.5400 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0979 ms 100.0%
  triton_mm_2377 0.0996 ms 98.3%
  triton_mm_2370 0.1053 ms 92.9%
  triton_mm_2376 0.1085 ms 90.2%
  triton_mm_2367 0.1187 ms 82.5%
  triton_mm_2368 0.1190 ms 82.2%
  triton_mm_2372 0.1199 ms 81.6%
  triton_mm_2375 0.1231 ms 79.5%
  triton_mm_2371 0.1270 ms 77.0%
  triton_mm_2373 0.1312 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.4295 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2233 ms 100.0%
  triton_mm_2395 0.2249 ms 99.3%
  triton_mm_2394 0.2315 ms 96.5%
  triton_mm_2396 0.2436 ms 91.6%
  triton_mm_2391 0.2578 ms 86.6%
  triton_mm_2389 0.2627 ms 85.0%
  triton_mm_2387 0.2632 ms 84.8%
  triton_mm_2390 0.2877 ms 77.6%
  triton_mm_2388 0.2915 ms 76.6%
  triton_mm_2392 0.2978 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5156 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2523 0.2885 ms 100.0%
  mm 0.2933 ms 98.3%
  triton_mm_2524 0.2948 ms 97.9%
  triton_mm_2525 0.3009 ms 95.9%
  triton_mm_2520 0.3470 ms 83.1%
  triton_mm_2516 0.3540 ms 81.5%
  triton_mm_2518 0.3575 ms 80.7%
  triton_mm_2519 0.3833 ms 75.3%
  triton_mm_2521 0.3927 ms 73.5%
  triton_mm_2517 0.4010 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.5403 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0980 ms 100.0%
  triton_mm_2563 0.0988 ms 99.1%
  triton_mm_2556 0.1053 ms 93.0%
  triton_mm_2562 0.1078 ms 90.9%
  triton_mm_2553 0.1180 ms 83.0%
  triton_mm_2554 0.1197 ms 81.8%
  triton_mm_2558 0.1199 ms 81.7%
  triton_mm_2561 0.1225 ms 80.0%
  triton_mm_2557 0.1269 ms 77.2%
  triton_mm_2559 0.1312 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4215 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2233 ms 100.0%
  triton_mm_2581 0.2257 ms 98.9%
  triton_mm_2580 0.2312 ms 96.6%
  triton_mm_2582 0.2428 ms 91.9%
  triton_mm_2577 0.2573 ms 86.8%
  triton_mm_2575 0.2622 ms 85.1%
  triton_mm_2573 0.2639 ms 84.6%
  triton_mm_2576 0.2883 ms 77.4%
  triton_mm_2574 0.2910 ms 76.7%
  triton_mm_2578 0.2972 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5139 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2709 0.2898 ms 100.0%
  mm 0.2934 ms 98.8%
  triton_mm_2710 0.2955 ms 98.1%
  triton_mm_2711 0.3021 ms 95.9%
  triton_mm_2706 0.3480 ms 83.3%
  triton_mm_2702 0.3537 ms 81.9%
  triton_mm_2704 0.3575 ms 81.1%
  triton_mm_2705 0.3839 ms 75.5%
  triton_mm_2707 0.3928 ms 73.8%
  triton_mm_2703 0.4009 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.5463 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2895 0.2897 ms 100.0%
  mm 0.2928 ms 98.9%
  triton_mm_2896 0.2951 ms 98.2%
  triton_mm_2897 0.3005 ms 96.4%
  triton_mm_2892 0.3466 ms 83.6%
  triton_mm_2888 0.3527 ms 82.1%
  triton_mm_2890 0.3582 ms 80.9%
  triton_mm_2891 0.3844 ms 75.4%
  triton_mm_2893 0.3923 ms 73.8%
  triton_mm_2889 0.4004 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5418 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_3081 0.2908 ms 100.0%
  mm 0.2928 ms 99.3%
  triton_mm_3082 0.2948 ms 98.6%
  triton_mm_3083 0.3001 ms 96.9%
  triton_mm_3078 0.3469 ms 83.8%
  triton_mm_3074 0.3528 ms 82.4%
  triton_mm_3076 0.3573 ms 81.4%
  triton_mm_3077 0.3839 ms 75.8%
  triton_mm_3079 0.3923 ms 74.1%
  triton_mm_3075 0.4005 ms 72.6%
SingleProcess AUTOTUNE benchmarking takes 2.5430 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_3267 0.2895 ms 100.0%
  mm 0.2927 ms 98.9%
  triton_mm_3268 0.2949 ms 98.2%
  triton_mm_3269 0.2997 ms 96.6%
  triton_mm_3264 0.3459 ms 83.7%
  triton_mm_3260 0.3526 ms 82.1%
  triton_mm_3262 0.3573 ms 81.0%
  triton_mm_3263 0.3829 ms 75.6%
  triton_mm_3265 0.3916 ms 73.9%
  triton_mm_3261 0.4005 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.5478 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_3453 0.2891 ms 100.0%
  mm 0.2935 ms 98.5%
  triton_mm_3454 0.2946 ms 98.1%
  triton_mm_3455 0.3010 ms 96.0%
  triton_mm_3450 0.3467 ms 83.4%
  triton_mm_3446 0.3536 ms 81.8%
  triton_mm_3448 0.3576 ms 80.8%
  triton_mm_3449 0.3833 ms 75.4%
  triton_mm_3451 0.3914 ms 73.8%
  triton_mm_3447 0.4006 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 2.5449 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0277 ms 100.0%
  triton_mm_4879 0.0499 ms 55.6%
  triton_mm_4872 0.0502 ms 55.3%
  triton_mm_4870 0.0566 ms 49.0%
  triton_mm_4871 0.0639 ms 43.4%
  triton_mm_4878 0.0674 ms 41.2%
  triton_mm_4875 0.0697 ms 39.8%
  triton_mm_4884 0.0737 ms 37.6%
  triton_mm_4883 0.0743 ms 37.3%
  triton_mm_4877 0.0781 ms 35.5%
SingleProcess AUTOTUNE benchmarking takes 6.3144 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_7 0.0251 ms 100.0%
  triton_mm_8 0.0262 ms 95.6%
  triton_mm_9 0.0264 ms 95.0%
  triton_mm_6 0.0270 ms 92.7%
  triton_mm_12 0.0271 ms 92.6%
  triton_mm_11 0.0272 ms 92.0%
  triton_mm_4 0.0274 ms 91.5%
  triton_mm_3 0.0278 ms 90.2%
  triton_mm_15 0.0279 ms 89.7%
  triton_mm_13 0.0281 ms 89.1%
SingleProcess AUTOTUNE benchmarking takes 2.0809 seconds and 0.0007 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2232 ms 100.0%
  triton_mm_51 0.2284 ms 97.7%
  triton_mm_52 0.2571 ms 86.8%
  triton_mm_45 0.2675 ms 83.4%
  triton_mm_47 0.2737 ms 81.5%
  triton_mm_43 0.2788 ms 80.1%
  bias_addmm 0.2986 ms 74.7%
  triton_mm_44 0.3116 ms 71.6%
  triton_mm_48 0.3140 ms 71.1%
  addmm 0.3212 ms 69.5%
SingleProcess AUTOTUNE benchmarking takes 2.5698 seconds and 0.0546 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0898 ms 100.0%
  triton_mm_69 0.0911 ms 98.6%
  bias_addmm 0.0967 ms 92.9%
  triton_mm_66 0.0981 ms 91.6%
  triton_mm_64 0.0984 ms 91.3%
  triton_mm_71 0.0989 ms 90.8%
  triton_mm_62 0.1020 ms 88.1%
  addmm 0.1106 ms 81.2%
  triton_mm_63 0.1118 ms 80.3%
  triton_mm_67 0.1121 ms 80.1%
SingleProcess AUTOTUNE benchmarking takes 2.5188 seconds and 0.0011 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2951 ms 100.0%
  triton_mm_89 0.2988 ms 98.8%
  bias_addmm 0.3247 ms 90.9%
  triton_mm_90 0.3370 ms 87.6%
  triton_mm_83 0.3442 ms 85.8%
  triton_mm_81 0.3649 ms 80.9%
  triton_mm_85 0.3655 ms 80.8%
  triton_mm_82 0.4057 ms 72.7%
  addmm 0.4164 ms 70.9%
  triton_mm_86 0.4174 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.6570 seconds and 0.0013 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2921 ms 100.0%
  triton_mm_108 0.3081 ms 94.8%
  triton_mm_107 0.3175 ms 92.0%
  addmm 0.3288 ms 88.8%
  triton_mm_109 0.3292 ms 88.7%
  triton_mm_104 0.3594 ms 81.3%
  triton_mm_102 0.3601 ms 81.1%
  triton_mm_103 0.3724 ms 78.4%
  triton_mm_100 0.3744 ms 78.0%
  triton_mm_105 0.4116 ms 71.0%
SingleProcess AUTOTUNE benchmarking takes 2.6701 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0141 ms 100.0%
  triton_mm_1606 0.0148 ms 95.7%
  triton_mm_1610 0.0159 ms 88.9%
  mm 0.0166 ms 85.3%
  triton_mm_1614 0.0169 ms 83.7%
  triton_mm_1605 0.0173 ms 81.7%
  triton_mm_1600 0.0175 ms 81.0%
  triton_mm_1601 0.0175 ms 81.0%
  triton_mm_1599 0.0177 ms 79.9%
  triton_mm_1609 0.0189 ms 74.9%
SingleProcess AUTOTUNE benchmarking takes 2.1782 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5601 ms 100.0%
  triton_mm_1631 0.5622 ms 99.6%
  triton_mm_1632 0.5626 ms 99.6%
  triton_mm_1633 0.6323 ms 88.6%
  triton_mm_1626 0.6649 ms 84.2%
  triton_mm_1628 0.6998 ms 80.0%
  addmm 0.7062 ms 79.3%
  triton_mm_1624 0.7142 ms 78.4%
  triton_mm_1625 0.7864 ms 71.2%
  triton_mm_1629 0.7868 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 11.5006 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5544 ms 100.0%
  triton_mm_1670 0.5780 ms 95.9%
  mm 0.5860 ms 94.6%
  triton_mm_1671 0.6016 ms 92.1%
  triton_mm_1664 0.6670 ms 83.1%
  triton_mm_1666 0.6856 ms 80.9%
  triton_mm_1662 0.6903 ms 80.3%
  triton_mm_1667 0.7349 ms 75.4%
  triton_mm_1665 0.7387 ms 75.0%
  triton_mm_1663 0.7437 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.5921 seconds and 0.0245 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2915 ms 100.0%
  triton_mm_1742 0.2976 ms 98.0%
  triton_mm_1741 0.2985 ms 97.7%
  triton_mm_1743 0.3026 ms 96.3%
  triton_mm_1736 0.3547 ms 82.2%
  triton_mm_1734 0.3594 ms 81.1%
  triton_mm_1738 0.3676 ms 79.3%
  triton_mm_1737 0.3828 ms 76.2%
  triton_mm_1739 0.4023 ms 72.5%
  triton_mm_1735 0.4075 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 2.5416 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1700 0.0109 ms 100.0%
  triton_mm_1695 0.0113 ms 97.2%
  triton_mm_1702 0.0115 ms 95.0%
  triton_mm_1701 0.0116 ms 94.7%
  triton_mm_1699 0.0118 ms 92.9%
  triton_mm_1694 0.0119 ms 92.3%
  triton_mm_1698 0.0120 ms 91.0%
  triton_mm_1697 0.0121 ms 90.1%
  triton_mm_1693 0.0122 ms 90.0%
  triton_mm_1692 0.0124 ms 88.1%
SingleProcess AUTOTUNE benchmarking takes 2.2220 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0154 ms 100.0%
  triton_mm_1680 0.0161 ms 95.4%
  mm 0.0169 ms 91.3%
  triton_mm_1684 0.0207 ms 74.3%
  triton_mm_1675 0.0220 ms 69.9%
  triton_mm_1688 0.0223 ms 69.1%
  triton_mm_1674 0.0235 ms 65.5%
  triton_mm_1683 0.0255 ms 60.3%
  triton_mm_1679 0.0257 ms 59.8%
  triton_mm_1673 0.0267 ms 57.7%
SingleProcess AUTOTUNE benchmarking takes 2.2110 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5392 ms 100.0%
  triton_mm_1650 0.5678 ms 95.0%
  triton_mm_1651 0.5772 ms 93.4%
  triton_mm_1652 0.5972 ms 90.3%
  triton_mm_1645 0.6615 ms 81.5%
  triton_mm_1647 0.6626 ms 81.4%
  triton_mm_1643 0.6815 ms 79.1%
  triton_mm_1646 0.7021 ms 76.8%
  triton_mm_1644 0.7269 ms 74.2%
  triton_mm_1648 0.7385 ms 73.0%
SingleProcess AUTOTUNE benchmarking takes 9.3503 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2776 ms 100.0%
  mm 0.2799 ms 99.2%
  triton_mm_1723 0.2810 ms 98.8%
  triton_mm_1724 0.3172 ms 87.5%
  triton_mm_1717 0.3441 ms 80.7%
  triton_mm_1715 0.3442 ms 80.7%
  triton_mm_1719 0.3496 ms 79.4%
  triton_mm_1716 0.3663 ms 75.8%
  triton_mm_1720 0.3890 ms 71.4%
  triton_mm_1718 0.4227 ms 65.7%
SingleProcess AUTOTUNE benchmarking takes 2.5378 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2254 ms 100.0%
  triton_mm_1836 0.2307 ms 97.7%
  triton_mm_1838 0.2424 ms 93.0%
  mm 0.2564 ms 87.9%
  triton_mm_1833 0.2577 ms 87.5%
  triton_mm_1831 0.2631 ms 85.7%
  triton_mm_1829 0.2644 ms 85.3%
  triton_mm_1832 0.2884 ms 78.2%
  triton_mm_1830 0.2925 ms 77.1%
  triton_mm_1834 0.2975 ms 75.8%
SingleProcess AUTOTUNE benchmarking takes 2.5134 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2916 ms 100.0%
  mm 0.2917 ms 99.9%
  triton_mm_1780 0.2958 ms 98.6%
  triton_mm_1781 0.3019 ms 96.6%
  triton_mm_1776 0.3491 ms 83.5%
  triton_mm_1772 0.3573 ms 81.6%
  triton_mm_1774 0.3606 ms 80.8%
  triton_mm_1775 0.3856 ms 75.6%
  triton_mm_1777 0.3952 ms 73.8%
  triton_mm_1773 0.3987 ms 73.1%
SingleProcess AUTOTUNE benchmarking takes 9.7782 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2273 ms 100.0%
  triton_mm_1855 0.2795 ms 81.3%
  triton_mm_1850 0.2851 ms 79.7%
  triton_mm_1852 0.2852 ms 79.7%
  triton_mm_1856 0.2869 ms 79.2%
  triton_mm_1848 0.2878 ms 79.0%
  triton_mm_1857 0.2899 ms 78.4%
  triton_mm_1851 0.3127 ms 72.7%
  triton_mm_1853 0.3263 ms 69.7%
  triton_mm_1849 0.3311 ms 68.7%
SingleProcess AUTOTUNE benchmarking takes 9.8880 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0996 ms 100.0%
  mm 0.1016 ms 98.0%
  triton_mm_1812 0.1055 ms 94.3%
  triton_mm_1818 0.1090 ms 91.3%
  triton_mm_1809 0.1200 ms 82.9%
  triton_mm_1810 0.1204 ms 82.7%
  triton_mm_1814 0.1219 ms 81.7%
  triton_mm_1817 0.1242 ms 80.1%
  triton_mm_1813 0.1276 ms 78.0%
  triton_mm_1815 0.1323 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 9.5388 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3044 ms 100.0%
  triton_mm_1760 0.3047 ms 99.9%
  triton_mm_1761 0.3126 ms 97.4%
  triton_mm_1762 0.3215 ms 94.7%
  triton_mm_1757 0.3455 ms 88.1%
  triton_mm_1755 0.3517 ms 86.5%
  triton_mm_1753 0.3530 ms 86.2%
  triton_mm_1756 0.3680 ms 82.7%
  triton_mm_1754 0.3880 ms 78.5%
  triton_mm_1758 0.3971 ms 76.7%
SingleProcess AUTOTUNE benchmarking takes 9.4615 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0843 ms 100.0%
  mm 0.0847 ms 99.5%
  triton_mm_1798 0.0857 ms 98.4%
  triton_mm_1795 0.0932 ms 90.5%
  triton_mm_1800 0.0942 ms 89.6%
  triton_mm_1791 0.0948 ms 88.9%
  triton_mm_1793 0.0965 ms 87.4%
  triton_mm_1792 0.1026 ms 82.2%
  triton_mm_1796 0.1054 ms 80.0%
  triton_mm_1794 0.1234 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 9.9727 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2765 ms 100.0%
  triton_mm_1909 0.2798 ms 98.8%
  mm 0.2798 ms 98.8%
  triton_mm_1910 0.3164 ms 87.4%
  triton_mm_1901 0.3432 ms 80.6%
  triton_mm_1903 0.3454 ms 80.1%
  triton_mm_1905 0.3465 ms 79.8%
  triton_mm_1902 0.3669 ms 75.4%
  triton_mm_1906 0.3870 ms 71.5%
  triton_mm_1904 0.4226 ms 65.4%
SingleProcess AUTOTUNE benchmarking takes 2.5312 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3043 ms 100.0%
  triton_mm_1946 0.3045 ms 99.9%
  triton_mm_1947 0.3108 ms 97.9%
  triton_mm_1948 0.3214 ms 94.7%
  triton_mm_1943 0.3453 ms 88.1%
  triton_mm_1939 0.3504 ms 86.9%
  triton_mm_1941 0.3524 ms 86.3%
  triton_mm_1942 0.3708 ms 82.1%
  triton_mm_1940 0.3915 ms 77.7%
  triton_mm_1944 0.3963 ms 76.8%
SingleProcess AUTOTUNE benchmarking takes 2.5340 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2912 ms 100.0%
  triton_mm_1928 0.2987 ms 97.5%
  triton_mm_1927 0.2990 ms 97.4%
  triton_mm_1929 0.3024 ms 96.3%
  triton_mm_1922 0.3551 ms 82.0%
  triton_mm_1920 0.3583 ms 81.3%
  triton_mm_1924 0.3682 ms 79.1%
  triton_mm_1923 0.3839 ms 75.9%
  triton_mm_1925 0.4025 ms 72.4%
  triton_mm_1921 0.4065 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.5419 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2910 ms 100.0%
  mm 0.2924 ms 99.5%
  triton_mm_1966 0.2964 ms 98.2%
  triton_mm_1967 0.3026 ms 96.2%
  triton_mm_1962 0.3518 ms 82.7%
  triton_mm_1958 0.3574 ms 81.4%
  triton_mm_1960 0.3599 ms 80.8%
  triton_mm_1961 0.3872 ms 75.1%
  triton_mm_1963 0.3946 ms 73.7%
  triton_mm_1959 0.4033 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 2.5352 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2240 ms 100.0%
  triton_mm_2041 0.2766 ms 81.0%
  triton_mm_2042 0.2846 ms 78.7%
  triton_mm_2038 0.2862 ms 78.3%
  triton_mm_2036 0.2878 ms 77.8%
  triton_mm_2034 0.2882 ms 77.7%
  triton_mm_2043 0.2895 ms 77.4%
  triton_mm_2037 0.3123 ms 71.7%
  triton_mm_2039 0.3265 ms 68.6%
  triton_mm_2035 0.3302 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5129 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2005 0.0986 ms 100.0%
  mm 0.1006 ms 97.9%
  triton_mm_1998 0.1053 ms 93.6%
  triton_mm_2004 0.1079 ms 91.3%
  triton_mm_1995 0.1188 ms 83.0%
  triton_mm_1996 0.1194 ms 82.6%
  triton_mm_2000 0.1209 ms 81.5%
  triton_mm_2003 0.1227 ms 80.3%
  triton_mm_1999 0.1272 ms 77.5%
  triton_mm_2001 0.1300 ms 75.8%
SingleProcess AUTOTUNE benchmarking takes 2.4125 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1985 0.0828 ms 100.0%
  mm 0.0838 ms 98.8%
  triton_mm_1984 0.0842 ms 98.4%
  triton_mm_1981 0.0923 ms 89.7%
  triton_mm_1977 0.0939 ms 88.2%
  triton_mm_1986 0.0940 ms 88.2%
  triton_mm_1979 0.0955 ms 86.7%
  triton_mm_1978 0.1030 ms 80.5%
  triton_mm_1982 0.1045 ms 79.3%
  triton_mm_1980 0.1229 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 2.4068 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2247 ms 100.0%
  triton_mm_2023 0.2261 ms 99.4%
  triton_mm_2022 0.2310 ms 97.3%
  triton_mm_2024 0.2432 ms 92.4%
  triton_mm_2019 0.2584 ms 87.0%
  triton_mm_2017 0.2645 ms 85.0%
  triton_mm_2015 0.2657 ms 84.6%
  triton_mm_2018 0.2918 ms 77.0%
  triton_mm_2016 0.2918 ms 77.0%
  triton_mm_2020 0.2984 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5087 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2094 0.2754 ms 100.0%
  mm 0.2776 ms 99.2%
  triton_mm_2095 0.2793 ms 98.6%
  triton_mm_2096 0.3162 ms 87.1%
  triton_mm_2087 0.3434 ms 80.2%
  triton_mm_2089 0.3443 ms 80.0%
  triton_mm_2091 0.3467 ms 79.4%
  triton_mm_2088 0.3658 ms 75.3%
  triton_mm_2092 0.3910 ms 70.4%
  triton_mm_2090 0.4249 ms 64.8%
SingleProcess AUTOTUNE benchmarking takes 2.5338 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3025 ms 100.0%
  triton_mm_2132 0.3034 ms 99.7%
  triton_mm_2133 0.3118 ms 97.0%
  triton_mm_2134 0.3225 ms 93.8%
  triton_mm_2129 0.3456 ms 87.5%
  triton_mm_2127 0.3519 ms 85.9%
  triton_mm_2125 0.3537 ms 85.5%
  triton_mm_2128 0.3706 ms 81.6%
  triton_mm_2126 0.3909 ms 77.4%
  triton_mm_2130 0.3976 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.5349 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2913 ms 100.0%
  triton_mm_2113 0.2982 ms 97.7%
  triton_mm_2114 0.2986 ms 97.6%
  triton_mm_2115 0.3029 ms 96.2%
  triton_mm_2108 0.3556 ms 81.9%
  triton_mm_2106 0.3594 ms 81.1%
  triton_mm_2110 0.3678 ms 79.2%
  triton_mm_2109 0.3841 ms 75.8%
  triton_mm_2111 0.4034 ms 72.2%
  triton_mm_2107 0.4071 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.5456 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2151 0.2917 ms 100.0%
  mm 0.2931 ms 99.5%
  triton_mm_2152 0.2974 ms 98.1%
  triton_mm_2153 0.3014 ms 96.8%
  triton_mm_2148 0.3505 ms 83.2%
  triton_mm_2144 0.3568 ms 81.8%
  triton_mm_2146 0.3612 ms 80.8%
  triton_mm_2147 0.3873 ms 75.3%
  triton_mm_2149 0.3953 ms 73.8%
  triton_mm_2145 0.4064 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.5317 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2251 ms 100.0%
  triton_mm_2227 0.2776 ms 81.1%
  triton_mm_2228 0.2851 ms 79.0%
  triton_mm_2224 0.2860 ms 78.7%
  triton_mm_2222 0.2865 ms 78.6%
  triton_mm_2229 0.2885 ms 78.0%
  triton_mm_2220 0.2891 ms 77.9%
  triton_mm_2223 0.3139 ms 71.7%
  triton_mm_2225 0.3259 ms 69.1%
  triton_mm_2221 0.3319 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5246 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2191 0.0991 ms 100.0%
  mm 0.1005 ms 98.6%
  triton_mm_2184 0.1045 ms 94.8%
  triton_mm_2190 0.1085 ms 91.3%
  triton_mm_2181 0.1182 ms 83.9%
  triton_mm_2182 0.1200 ms 82.6%
  triton_mm_2186 0.1208 ms 82.0%
  triton_mm_2189 0.1232 ms 80.4%
  triton_mm_2185 0.1264 ms 78.5%
  triton_mm_2187 0.1300 ms 76.3%
SingleProcess AUTOTUNE benchmarking takes 2.4126 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0830 ms 100.0%
  triton_mm_2171 0.0836 ms 99.2%
  triton_mm_2170 0.0848 ms 97.8%
  triton_mm_2167 0.0923 ms 89.9%
  triton_mm_2172 0.0932 ms 89.0%
  triton_mm_2163 0.0940 ms 88.3%
  triton_mm_2165 0.0956 ms 86.9%
  triton_mm_2164 0.1024 ms 81.1%
  triton_mm_2168 0.1052 ms 78.9%
  triton_mm_2166 0.1228 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.4104 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2245 ms 100.0%
  triton_mm_2209 0.2256 ms 99.5%
  triton_mm_2208 0.2323 ms 96.6%
  triton_mm_2210 0.2441 ms 92.0%
  triton_mm_2205 0.2590 ms 86.7%
  triton_mm_2203 0.2645 ms 84.9%
  triton_mm_2201 0.2668 ms 84.2%
  triton_mm_2204 0.2903 ms 77.3%
  triton_mm_2202 0.2923 ms 76.8%
  triton_mm_2206 0.2990 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5123 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2911 ms 100.0%
  triton_mm_2337 0.2915 ms 99.9%
  triton_mm_2338 0.2964 ms 98.2%
  triton_mm_2339 0.3028 ms 96.1%
  triton_mm_2334 0.3504 ms 83.1%
  triton_mm_2330 0.3537 ms 82.3%
  triton_mm_2332 0.3600 ms 80.8%
  triton_mm_2333 0.3861 ms 75.4%
  triton_mm_2335 0.3950 ms 73.7%
  triton_mm_2331 0.4032 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 2.5353 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_2395 0.2252 ms 100.0%
  triton_mm_2394 0.2316 ms 97.2%
  triton_mm_2396 0.2434 ms 92.5%
  mm 0.2564 ms 87.8%
  triton_mm_2391 0.2577 ms 87.4%
  triton_mm_2389 0.2650 ms 85.0%
  triton_mm_2387 0.2660 ms 84.6%
  triton_mm_2390 0.2905 ms 77.5%
  triton_mm_2388 0.2928 ms 76.9%
  triton_mm_2392 0.2989 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5000 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2912 ms 100.0%
  triton_mm_2523 0.2918 ms 99.8%
  triton_mm_2524 0.2965 ms 98.2%
  triton_mm_2525 0.3027 ms 96.2%
  triton_mm_2520 0.3497 ms 83.3%
  triton_mm_2516 0.3556 ms 81.9%
  triton_mm_2518 0.3605 ms 80.8%
  triton_mm_2519 0.3863 ms 75.4%
  triton_mm_2521 0.3954 ms 73.6%
  triton_mm_2517 0.4027 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.5450 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2231 ms 100.0%
  triton_mm_2581 0.2252 ms 99.1%
  triton_mm_2580 0.2312 ms 96.5%
  triton_mm_2582 0.2438 ms 91.5%
  triton_mm_2577 0.2588 ms 86.2%
  triton_mm_2575 0.2646 ms 84.3%
  triton_mm_2573 0.2649 ms 84.2%
  triton_mm_2576 0.2912 ms 76.6%
  triton_mm_2574 0.2930 ms 76.2%
  triton_mm_2578 0.2985 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5110 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2910 ms 100.0%
  triton_mm_2709 0.2928 ms 99.4%
  triton_mm_2710 0.2971 ms 98.0%
  triton_mm_2711 0.3022 ms 96.3%
  triton_mm_2706 0.3494 ms 83.3%
  triton_mm_2702 0.3568 ms 81.5%
  triton_mm_2704 0.3604 ms 80.7%
  triton_mm_2705 0.3863 ms 75.3%
  triton_mm_2707 0.3951 ms 73.6%
  triton_mm_2703 0.4033 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.5482 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2238 ms 100.0%
  triton_mm_2767 0.2252 ms 99.4%
  triton_mm_2766 0.2314 ms 96.7%
  triton_mm_2768 0.2437 ms 91.8%
  triton_mm_2763 0.2591 ms 86.4%
  triton_mm_2761 0.2650 ms 84.4%
  triton_mm_2759 0.2655 ms 84.3%
  triton_mm_2762 0.2903 ms 77.1%
  triton_mm_2760 0.2917 ms 76.7%
  triton_mm_2764 0.2987 ms 74.9%
SingleProcess AUTOTUNE benchmarking takes 2.5120 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2228 ms 100.0%
  triton_mm_2953 0.2248 ms 99.1%
  triton_mm_2952 0.2312 ms 96.4%
  triton_mm_2954 0.2428 ms 91.8%
  triton_mm_2949 0.2587 ms 86.1%
  triton_mm_2947 0.2637 ms 84.5%
  triton_mm_2945 0.2646 ms 84.2%
  triton_mm_2948 0.2891 ms 77.1%
  triton_mm_2946 0.2927 ms 76.1%
  triton_mm_2950 0.2984 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5230 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2249 ms 100.0%
  triton_mm_3139 0.2253 ms 99.8%
  triton_mm_3138 0.2305 ms 97.6%
  triton_mm_3140 0.2422 ms 92.9%
  triton_mm_3135 0.2581 ms 87.1%
  triton_mm_3133 0.2638 ms 85.3%
  triton_mm_3131 0.2667 ms 84.3%
  triton_mm_3134 0.2896 ms 77.7%
  triton_mm_3132 0.2917 ms 77.1%
  triton_mm_3136 0.2980 ms 75.5%
SingleProcess AUTOTUNE benchmarking takes 2.5226 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0277 ms 100.0%
  triton_mm_4872 0.0505 ms 54.9%
  triton_mm_4879 0.0510 ms 54.3%
  triton_mm_4870 0.0569 ms 48.7%
  triton_mm_4871 0.0642 ms 43.1%
  triton_mm_4878 0.0669 ms 41.4%
  triton_mm_4875 0.0706 ms 39.2%
  triton_mm_4884 0.0736 ms 37.6%
  triton_mm_4883 0.0740 ms 37.4%
  triton_mm_4877 0.0777 ms 35.6%
SingleProcess AUTOTUNE benchmarking takes 6.2034 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8237 ms 100.0%
  mm 0.9401 ms 87.6%
  triton_mm_4987 1.0011 ms 82.3%
  triton_mm_4983 1.0075 ms 81.8%
  triton_mm_4991 1.0702 ms 77.0%
  triton_mm_4988 1.1067 ms 74.4%
  triton_mm_4984 1.1243 ms 73.3%
  triton_mm_4985 1.1360 ms 72.5%
  triton_mm_4980 1.3433 ms 61.3%
  triton_mm_4981 1.4118 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1607 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8233 ms 100.0%
  mm 0.8488 ms 97.0%
  triton_mm_5080 0.9913 ms 83.1%
  triton_mm_5076 1.0101 ms 81.5%
  triton_mm_5084 1.0656 ms 77.3%
  triton_mm_5081 1.1073 ms 74.4%
  triton_mm_5077 1.1180 ms 73.6%
  triton_mm_5078 1.1435 ms 72.0%
  triton_mm_5073 1.3422 ms 61.3%
  triton_mm_5074 1.4109 ms 58.4%
SingleProcess AUTOTUNE benchmarking takes 2.1595 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6385 0.8370 ms 100.0%
  mm 0.8443 ms 99.1%
  triton_mm_6382 0.9922 ms 84.4%
  triton_mm_6378 0.9967 ms 84.0%
  triton_mm_6386 1.0653 ms 78.6%
  triton_mm_6383 1.1005 ms 76.1%
  triton_mm_6379 1.1159 ms 75.0%
  triton_mm_6380 1.1322 ms 73.9%
  triton_mm_6375 1.3346 ms 62.7%
  triton_mm_6376 1.3940 ms 60.0%
SingleProcess AUTOTUNE benchmarking takes 2.1620 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0364 ms 100.0%
  triton_mm_4892 0.0377 ms 96.6%
  triton_mm_4899 0.0380 ms 95.8%
  triton_mm_4896 0.0383 ms 95.2%
  triton_mm_4898 0.0389 ms 93.6%
  triton_mm_4895 0.0389 ms 93.5%
  triton_mm_4888 0.0403 ms 90.3%
  triton_mm_4887 0.0412 ms 88.5%
  triton_mm_4894 0.0418 ms 87.1%
  triton_mm_4886 0.0460 ms 79.2%
SingleProcess AUTOTUNE benchmarking takes 1.7130 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4909 0.0345 ms 100.0%
  triton_mm_4914 0.0349 ms 98.9%
  triton_mm_4908 0.0351 ms 98.3%
  triton_mm_4911 0.0353 ms 97.8%
  triton_mm_4910 0.0362 ms 95.2%
  triton_mm_4913 0.0366 ms 94.2%
  triton_mm_4906 0.0375 ms 91.9%
  triton_mm_4917 0.0383 ms 90.1%
  triton_mm_4907 0.0390 ms 88.5%
  triton_mm_4904 0.0392 ms 87.9%
SingleProcess AUTOTUNE benchmarking takes 2.1176 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6398 ms 100.0%
  bias_addmm 0.6453 ms 99.1%
  triton_mm_4932 0.7515 ms 85.1%
  triton_mm_4928 0.7587 ms 84.3%
  addmm 0.8010 ms 79.9%
  triton_mm_4936 0.8373 ms 76.4%
  triton_mm_4933 0.8379 ms 76.4%
  triton_mm_4929 0.8484 ms 75.4%
  triton_mm_4930 0.8698 ms 73.6%
  triton_mm_4925 1.0044 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.2507 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2234 ms 100.0%
  mm 0.2316 ms 96.4%
  triton_mm_4951 0.2512 ms 88.9%
  triton_mm_4947 0.2630 ms 84.9%
  triton_mm_4952 0.2764 ms 80.8%
  triton_mm_4955 0.2897 ms 77.1%
  triton_mm_4948 0.2925 ms 76.4%
  triton_mm_4949 0.3042 ms 73.4%
  triton_mm_4944 0.3400 ms 65.7%
  triton_mm_4945 0.3508 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.0160 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8333 ms 100.0%
  mm 0.8696 ms 95.8%
  triton_mm_5010 0.9933 ms 83.9%
  triton_mm_5006 1.0133 ms 82.2%
  triton_mm_5002 1.0563 ms 78.9%
  triton_mm_5007 1.0645 ms 78.3%
  triton_mm_5003 1.1215 ms 74.3%
  triton_mm_5004 1.1217 ms 74.3%
  triton_mm_4999 1.3435 ms 62.0%
  triton_mm_5000 1.3586 ms 61.3%
SingleProcess AUTOTUNE benchmarking takes 2.1519 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_6218 0.8327 ms 100.0%
  mm 0.8699 ms 95.7%
  triton_mm_6219 0.9902 ms 84.1%
  triton_mm_6215 1.0139 ms 82.1%
  triton_mm_6211 1.0428 ms 79.9%
  triton_mm_6216 1.0678 ms 78.0%
  triton_mm_6213 1.1306 ms 73.7%
  triton_mm_6212 1.1449 ms 72.7%
  triton_mm_6208 1.3397 ms 62.2%
  triton_mm_6209 1.3600 ms 61.2%
SingleProcess AUTOTUNE benchmarking takes 2.1586 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6387 ms 100.0%
  triton_mm_6237 0.6396 ms 99.9%
  triton_mm_6234 0.7507 ms 85.1%
  triton_mm_6230 0.7603 ms 84.0%
  addmm 0.7932 ms 80.5%
  triton_mm_6238 0.8362 ms 76.4%
  triton_mm_6235 0.8384 ms 76.2%
  triton_mm_6231 0.8507 ms 75.1%
  triton_mm_6232 0.8694 ms 73.5%
  triton_mm_6227 1.0119 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.2534 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_6256 0.2223 ms 100.0%
  mm 0.2326 ms 95.6%
  triton_mm_6253 0.2531 ms 87.8%
  triton_mm_6249 0.2609 ms 85.2%
  triton_mm_6254 0.2766 ms 80.4%
  triton_mm_6257 0.2905 ms 76.5%
  triton_mm_6250 0.2924 ms 76.0%
  triton_mm_6251 0.3040 ms 73.1%
  triton_mm_6246 0.3391 ms 65.6%
  triton_mm_6247 0.3515 ms 63.3%
SingleProcess AUTOTUNE benchmarking takes 2.0303 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0364 ms 100.0%
  triton_mm_6273 0.0368 ms 98.7%
  triton_mm_6266 0.0371 ms 98.1%
  triton_mm_6270 0.0380 ms 95.6%
  triton_mm_6272 0.0389 ms 93.3%
  triton_mm_6269 0.0390 ms 93.3%
  triton_mm_6262 0.0393 ms 92.6%
  triton_mm_6268 0.0406 ms 89.4%
  triton_mm_6261 0.0411 ms 88.5%
  triton_mm_6260 0.0460 ms 79.1%
SingleProcess AUTOTUNE benchmarking takes 1.6726 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6447 0.0207 ms 100.0%
  triton_mm_6448 0.0212 ms 97.7%
  mm 0.0217 ms 95.4%
  triton_mm_6452 0.0235 ms 88.3%
  triton_mm_6446 0.0243 ms 85.1%
  triton_mm_6459 0.0248 ms 83.5%
  triton_mm_6456 0.0273 ms 75.9%
  triton_mm_6455 0.0283 ms 73.1%
  triton_mm_6458 0.0286 ms 72.5%
  triton_mm_6454 0.0310 ms 66.8%
SingleProcess AUTOTUNE benchmarking takes 1.7150 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5484 ms 100.0%
  bias_addmm 1.5644 ms 99.0%
  triton_mm_6513 1.8579 ms 83.3%
  triton_mm_6509 1.8988 ms 81.5%
  addmm 1.9140 ms 80.9%
  triton_mm_6517 2.0035 ms 77.3%
  triton_mm_6514 2.0718 ms 74.7%
  triton_mm_6510 2.0976 ms 73.8%
  triton_mm_6511 2.1514 ms 72.0%
  triton_mm_6506 2.5278 ms 61.3%
SingleProcess AUTOTUNE benchmarking takes 2.4108 seconds and 0.0009 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:00<1:26:32, 120.76s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8248 ms 100.0%
  mm 0.9389 ms 87.8%
  triton_mm_4987 0.9830 ms 83.9%
  triton_mm_4983 1.0000 ms 82.5%
  triton_mm_4991 1.0567 ms 78.1%
  triton_mm_4984 1.1021 ms 74.8%
  triton_mm_4988 1.1027 ms 74.8%
  triton_mm_4985 1.1315 ms 72.9%
  triton_mm_4980 1.3298 ms 62.0%
  triton_mm_4981 1.3978 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1430 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8330 ms 100.0%
  mm 0.8398 ms 99.2%
  triton_mm_5080 0.9860 ms 84.5%
  triton_mm_5076 1.0020 ms 83.1%
  triton_mm_5084 1.0672 ms 78.1%
  triton_mm_5081 1.1077 ms 75.2%
  triton_mm_5077 1.1184 ms 74.5%
  triton_mm_5078 1.1311 ms 73.6%
  triton_mm_5073 1.3417 ms 62.1%
  triton_mm_5074 1.3965 ms 59.6%
SingleProcess AUTOTUNE benchmarking takes 2.1494 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0358 ms 100.0%
  triton_mm_4892 0.0371 ms 96.5%
  triton_mm_4899 0.0374 ms 95.7%
  triton_mm_4896 0.0377 ms 94.9%
  triton_mm_4895 0.0382 ms 93.8%
  triton_mm_4888 0.0384 ms 93.3%
  triton_mm_4898 0.0386 ms 92.7%
  triton_mm_4894 0.0403 ms 88.8%
  triton_mm_4887 0.0404 ms 88.6%
  triton_mm_4886 0.0434 ms 82.6%
SingleProcess AUTOTUNE benchmarking takes 1.7107 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4908 0.0348 ms 100.0%
  triton_mm_4913 0.0351 ms 99.0%
  triton_mm_4909 0.0354 ms 98.1%
  triton_mm_4914 0.0357 ms 97.3%
  triton_mm_4910 0.0358 ms 97.1%
  triton_mm_4911 0.0361 ms 96.4%
  triton_mm_4906 0.0371 ms 93.7%
  triton_mm_4917 0.0379 ms 91.6%
  triton_mm_4904 0.0388 ms 89.5%
  triton_mm_4905 0.0392 ms 88.7%
SingleProcess AUTOTUNE benchmarking takes 2.1107 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6392 ms 100.0%
  bias_addmm 0.6435 ms 99.3%
  triton_mm_4932 0.7454 ms 85.8%
  triton_mm_4928 0.7613 ms 84.0%
  addmm 0.7963 ms 80.3%
  triton_mm_4936 0.8374 ms 76.3%
  triton_mm_4933 0.8391 ms 76.2%
  triton_mm_4929 0.8537 ms 74.9%
  triton_mm_4930 0.8746 ms 73.1%
  triton_mm_4925 1.0127 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.2393 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2261 ms 100.0%
  mm 0.2371 ms 95.4%
  triton_mm_4951 0.2550 ms 88.7%
  triton_mm_4947 0.2675 ms 84.5%
  triton_mm_4952 0.2800 ms 80.7%
  triton_mm_4955 0.2903 ms 77.9%
  triton_mm_4948 0.2957 ms 76.5%
  triton_mm_4949 0.3072 ms 73.6%
  triton_mm_4944 0.3409 ms 66.3%
  triton_mm_4945 0.3525 ms 64.1%
SingleProcess AUTOTUNE benchmarking takes 2.0172 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8378 ms 100.0%
  mm 0.8772 ms 95.5%
  triton_mm_5010 1.0002 ms 83.8%
  triton_mm_5006 1.0102 ms 82.9%
  triton_mm_5002 1.0512 ms 79.7%
  triton_mm_5007 1.0693 ms 78.3%
  triton_mm_5003 1.1200 ms 74.8%
  triton_mm_5004 1.1398 ms 73.5%
  triton_mm_4999 1.3439 ms 62.3%
  triton_mm_5000 1.3608 ms 61.6%
SingleProcess AUTOTUNE benchmarking takes 2.1476 seconds and 0.0011 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_5400 0.6437 ms 100.0%
  bias_addmm 0.6468 ms 99.5%
  triton_mm_5397 0.7512 ms 85.7%
  triton_mm_5393 0.7621 ms 84.5%
  addmm 0.7978 ms 80.7%
  triton_mm_5401 0.8362 ms 77.0%
  triton_mm_5398 0.8457 ms 76.1%
  triton_mm_5394 0.8621 ms 74.7%
  triton_mm_5395 0.8731 ms 73.7%
  triton_mm_5390 1.0110 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.2366 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_5419 0.2265 ms 100.0%
  mm 0.2378 ms 95.3%
  triton_mm_5416 0.2564 ms 88.4%
  triton_mm_5412 0.2680 ms 84.5%
  triton_mm_5417 0.2812 ms 80.6%
  triton_mm_5420 0.2897 ms 78.2%
  triton_mm_5413 0.2965 ms 76.4%
  triton_mm_5414 0.3073 ms 73.7%
  triton_mm_5409 0.3404 ms 66.5%
  triton_mm_5410 0.3566 ms 63.5%
SingleProcess AUTOTUNE benchmarking takes 2.0317 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0358 ms 100.0%
  triton_mm_5436 0.0365 ms 98.2%
  triton_mm_5432 0.0372 ms 96.4%
  triton_mm_5429 0.0372 ms 96.2%
  triton_mm_5433 0.0378 ms 94.9%
  triton_mm_5425 0.0390 ms 91.8%
  triton_mm_5435 0.0395 ms 90.7%
  triton_mm_5424 0.0402 ms 89.1%
  triton_mm_5431 0.0403 ms 89.0%
  triton_mm_5423 0.0441 ms 81.2%
SingleProcess AUTOTUNE benchmarking takes 1.6572 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5474 0.8432 ms 100.0%
  mm 0.8771 ms 96.1%
  triton_mm_5475 1.0001 ms 84.3%
  triton_mm_5471 1.0104 ms 83.4%
  triton_mm_5467 1.0516 ms 80.2%
  triton_mm_5472 1.0698 ms 78.8%
  triton_mm_5468 1.1206 ms 75.2%
  triton_mm_5469 1.1414 ms 73.9%
  triton_mm_5464 1.3441 ms 62.7%
  triton_mm_5465 1.3763 ms 61.3%
SingleProcess AUTOTUNE benchmarking takes 2.1479 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0204 ms 100.0%
  mm 0.0214 ms 95.5%
  triton_mm_6447 0.0214 ms 95.2%
  triton_mm_6452 0.0232 ms 87.9%
  triton_mm_6446 0.0245 ms 83.3%
  triton_mm_6459 0.0254 ms 80.5%
  triton_mm_6456 0.0258 ms 79.2%
  triton_mm_6458 0.0273 ms 74.7%
  triton_mm_6455 0.0281 ms 72.6%
  triton_mm_6454 0.0316 ms 64.7%
SingleProcess AUTOTUNE benchmarking takes 1.7103 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5467 ms 100.0%
  bias_addmm 1.5659 ms 98.8%
  triton_mm_6513 1.8560 ms 83.3%
  triton_mm_6509 1.9060 ms 81.1%
  addmm 1.9268 ms 80.3%
  triton_mm_6517 2.0036 ms 77.2%
  triton_mm_6514 2.0975 ms 73.7%
  triton_mm_6510 2.1004 ms 73.6%
  triton_mm_6511 2.1774 ms 71.0%
  triton_mm_6506 2.5326 ms 61.1%
SingleProcess AUTOTUNE benchmarking takes 2.4015 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:00<1:26:32, 120.77s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8174 ms 100.0%
  mm 0.9407 ms 86.9%
  triton_mm_4987 0.9947 ms 82.2%
  triton_mm_4983 1.0044 ms 81.4%
  triton_mm_4991 1.0599 ms 77.1%
  triton_mm_4988 1.1048 ms 74.0%
  triton_mm_4984 1.1176 ms 73.1%
  triton_mm_4985 1.1516 ms 71.0%
  triton_mm_4980 1.3472 ms 60.7%
  triton_mm_4981 1.4033 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1571 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8260 ms 100.0%
  mm 0.8417 ms 98.1%
  triton_mm_5080 0.9849 ms 83.9%
  triton_mm_5076 1.0079 ms 82.0%
  triton_mm_5084 1.0679 ms 77.4%
  triton_mm_5077 1.1086 ms 74.5%
  triton_mm_5081 1.1099 ms 74.4%
  triton_mm_5078 1.1423 ms 72.3%
  triton_mm_5073 1.3373 ms 61.8%
  triton_mm_5074 1.4031 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1498 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5827 0.8254 ms 100.0%
  mm 0.8462 ms 97.5%
  triton_mm_5824 0.9859 ms 83.7%
  triton_mm_5820 1.0079 ms 81.9%
  triton_mm_5828 1.0693 ms 77.2%
  triton_mm_5821 1.0968 ms 75.3%
  triton_mm_5825 1.1104 ms 74.3%
  triton_mm_5822 1.1423 ms 72.3%
  triton_mm_5817 1.3369 ms 61.7%
  triton_mm_5818 1.4024 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1531 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5920 0.8269 ms 100.0%
  mm 0.8322 ms 99.4%
  triton_mm_5917 0.9876 ms 83.7%
  triton_mm_5913 1.0080 ms 82.0%
  triton_mm_5921 1.0696 ms 77.3%
  triton_mm_5918 1.1100 ms 74.5%
  triton_mm_5914 1.1198 ms 73.8%
  triton_mm_5915 1.1420 ms 72.4%
  triton_mm_5910 1.3367 ms 61.9%
  triton_mm_5911 1.4028 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1412 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6385 0.8273 ms 100.0%
  mm 0.8466 ms 97.7%
  triton_mm_6382 0.9966 ms 83.0%
  triton_mm_6378 1.0093 ms 82.0%
  triton_mm_6386 1.0767 ms 76.8%
  triton_mm_6383 1.1101 ms 74.5%
  triton_mm_6379 1.1327 ms 73.0%
  triton_mm_6380 1.1421 ms 72.4%
  triton_mm_6375 1.3330 ms 62.1%
  triton_mm_6376 1.3977 ms 59.2%
SingleProcess AUTOTUNE benchmarking takes 2.1406 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0366 ms 100.0%
  triton_mm_4899 0.0369 ms 99.3%
  triton_mm_4895 0.0378 ms 96.9%
  triton_mm_4892 0.0379 ms 96.6%
  triton_mm_4896 0.0382 ms 95.7%
  triton_mm_4888 0.0384 ms 95.2%
  triton_mm_4898 0.0398 ms 92.0%
  triton_mm_4887 0.0408 ms 89.7%
  triton_mm_4894 0.0409 ms 89.6%
  triton_mm_4886 0.0444 ms 82.4%
SingleProcess AUTOTUNE benchmarking takes 1.7167 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4909 0.0344 ms 100.0%
  triton_mm_4914 0.0350 ms 98.2%
  triton_mm_4908 0.0359 ms 95.6%
  triton_mm_4910 0.0360 ms 95.5%
  triton_mm_4906 0.0360 ms 95.4%
  triton_mm_4911 0.0361 ms 95.1%
  triton_mm_4913 0.0363 ms 94.7%
  triton_mm_4904 0.0380 ms 90.3%
  triton_mm_4917 0.0383 ms 89.8%
  triton_mm_4907 0.0390 ms 88.1%
SingleProcess AUTOTUNE benchmarking takes 2.1331 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6386 ms 100.0%
  bias_addmm 0.6430 ms 99.3%
  triton_mm_4932 0.7464 ms 85.6%
  triton_mm_4928 0.7626 ms 83.7%
  addmm 0.7937 ms 80.5%
  triton_mm_4936 0.8395 ms 76.1%
  triton_mm_4933 0.8399 ms 76.0%
  triton_mm_4929 0.8533 ms 74.8%
  triton_mm_4930 0.8756 ms 72.9%
  triton_mm_4925 1.0072 ms 63.4%
SingleProcess AUTOTUNE benchmarking takes 2.2442 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2260 ms 100.0%
  mm 0.2368 ms 95.4%
  triton_mm_4951 0.2588 ms 87.3%
  triton_mm_4947 0.2693 ms 83.9%
  triton_mm_4952 0.2815 ms 80.3%
  triton_mm_4955 0.2897 ms 78.0%
  triton_mm_4948 0.2961 ms 76.3%
  triton_mm_4949 0.3092 ms 73.1%
  triton_mm_4944 0.3450 ms 65.5%
  triton_mm_4945 0.3548 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.0277 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8376 ms 100.0%
  mm 0.8759 ms 95.6%
  triton_mm_5010 1.0026 ms 83.5%
  triton_mm_5006 1.0126 ms 82.7%
  triton_mm_5002 1.0541 ms 79.5%
  triton_mm_5007 1.0759 ms 77.9%
  triton_mm_5003 1.1315 ms 74.0%
  triton_mm_5004 1.1325 ms 74.0%
  triton_mm_4999 1.3474 ms 62.2%
  triton_mm_5000 1.3644 ms 61.4%
SingleProcess AUTOTUNE benchmarking takes 2.1604 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0206 ms 100.0%
  triton_mm_6447 0.0207 ms 99.2%
  mm 0.0214 ms 96.3%
  triton_mm_6446 0.0239 ms 86.0%
  triton_mm_6452 0.0242 ms 84.9%
  triton_mm_6459 0.0248 ms 83.0%
  triton_mm_6456 0.0270 ms 76.3%
  triton_mm_6458 0.0275 ms 74.8%
  triton_mm_6455 0.0292 ms 70.4%
  triton_mm_6454 0.0308 ms 66.7%
SingleProcess AUTOTUNE benchmarking takes 1.7114 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5516 ms 100.0%
  bias_addmm 1.5711 ms 98.8%
  triton_mm_6513 1.8618 ms 83.3%
  addmm 1.9126 ms 81.1%
  triton_mm_6509 1.9256 ms 80.6%
  triton_mm_6517 2.0257 ms 76.6%
  triton_mm_6514 2.1013 ms 73.8%
  triton_mm_6510 2.1200 ms 73.2%
  triton_mm_6511 2.1644 ms 71.7%
  triton_mm_6506 2.5346 ms 61.2%
SingleProcess AUTOTUNE benchmarking takes 2.4051 seconds and 0.0012 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:00<1:26:33, 120.78s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8417 ms 100.0%
  mm 0.9385 ms 89.7%
  triton_mm_4987 1.0098 ms 83.4%
  triton_mm_4983 1.0236 ms 82.2%
  triton_mm_4991 1.0843 ms 77.6%
  triton_mm_4988 1.1310 ms 74.4%
  triton_mm_4984 1.1404 ms 73.8%
  triton_mm_4985 1.1670 ms 72.1%
  triton_mm_4980 1.3591 ms 61.9%
  triton_mm_4981 1.4274 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1638 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8512 ms 100.0%
  mm 0.8526 ms 99.8%
  triton_mm_5080 1.0053 ms 84.7%
  triton_mm_5076 1.0391 ms 81.9%
  triton_mm_5084 1.0872 ms 78.3%
  triton_mm_5081 1.1317 ms 75.2%
  triton_mm_5077 1.1321 ms 75.2%
  triton_mm_5078 1.1610 ms 73.3%
  triton_mm_5073 1.3615 ms 62.5%
  triton_mm_5074 1.4288 ms 59.6%
SingleProcess AUTOTUNE benchmarking takes 2.1632 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5176 0.8508 ms 100.0%
  mm 0.8536 ms 99.7%
  triton_mm_5173 1.0054 ms 84.6%
  triton_mm_5169 1.0385 ms 81.9%
  triton_mm_5177 1.0884 ms 78.2%
  triton_mm_5174 1.1330 ms 75.1%
  triton_mm_5170 1.1333 ms 75.1%
  triton_mm_5171 1.1645 ms 73.1%
  triton_mm_5166 1.3619 ms 62.5%
  triton_mm_5167 1.4296 ms 59.5%
SingleProcess AUTOTUNE benchmarking takes 2.1589 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5269 0.8419 ms 100.0%
  mm 0.8529 ms 98.7%
  triton_mm_5266 1.0223 ms 82.4%
  triton_mm_5262 1.0395 ms 81.0%
  triton_mm_5270 1.0873 ms 77.4%
  triton_mm_5263 1.1315 ms 74.4%
  triton_mm_5267 1.1329 ms 74.3%
  triton_mm_5264 1.1684 ms 72.1%
  triton_mm_5259 1.3601 ms 61.9%
  triton_mm_5260 1.4271 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1572 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5641 0.8418 ms 100.0%
  mm 0.8619 ms 97.7%
  triton_mm_5638 1.0173 ms 82.7%
  triton_mm_5634 1.0270 ms 82.0%
  triton_mm_5642 1.0880 ms 77.4%
  triton_mm_5635 1.1314 ms 74.4%
  triton_mm_5639 1.1326 ms 74.3%
  triton_mm_5636 1.1636 ms 72.3%
  triton_mm_5631 1.3614 ms 61.8%
  triton_mm_5640 1.4352 ms 58.7%
SingleProcess AUTOTUNE benchmarking takes 2.1559 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6478 0.8420 ms 100.0%
  mm 0.8528 ms 98.7%
  triton_mm_6475 1.0059 ms 83.7%
  triton_mm_6471 1.0287 ms 81.9%
  triton_mm_6479 1.0864 ms 77.5%
  triton_mm_6476 1.1324 ms 74.4%
  triton_mm_6472 1.1324 ms 74.4%
  triton_mm_6473 1.1601 ms 72.6%
  triton_mm_6468 1.3616 ms 61.8%
  triton_mm_6469 1.4288 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1588 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0367 ms 100.0%
  triton_mm_4892 0.0369 ms 99.7%
  triton_mm_4899 0.0374 ms 98.2%
  triton_mm_4895 0.0375 ms 98.0%
  triton_mm_4896 0.0380 ms 96.6%
  triton_mm_4888 0.0386 ms 95.3%
  triton_mm_4898 0.0396 ms 92.8%
  triton_mm_4887 0.0404 ms 91.0%
  triton_mm_4894 0.0415 ms 88.4%
  triton_mm_4886 0.0439 ms 83.7%
SingleProcess AUTOTUNE benchmarking takes 1.7223 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4909 0.0342 ms 100.0%
  triton_mm_4908 0.0346 ms 98.7%
  triton_mm_4914 0.0347 ms 98.6%
  triton_mm_4911 0.0351 ms 97.4%
  triton_mm_4913 0.0351 ms 97.4%
  triton_mm_4910 0.0357 ms 95.8%
  triton_mm_4906 0.0370 ms 92.5%
  triton_mm_4917 0.0380 ms 89.9%
  triton_mm_4904 0.0387 ms 88.3%
  triton_mm_4907 0.0388 ms 88.1%
SingleProcess AUTOTUNE benchmarking takes 2.1403 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6476 ms 100.0%
  bias_addmm 0.6531 ms 99.2%
  triton_mm_4932 0.7611 ms 85.1%
  triton_mm_4928 0.7718 ms 83.9%
  addmm 0.8077 ms 80.2%
  triton_mm_4936 0.8486 ms 76.3%
  triton_mm_4933 0.8558 ms 75.7%
  triton_mm_4929 0.8717 ms 74.3%
  triton_mm_4930 0.8894 ms 72.8%
  triton_mm_4925 1.0265 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.2543 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2265 ms 100.0%
  mm 0.2389 ms 94.8%
  triton_mm_4951 0.2592 ms 87.4%
  triton_mm_4947 0.2692 ms 84.1%
  triton_mm_4952 0.2831 ms 80.0%
  triton_mm_4955 0.2916 ms 77.7%
  triton_mm_4948 0.2973 ms 76.2%
  triton_mm_4949 0.3103 ms 73.0%
  triton_mm_4944 0.3446 ms 65.7%
  triton_mm_4945 0.3557 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.0357 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8433 ms 100.0%
  mm 0.8829 ms 95.5%
  triton_mm_5010 1.0093 ms 83.5%
  triton_mm_5006 1.0265 ms 82.2%
  triton_mm_5002 1.0647 ms 79.2%
  triton_mm_5007 1.0898 ms 77.4%
  triton_mm_5003 1.1462 ms 73.6%
  triton_mm_5004 1.1592 ms 72.7%
  triton_mm_4999 1.3669 ms 61.7%
  triton_mm_5000 1.3962 ms 60.4%
SingleProcess AUTOTUNE benchmarking takes 2.1587 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0212 ms 100.0%
  triton_mm_6447 0.0213 ms 99.2%
  mm 0.0214 ms 98.9%
  triton_mm_6452 0.0231 ms 91.6%
  triton_mm_6446 0.0240 ms 88.3%
  triton_mm_6459 0.0246 ms 85.8%
  triton_mm_6456 0.0257 ms 82.2%
  triton_mm_6458 0.0273 ms 77.6%
  triton_mm_6455 0.0281 ms 75.2%
  triton_mm_6454 0.0313 ms 67.5%
SingleProcess AUTOTUNE benchmarking takes 1.7610 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5820 ms 100.0%
  bias_addmm 1.5839 ms 99.9%
  triton_mm_6513 1.9021 ms 83.2%
  addmm 1.9446 ms 81.4%
  triton_mm_6509 1.9876 ms 79.6%
  triton_mm_6517 2.0221 ms 78.2%
  triton_mm_6514 2.1188 ms 74.7%
  triton_mm_6510 2.1228 ms 74.5%
  triton_mm_6511 2.2081 ms 71.6%
  triton_mm_6506 2.5623 ms 61.7%
SingleProcess AUTOTUNE benchmarking takes 2.4072 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:00<1:26:39, 120.91s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:03<35:53, 51.28s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:03<35:54, 51.29s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:03<35:54, 51.29s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:03<35:56, 51.35s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:04<19:20, 28.29s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:04<19:20, 28.30s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:04<19:20, 28.30s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:04<19:21, 28.33s/it]
Validation Progress:   9%|9         | 4/44 [02:05<11:40, 17.51s/it]
Validation Progress:   9%|9         | 4/44 [02:05<11:40, 17.51s/it]
Validation Progress:   9%|9         | 4/44 [02:05<11:40, 17.51s/it]
Validation Progress:   9%|9         | 4/44 [02:05<11:41, 17.53s/it]
Validation Progress:  11%|#1        | 5/44 [02:06<07:32, 11.61s/it]
Validation Progress:  11%|#1        | 5/44 [02:06<07:32, 11.61s/it]
Validation Progress:  11%|#1        | 5/44 [02:06<07:32, 11.61s/it]
Validation Progress:  11%|#1        | 5/44 [02:06<07:33, 11.63s/it]
Validation Progress:  14%|#3        | 6/44 [02:07<05:05,  8.03s/it]
Validation Progress:  14%|#3        | 6/44 [02:07<05:05,  8.03s/it]
Validation Progress:  14%|#3        | 6/44 [02:07<05:05,  8.03s/it]
Validation Progress:  14%|#3        | 6/44 [02:07<05:05,  8.04s/it]
Validation Progress:  16%|#5        | 7/44 [02:08<03:32,  5.75s/it]
Validation Progress:  16%|#5        | 7/44 [02:08<03:32,  5.75s/it]
Validation Progress:  16%|#5        | 7/44 [02:08<03:32,  5.75s/it]
Validation Progress:  16%|#5        | 7/44 [02:08<03:32,  5.75s/it]
Validation Progress:  18%|#8        | 8/44 [02:09<02:31,  4.22s/it]
Validation Progress:  18%|#8        | 8/44 [02:09<02:31,  4.22s/it]
Validation Progress:  18%|#8        | 8/44 [02:09<02:31,  4.22s/it]
Validation Progress:  18%|#8        | 8/44 [02:09<02:31,  4.22s/it]
Validation Progress:  20%|##        | 9/44 [02:10<01:51,  3.20s/it]
Validation Progress:  20%|##        | 9/44 [02:10<01:51,  3.20s/it]
Validation Progress:  20%|##        | 9/44 [02:10<01:51,  3.20s/it]
Validation Progress:  20%|##        | 9/44 [02:10<01:52,  3.20s/it]
Validation Progress:  23%|##2       | 10/44 [02:11<01:25,  2.52s/it]
Validation Progress:  23%|##2       | 10/44 [02:11<01:25,  2.53s/it]
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Validation Progress: 100%|##########| 44/44 [02:49<00:00,  1.10s/it]
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 10%|9         | 76/781 [00:04<00:42, 16.52it/s]
 10%|9         | 78/781 [00:04<00:42, 16.38it/s]
 10%|#         | 80/781 [00:04<00:42, 16.40it/s]
 10%|#         | 82/781 [00:04<00:42, 16.43it/s]
 11%|#         | 84/781 [00:04<00:42, 16.39it/s]
 11%|#1        | 86/781 [00:05<00:42, 16.31it/s]
 11%|#1        | 88/781 [00:05<00:42, 16.24it/s]
 12%|#1        | 90/781 [00:05<00:42, 16.35it/s]
 12%|#1        | 92/781 [00:05<00:41, 16.43it/s]
 12%|#2        | 94/781 [00:05<00:41, 16.48it/s]
 12%|#2        | 96/781 [00:05<00:41, 16.48it/s]
 13%|#2        | 98/781 [00:05<00:41, 16.58it/s]
 13%|#2        | 100/781 [00:05<00:41, 16.48it/s]
 13%|#3        | 102/781 [00:06<00:41, 16.40it/s]
 13%|#3        | 104/781 [00:06<00:41, 16.47it/s]
 14%|#3        | 106/781 [00:06<00:40, 16.46it/s]
 14%|#3        | 108/781 [00:06<00:40, 16.46it/s]
 14%|#4        | 110/781 [00:06<00:40, 16.44it/s]
 14%|#4        | 112/781 [00:06<00:40, 16.47it/s]
 15%|#4        | 114/781 [00:06<00:40, 16.58it/s]
 15%|#4        | 116/781 [00:06<00:41, 16.06it/s]
 15%|#5        | 118/781 [00:07<00:40, 16.20it/s]
 15%|#5        | 120/781 [00:07<00:41, 16.10it/s]
 16%|#5        | 122/781 [00:07<00:40, 16.26it/s]
 16%|#5        | 124/781 [00:07<00:40, 16.25it/s]
 16%|#6        | 126/781 [00:07<00:40, 16.19it/s]
 16%|#6        | 128/781 [00:07<00:40, 16.25it/s]
 17%|#6        | 130/781 [00:07<00:40, 16.25it/s]
 17%|#6        | 132/781 [00:07<00:39, 16.44it/s]
 17%|#7        | 134/781 [00:08<00:39, 16.53it/s]
 17%|#7        | 136/781 [00:08<00:39, 16.52it/s]
 18%|#7        | 138/781 [00:08<00:38, 16.67it/s]
 18%|#7        | 140/781 [00:08<00:38, 16.72it/s]
 18%|#8        | 142/781 [00:08<00:37, 16.86it/s]
 18%|#8        | 144/781 [00:08<00:37, 16.89it/s]
 19%|#8        | 146/781 [00:08<00:37, 16.99it/s]
 19%|#8        | 148/781 [00:08<00:37, 17.07it/s]
 19%|#9        | 150/781 [00:08<00:37, 17.05it/s]
 19%|#9        | 152/781 [00:09<00:37, 16.97it/s]
 20%|#9        | 154/781 [00:09<00:37, 16.87it/s]
 20%|#9        | 156/781 [00:09<00:36, 17.05it/s]
 20%|##        | 158/781 [00:09<00:36, 17.07it/s]
 20%|##        | 160/781 [00:09<00:36, 16.89it/s]
 21%|##        | 162/781 [00:09<00:36, 17.04it/s]
 21%|##        | 164/781 [00:09<00:36, 17.10it/s]
 21%|##1       | 166/781 [00:09<00:35, 17.17it/s]
 22%|##1       | 168/781 [00:10<00:35, 17.15it/s]
 22%|##1       | 170/781 [00:10<00:35, 17.23it/s]
 22%|##2       | 172/781 [00:10<00:35, 17.34it/s]
 22%|##2       | 174/781 [00:10<00:34, 17.35it/s]
 23%|##2       | 176/781 [00:10<00:34, 17.38it/s]
 23%|##2       | 178/781 [00:10<00:34, 17.43it/s]
 23%|##3       | 180/781 [00:10<00:34, 17.50it/s]
 23%|##3       | 182/781 [00:10<00:34, 17.53it/s]
 24%|##3       | 184/781 [00:10<00:34, 17.48it/s]
 24%|##3       | 186/781 [00:11<00:34, 17.45it/s]
 24%|##4       | 188/781 [00:11<00:34, 17.15it/s]
 24%|##4       | 190/781 [00:11<00:34, 17.23it/s]
 25%|##4       | 192/781 [00:11<00:34, 17.31it/s]
 25%|##4       | 194/781 [00:11<00:33, 17.32it/s]
 25%|##5       | 196/781 [00:11<00:33, 17.22it/s]
 25%|##5       | 198/781 [00:11<00:33, 17.22it/s]
 26%|##5       | 200/781 [00:11<00:33, 17.24it/s]
 26%|##5       | 202/781 [00:11<00:33, 17.26it/s]
 26%|##6       | 204/781 [00:12<00:33, 17.12it/s]
 26%|##6       | 206/781 [00:12<00:33, 17.08it/s]
 27%|##6       | 208/781 [00:12<00:33, 17.23it/s]
 27%|##6       | 210/781 [00:12<00:33, 17.30it/s]
 27%|##7       | 212/781 [00:12<00:33, 17.09it/s]
 27%|##7       | 214/781 [00:12<00:32, 17.22it/s]
 28%|##7       | 216/781 [00:12<00:32, 17.31it/s]
 28%|##7       | 218/781 [00:12<00:32, 17.21it/s]
 28%|##8       | 220/781 [00:13<00:32, 17.26it/s]
 28%|##8       | 222/781 [00:13<00:32, 17.28it/s]
 29%|##8       | 224/781 [00:13<00:32, 17.27it/s]
 29%|##8       | 226/781 [00:13<00:32, 17.19it/s]
 29%|##9       | 228/781 [00:13<00:32, 17.24it/s]
 29%|##9       | 230/781 [00:13<00:31, 17.32it/s]
 30%|##9       | 232/781 [00:13<00:31, 17.36it/s]
 30%|##9       | 234/781 [00:13<00:31, 17.27it/s]
 30%|###       | 236/781 [00:13<00:31, 17.30it/s]
 30%|###       | 238/781 [00:14<00:31, 17.26it/s]
 31%|###       | 240/781 [00:14<00:31, 17.30it/s]
 31%|###       | 242/781 [00:14<00:31, 16.98it/s]
 31%|###1      | 244/781 [00:14<00:31, 17.04it/s]
 31%|###1      | 246/781 [00:14<00:31, 17.03it/s]
 32%|###1      | 248/781 [00:14<00:31, 16.99it/s]
 32%|###2      | 250/781 [00:14<00:31, 16.91it/s]
 32%|###2      | 252/781 [00:14<00:31, 16.72it/s]
 33%|###2      | 254/781 [00:15<00:31, 16.62it/s]
 33%|###2      | 256/781 [00:15<00:32, 16.24it/s]
 33%|###3      | 258/781 [00:15<00:32, 16.25it/s]
 33%|###3      | 260/781 [00:15<00:32, 16.04it/s]
 34%|###3      | 262/781 [00:15<00:44, 11.74it/s]
 34%|###3      | 264/781 [00:15<00:40, 12.74it/s]
 34%|###4      | 266/781 [00:15<00:37, 13.61it/s]
 34%|###4      | 268/781 [00:16<00:35, 14.30it/s]
 35%|###4      | 270/781 [00:16<00:34, 14.75it/s]
 35%|###4      | 272/781 [00:16<00:33, 15.23it/s]
 35%|###5      | 274/781 [00:16<00:32, 15.62it/s]
 35%|###5      | 276/781 [00:16<00:31, 15.96it/s]
 36%|###5      | 278/781 [00:16<00:30, 16.27it/s]
 36%|###5      | 280/781 [00:16<00:30, 16.25it/s]
 36%|###6      | 282/781 [00:16<00:30, 16.27it/s]
 36%|###6      | 284/781 [00:17<00:30, 16.51it/s]
 37%|###6      | 286/781 [00:17<00:29, 16.64it/s]
 37%|###6      | 288/781 [00:17<00:29, 16.59it/s]
 37%|###7      | 290/781 [00:17<00:29, 16.71it/s]
 37%|###7      | 292/781 [00:17<00:29, 16.64it/s]
 38%|###7      | 294/781 [00:17<00:29, 16.74it/s]
 38%|###7      | 296/781 [00:17<00:28, 16.75it/s]
 38%|###8      | 298/781 [00:17<00:28, 16.77it/s]
 38%|###8      | 300/781 [00:17<00:28, 16.70it/s]
 39%|###8      | 302/781 [00:18<00:29, 16.41it/s]
 39%|###8      | 304/781 [00:18<00:29, 16.32it/s]
 39%|###9      | 306/781 [00:18<00:29, 16.38it/s]
 39%|###9      | 308/781 [00:18<00:28, 16.58it/s]
 40%|###9      | 310/781 [00:18<00:28, 16.57it/s]
 40%|###9      | 312/781 [00:18<00:28, 16.58it/s]
 40%|####      | 314/781 [00:18<00:28, 16.55it/s]
 40%|####      | 316/781 [00:18<00:28, 16.50it/s]
 41%|####      | 318/781 [00:19<00:28, 16.26it/s]
 41%|####      | 320/781 [00:19<00:28, 16.01it/s]
 41%|####1     | 322/781 [00:19<00:29, 15.82it/s]
 41%|####1     | 324/781 [00:19<00:28, 15.91it/s]
 42%|####1     | 326/781 [00:19<00:28, 15.93it/s]
 42%|####1     | 328/781 [00:19<00:28, 15.88it/s]
 42%|####2     | 330/781 [00:19<00:28, 15.78it/s]
 43%|####2     | 332/781 [00:19<00:28, 15.89it/s]
 43%|####2     | 334/781 [00:20<00:28, 15.91it/s]
 43%|####3     | 336/781 [00:20<00:28, 15.89it/s]
 43%|####3     | 338/781 [00:20<00:27, 15.89it/s]
 44%|####3     | 340/781 [00:20<00:27, 15.92it/s]
 44%|####3     | 342/781 [00:20<00:27, 15.95it/s]
 44%|####4     | 344/781 [00:20<00:27, 15.99it/s]
 44%|####4     | 346/781 [00:20<00:27, 16.04it/s]
 45%|####4     | 348/781 [00:20<00:26, 16.05it/s]
 45%|####4     | 350/781 [00:21<00:26, 16.06it/s]
 45%|####5     | 352/781 [00:21<00:26, 16.02it/s]
 45%|####5     | 354/781 [00:21<00:26, 16.02it/s]
 46%|####5     | 356/781 [00:21<00:26, 16.02it/s]
 46%|####5     | 358/781 [00:21<00:26, 15.99it/s]
 46%|####6     | 360/781 [00:21<00:26, 15.89it/s]
 46%|####6     | 362/781 [00:21<00:26, 15.82it/s]
 47%|####6     | 364/781 [00:21<00:26, 15.88it/s]
 47%|####6     | 366/781 [00:22<00:26, 15.92it/s]
 47%|####7     | 368/781 [00:22<00:25, 15.96it/s]
 47%|####7     | 370/781 [00:22<00:25, 15.96it/s]
 48%|####7     | 372/781 [00:22<00:25, 15.87it/s]
 48%|####7     | 374/781 [00:22<00:25, 15.85it/s]
 48%|####8     | 376/781 [00:22<00:25, 15.65it/s]
 48%|####8     | 378/781 [00:22<00:25, 15.59it/s]
 49%|####8     | 380/781 [00:22<00:25, 15.57it/s]
 49%|####8     | 382/781 [00:23<00:25, 15.50it/s]
 49%|####9     | 384/781 [00:23<00:25, 15.57it/s]
 49%|####9     | 386/781 [00:23<00:25, 15.68it/s]
 50%|####9     | 388/781 [00:23<00:25, 15.69it/s]
 50%|####9     | 390/781 [00:23<00:24, 15.71it/s]
 50%|#####     | 392/781 [00:23<00:24, 15.71it/s]
 50%|#####     | 394/781 [00:23<00:24, 15.64it/s]
 51%|#####     | 396/781 [00:24<00:24, 15.64it/s]
 51%|#####     | 398/781 [00:24<00:24, 15.61it/s]
 51%|#####1    | 400/781 [00:24<00:24, 15.62it/s]
 51%|#####1    | 402/781 [00:24<00:24, 15.63it/s]
 52%|#####1    | 404/781 [00:24<00:24, 15.56it/s]
 52%|#####1    | 406/781 [00:24<00:24, 15.48it/s]
 52%|#####2    | 408/781 [00:24<00:24, 15.52it/s]
 52%|#####2    | 410/781 [00:24<00:23, 15.56it/s]
 53%|#####2    | 412/781 [00:25<00:23, 15.66it/s]
 53%|#####3    | 414/781 [00:25<00:23, 15.56it/s]
 53%|#####3    | 416/781 [00:25<00:23, 15.51it/s]
 54%|#####3    | 418/781 [00:25<00:23, 15.40it/s]
 54%|#####3    | 420/781 [00:25<00:23, 15.42it/s]
 54%|#####4    | 422/781 [00:25<00:23, 15.57it/s]
 54%|#####4    | 424/781 [00:25<00:22, 15.62it/s]
 55%|#####4    | 426/781 [00:25<00:22, 15.68it/s]
 55%|#####4    | 428/781 [00:26<00:22, 15.74it/s]
 55%|#####5    | 430/781 [00:26<00:22, 15.45it/s]
 55%|#####5    | 432/781 [00:26<00:22, 15.43it/s]
 56%|#####5    | 434/781 [00:26<00:22, 15.53it/s]
 56%|#####5    | 436/781 [00:26<00:22, 15.40it/s]
 56%|#####6    | 438/781 [00:26<00:22, 15.47it/s]
 56%|#####6    | 440/781 [00:26<00:22, 15.42it/s]
 57%|#####6    | 442/781 [00:26<00:21, 15.57it/s]
 57%|#####6    | 444/781 [00:27<00:21, 15.73it/s]
 57%|#####7    | 446/781 [00:27<00:21, 15.86it/s]
 57%|#####7    | 448/781 [00:27<00:20, 15.92it/s]
 58%|#####7    | 450/781 [00:27<00:20, 15.96it/s]
 58%|#####7    | 452/781 [00:27<00:20, 15.84it/s]
 58%|#####8    | 454/781 [00:27<00:20, 15.80it/s]
 58%|#####8    | 456/781 [00:27<00:20, 15.87it/s]
 59%|#####8    | 458/781 [00:27<00:20, 15.88it/s]
 59%|#####8    | 460/781 [00:28<00:20, 15.93it/s]
 59%|#####9    | 462/781 [00:28<00:20, 15.88it/s]
 59%|#####9    | 464/781 [00:28<00:19, 15.92it/s]
 60%|#####9    | 466/781 [00:28<00:19, 15.93it/s]
 60%|#####9    | 468/781 [00:28<00:19, 15.86it/s]
 60%|######    | 470/781 [00:28<00:19, 15.82it/s]
 60%|######    | 472/781 [00:28<00:19, 15.78it/s]
 61%|######    | 474/781 [00:28<00:19, 15.77it/s]
 61%|######    | 476/781 [00:29<00:19, 15.61it/s]
 61%|######1   | 478/781 [00:29<00:19, 15.42it/s]
 61%|######1   | 480/781 [00:29<00:19, 15.60it/s]
 62%|######1   | 482/781 [00:29<00:19, 15.73it/s]
 62%|######1   | 484/781 [00:29<00:18, 15.79it/s]
 62%|######2   | 486/781 [00:29<00:18, 15.85it/s]
 62%|######2   | 488/781 [00:29<00:18, 15.92it/s]
 63%|######2   | 490/781 [00:29<00:18, 15.89it/s]
 63%|######2   | 492/781 [00:30<00:18, 15.88it/s]
 63%|######3   | 494/781 [00:30<00:18, 15.91it/s]
 64%|######3   | 496/781 [00:30<00:17, 15.95it/s]
 64%|######3   | 498/781 [00:30<00:17, 15.88it/s]
 64%|######4   | 500/781 [00:30<00:17, 15.86it/s]
 64%|######4   | 502/781 [00:30<00:17, 15.77it/s]
 65%|######4   | 504/781 [00:30<00:17, 15.75it/s]
 65%|######4   | 506/781 [00:31<00:17, 15.76it/s]
 65%|######5   | 508/781 [00:31<00:17, 15.83it/s]
 65%|######5   | 510/781 [00:31<00:17, 15.85it/s]
 66%|######5   | 512/781 [00:31<00:17, 15.79it/s]
 66%|######5   | 514/781 [00:31<00:16, 15.84it/s]
 66%|######6   | 516/781 [00:31<00:16, 15.84it/s]
 66%|######6   | 518/781 [00:31<00:16, 15.86it/s]
 67%|######6   | 520/781 [00:32<00:28,  9.23it/s]
 67%|######6   | 522/781 [00:32<00:24, 10.57it/s]
 67%|######7   | 524/781 [00:32<00:21, 11.78it/s]
 67%|######7   | 526/781 [00:32<00:19, 12.78it/s]
 68%|######7   | 528/781 [00:32<00:18, 13.57it/s]
 68%|######7   | 530/781 [00:32<00:17, 14.22it/s]
 68%|######8   | 532/781 [00:32<00:16, 14.72it/s]
 68%|######8   | 534/781 [00:33<00:16, 14.96it/s]
 69%|######8   | 536/781 [00:33<00:16, 15.08it/s]
 69%|######8   | 538/781 [00:33<00:15, 15.23it/s]
 69%|######9   | 540/781 [00:33<00:15, 15.43it/s]
 69%|######9   | 542/781 [00:33<00:15, 15.59it/s]
 70%|######9   | 544/781 [00:33<00:15, 15.71it/s]
 70%|######9   | 546/781 [00:33<00:14, 15.76it/s]
 70%|#######   | 548/781 [00:33<00:14, 15.84it/s]
 70%|#######   | 550/781 [00:34<00:14, 15.90it/s]
 71%|#######   | 552/781 [00:34<00:14, 15.91it/s]
 71%|#######   | 554/781 [00:34<00:14, 15.89it/s]
 71%|#######1  | 556/781 [00:34<00:14, 15.78it/s]
 71%|#######1  | 558/781 [00:34<00:14, 15.86it/s]
 72%|#######1  | 560/781 [00:34<00:14, 15.54it/s]
 72%|#######1  | 562/781 [00:34<00:14, 15.51it/s]
 72%|#######2  | 564/781 [00:34<00:13, 15.55it/s]
 72%|#######2  | 566/781 [00:35<00:13, 15.52it/s]
 73%|#######2  | 568/781 [00:35<00:13, 15.46it/s]
 73%|#######2  | 570/781 [00:35<00:13, 15.60it/s]
 73%|#######3  | 572/781 [00:35<00:13, 15.57it/s]
 73%|#######3  | 574/781 [00:35<00:13, 15.60it/s]
 74%|#######3  | 576/781 [00:35<00:13, 15.62it/s]
 74%|#######4  | 578/781 [00:35<00:12, 15.73it/s]
 74%|#######4  | 580/781 [00:36<00:12, 15.70it/s]
 75%|#######4  | 582/781 [00:36<00:12, 15.82it/s]
 75%|#######4  | 584/781 [00:36<00:12, 15.61it/s]
 75%|#######5  | 586/781 [00:36<00:12, 15.60it/s]
 75%|#######5  | 588/781 [00:36<00:12, 15.51it/s]
 76%|#######5  | 590/781 [00:36<00:12, 15.49it/s]
 76%|#######5  | 592/781 [00:36<00:12, 15.54it/s]
 76%|#######6  | 594/781 [00:36<00:11, 15.84it/s]
 76%|#######6  | 596/781 [00:37<00:11, 16.09it/s]
 77%|#######6  | 598/781 [00:37<00:11, 16.27it/s]
 77%|#######6  | 600/781 [00:37<00:11, 16.29it/s]
 77%|#######7  | 602/781 [00:37<00:11, 16.03it/s]
 77%|#######7  | 604/781 [00:37<00:11, 15.98it/s]
 78%|#######7  | 606/781 [00:37<00:10, 16.22it/s]
 78%|#######7  | 608/781 [00:37<00:10, 16.52it/s]
 78%|#######8  | 610/781 [00:37<00:10, 16.81it/s]
 78%|#######8  | 612/781 [00:37<00:09, 16.93it/s]
 79%|#######8  | 614/781 [00:38<00:09, 16.94it/s]
 79%|#######8  | 616/781 [00:38<00:09, 16.92it/s]
 79%|#######9  | 618/781 [00:38<00:09, 16.76it/s]
 79%|#######9  | 620/781 [00:38<00:09, 16.80it/s]
 80%|#######9  | 622/781 [00:38<00:09, 16.84it/s]
 80%|#######9  | 624/781 [00:38<00:09, 16.85it/s]
 80%|########  | 626/781 [00:38<00:09, 16.93it/s]
 80%|########  | 628/781 [00:38<00:08, 17.10it/s]
 81%|########  | 630/781 [00:39<00:08, 17.25it/s]
 81%|########  | 632/781 [00:39<00:08, 17.34it/s]
 81%|########1 | 634/781 [00:39<00:08, 17.29it/s]
 81%|########1 | 636/781 [00:39<00:08, 17.21it/s]
 82%|########1 | 638/781 [00:39<00:08, 17.14it/s]
 82%|########1 | 640/781 [00:39<00:08, 17.05it/s]
 82%|########2 | 642/781 [00:39<00:08, 17.02it/s]
 82%|########2 | 644/781 [00:39<00:08, 17.01it/s]
 83%|########2 | 646/781 [00:39<00:07, 16.92it/s]
 83%|########2 | 648/781 [00:40<00:07, 17.05it/s]
 83%|########3 | 650/781 [00:40<00:07, 17.05it/s]
 83%|########3 | 652/781 [00:40<00:07, 17.13it/s]
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Validation Progress:  98%|#########7| 43/44 [00:49<00:01,  1.19s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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  with torch.cuda.amp.autocast(enabled=False):

Validation Progress: 100%|##########| 44/44 [00:51<00:00,  1.49s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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  with torch.cuda.amp.autocast(enabled=False):

Validation Progress: 100%|##########| 44/44 [00:51<00:00,  1.49s/it]
Validation Progress: 100%|##########| 44/44 [00:51<00:00,  1.17s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:02<00:00,  2.42s/it]
100%|##########| 1/1 [00:02<00:00,  2.42s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:09, 16.34it/s]
  3%|2         | 4/157 [00:00<00:09, 16.66it/s]
  4%|3         | 6/157 [00:00<00:09, 16.61it/s]
  5%|5         | 8/157 [00:00<00:08, 17.06it/s]
  6%|6         | 10/157 [00:00<00:08, 17.33it/s]
  8%|7         | 12/157 [00:00<00:08, 17.36it/s]
  9%|8         | 14/157 [00:00<00:08, 17.51it/s]
 10%|#         | 16/157 [00:00<00:08, 17.55it/s]
 11%|#1        | 18/157 [00:01<00:07, 17.55it/s]
 13%|#2        | 20/157 [00:01<00:07, 17.66it/s]
 14%|#4        | 22/157 [00:01<00:07, 17.78it/s]
 15%|#5        | 24/157 [00:01<00:07, 17.93it/s]
 17%|#6        | 26/157 [00:01<00:07, 17.95it/s]
 18%|#7        | 28/157 [00:01<00:07, 17.99it/s]
 19%|#9        | 30/157 [00:01<00:07, 17.67it/s]
 20%|##        | 32/157 [00:01<00:07, 17.24it/s]
 22%|##1       | 34/157 [00:01<00:07, 17.15it/s]
 23%|##2       | 36/157 [00:02<00:07, 17.21it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.73it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.61it/s]
 27%|##6       | 42/157 [00:02<00:06, 16.69it/s]
 28%|##8       | 44/157 [00:02<00:06, 16.78it/s]
 29%|##9       | 46/157 [00:02<00:06, 16.83it/s]
 31%|###       | 48/157 [00:02<00:06, 16.52it/s]
 32%|###1      | 50/157 [00:02<00:06, 16.11it/s]
 33%|###3      | 52/157 [00:03<00:06, 15.88it/s]
 34%|###4      | 54/157 [00:03<00:06, 15.82it/s]
 36%|###5      | 56/157 [00:03<00:06, 15.95it/s]
 37%|###6      | 58/157 [00:03<00:06, 15.93it/s]
 38%|###8      | 60/157 [00:03<00:06, 15.95it/s]
 39%|###9      | 62/157 [00:03<00:05, 16.07it/s]
 41%|####      | 64/157 [00:03<00:05, 15.90it/s]
 42%|####2     | 66/157 [00:03<00:05, 15.99it/s]
 43%|####3     | 68/157 [00:04<00:05, 15.81it/s]
 45%|####4     | 70/157 [00:04<00:05, 15.67it/s]
 46%|####5     | 72/157 [00:04<00:05, 15.72it/s]
 47%|####7     | 74/157 [00:04<00:05, 15.78it/s]
 48%|####8     | 76/157 [00:04<00:05, 15.78it/s]
 50%|####9     | 78/157 [00:04<00:05, 15.79it/s]
 51%|#####     | 80/157 [00:04<00:04, 15.74it/s]
 52%|#####2    | 82/157 [00:04<00:04, 15.69it/s]
 54%|#####3    | 84/157 [00:05<00:04, 15.41it/s]
 55%|#####4    | 86/157 [00:05<00:04, 15.44it/s]
 56%|#####6    | 88/157 [00:05<00:04, 15.43it/s]
 57%|#####7    | 90/157 [00:05<00:04, 15.46it/s]
 59%|#####8    | 92/157 [00:05<00:04, 15.44it/s]
 60%|#####9    | 94/157 [00:05<00:04, 15.55it/s]
 61%|######1   | 96/157 [00:05<00:03, 15.61it/s]
 62%|######2   | 98/157 [00:05<00:03, 15.62it/s]
 64%|######3   | 100/157 [00:06<00:03, 15.70it/s]
 65%|######4   | 102/157 [00:06<00:03, 15.66it/s]
 66%|######6   | 104/157 [00:06<00:03, 15.64it/s]
 68%|######7   | 106/157 [00:06<00:03, 15.68it/s]
 69%|######8   | 108/157 [00:06<00:03, 15.57it/s]
 70%|#######   | 110/157 [00:06<00:03, 15.48it/s]
 71%|#######1  | 112/157 [00:06<00:02, 15.53it/s]
 73%|#######2  | 114/157 [00:07<00:02, 15.61it/s]
 74%|#######3  | 116/157 [00:07<00:02, 15.43it/s]
 75%|#######5  | 118/157 [00:07<00:02, 15.32it/s]
 76%|#######6  | 120/157 [00:07<00:02, 15.25it/s]
 78%|#######7  | 122/157 [00:07<00:02, 15.31it/s]
 79%|#######8  | 124/157 [00:07<00:02, 15.38it/s]
 80%|########  | 126/157 [00:07<00:02, 15.41it/s]
 82%|########1 | 128/157 [00:07<00:01, 15.48it/s]
 83%|########2 | 130/157 [00:08<00:01, 15.53it/s]
 84%|########4 | 132/157 [00:08<00:01, 15.66it/s]
 85%|########5 | 134/157 [00:08<00:01, 15.70it/s]
 87%|########6 | 136/157 [00:08<00:01, 15.76it/s]
 88%|########7 | 138/157 [00:08<00:01, 15.74it/s]
 89%|########9 | 140/157 [00:08<00:01, 15.80it/s]
 90%|######### | 142/157 [00:08<00:00, 15.81it/s]
 92%|#########1| 144/157 [00:08<00:00, 15.88it/s]
 93%|#########2| 146/157 [00:09<00:00, 15.91it/s]
 94%|#########4| 148/157 [00:09<00:00, 15.85it/s]
 96%|#########5| 150/157 [00:09<00:00, 15.81it/s]
 97%|#########6| 152/157 [00:09<00:00, 15.78it/s]
 98%|#########8| 154/157 [00:09<00:00, 15.78it/s]
 99%|#########9| 156/157 [00:09<00:00, 15.73it/s]
100%|##########| 157/157 [00:09<00:00, 16.14it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:44, 17.57it/s]
  1%|          | 4/781 [00:00<00:43, 17.79it/s]
  1%|          | 6/781 [00:00<00:43, 17.68it/s]
  1%|1         | 8/781 [00:00<00:43, 17.96it/s]
  1%|1         | 10/781 [00:00<00:43, 17.71it/s]
  2%|1         | 12/781 [00:00<00:43, 17.64it/s]
  2%|1         | 14/781 [00:00<00:43, 17.81it/s]
  2%|2         | 16/781 [00:00<00:42, 17.86it/s]
  2%|2         | 18/781 [00:01<00:43, 17.60it/s]
  3%|2         | 20/781 [00:01<00:43, 17.65it/s]
  3%|2         | 22/781 [00:01<00:42, 17.82it/s]
  3%|3         | 24/781 [00:01<00:42, 17.96it/s]
  3%|3         | 26/781 [00:01<00:41, 18.06it/s]
  4%|3         | 28/781 [00:01<00:41, 18.06it/s]
  4%|3         | 30/781 [00:01<00:41, 17.92it/s]
  4%|4         | 32/781 [00:01<00:41, 17.97it/s]
  4%|4         | 34/781 [00:01<00:41, 18.05it/s]
  5%|4         | 36/781 [00:02<00:41, 18.11it/s]
  5%|4         | 38/781 [00:02<00:40, 18.18it/s]
  5%|5         | 40/781 [00:02<00:40, 18.14it/s]
  5%|5         | 42/781 [00:02<00:40, 18.21it/s]
  6%|5         | 44/781 [00:02<00:40, 18.25it/s]
  6%|5         | 46/781 [00:02<00:40, 18.25it/s]
  6%|6         | 48/781 [00:02<00:40, 18.07it/s]
  6%|6         | 50/781 [00:02<00:40, 18.11it/s]
  7%|6         | 52/781 [00:02<00:40, 18.17it/s]
  7%|6         | 54/781 [00:03<00:40, 18.17it/s]
  7%|7         | 56/781 [00:03<00:39, 18.15it/s]
  7%|7         | 58/781 [00:03<00:40, 17.98it/s]
  8%|7         | 60/781 [00:03<00:40, 17.88it/s]
  8%|7         | 62/781 [00:03<00:40, 17.76it/s]
  8%|8         | 64/781 [00:03<00:40, 17.74it/s]
  8%|8         | 66/781 [00:03<00:40, 17.69it/s]
  9%|8         | 68/781 [00:03<00:40, 17.63it/s]
  9%|8         | 70/781 [00:03<00:40, 17.77it/s]
  9%|9         | 72/781 [00:04<00:39, 17.84it/s]
  9%|9         | 74/781 [00:04<00:40, 17.53it/s]
 10%|9         | 76/781 [00:04<00:40, 17.56it/s]
 10%|9         | 78/781 [00:04<00:39, 17.76it/s]
 10%|#         | 80/781 [00:04<00:39, 17.87it/s]
 10%|#         | 82/781 [00:04<00:38, 17.97it/s]
 11%|#         | 84/781 [00:04<00:39, 17.82it/s]
 11%|#1        | 86/781 [00:04<00:38, 17.93it/s]
 11%|#1        | 88/781 [00:04<00:38, 18.01it/s]
 12%|#1        | 90/781 [00:05<00:38, 17.98it/s]
 12%|#1        | 92/781 [00:05<00:38, 18.10it/s]
 12%|#2        | 94/781 [00:05<00:38, 18.06it/s]
 12%|#2        | 96/781 [00:05<00:37, 18.13it/s]
 13%|#2        | 98/781 [00:05<00:37, 18.22it/s]
 13%|#2        | 100/781 [00:05<00:37, 18.21it/s]
 13%|#3        | 102/781 [00:05<00:52, 12.92it/s]
 13%|#3        | 104/781 [00:05<00:48, 14.06it/s]
 14%|#3        | 106/781 [00:06<00:45, 14.93it/s]
 14%|#3        | 108/781 [00:06<00:42, 15.67it/s]
 14%|#4        | 110/781 [00:06<00:41, 16.21it/s]
 14%|#4        | 112/781 [00:06<00:40, 16.61it/s]
 15%|#4        | 114/781 [00:06<00:39, 17.04it/s]
 15%|#4        | 116/781 [00:06<00:38, 17.11it/s]
 15%|#5        | 118/781 [00:06<00:38, 17.40it/s]
 15%|#5        | 120/781 [00:06<00:37, 17.63it/s]
 16%|#5        | 122/781 [00:06<00:37, 17.73it/s]
 16%|#5        | 124/781 [00:07<00:36, 17.80it/s]
 16%|#6        | 126/781 [00:07<00:36, 17.91it/s]
 16%|#6        | 128/781 [00:07<00:36, 17.86it/s]
 17%|#6        | 130/781 [00:07<00:36, 17.96it/s]
 17%|#6        | 132/781 [00:07<00:36, 17.88it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.76it/s]
 17%|#7        | 136/781 [00:07<00:36, 17.80it/s]
 18%|#7        | 138/781 [00:07<00:35, 17.88it/s]
 18%|#7        | 140/781 [00:07<00:35, 17.87it/s]
 18%|#8        | 142/781 [00:08<00:35, 17.88it/s]
 18%|#8        | 144/781 [00:08<00:35, 17.97it/s]
 19%|#8        | 146/781 [00:08<00:35, 18.09it/s]
 19%|#8        | 148/781 [00:08<00:34, 18.14it/s]
 19%|#9        | 150/781 [00:08<00:34, 18.21it/s]
 19%|#9        | 152/781 [00:08<00:34, 18.22it/s]
 20%|#9        | 154/781 [00:08<00:34, 18.21it/s]
 20%|#9        | 156/781 [00:08<00:34, 18.27it/s]
 20%|##        | 158/781 [00:08<00:34, 18.19it/s]
 20%|##        | 160/781 [00:09<00:34, 18.21it/s]
 21%|##        | 162/781 [00:09<00:33, 18.24it/s]
 21%|##        | 164/781 [00:09<00:33, 18.22it/s]
 21%|##1       | 166/781 [00:09<00:33, 18.20it/s]
 22%|##1       | 168/781 [00:09<00:34, 18.02it/s]
 22%|##1       | 170/781 [00:09<00:33, 17.99it/s]
 22%|##2       | 172/781 [00:09<00:34, 17.88it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.96it/s]
 23%|##2       | 176/781 [00:09<00:33, 18.03it/s]
 23%|##2       | 178/781 [00:10<00:33, 18.09it/s]
 23%|##3       | 180/781 [00:10<00:33, 18.15it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.98it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.99it/s]
 24%|##3       | 186/781 [00:10<00:33, 18.02it/s]
 24%|##4       | 188/781 [00:10<00:32, 18.05it/s]
 24%|##4       | 190/781 [00:10<00:32, 18.12it/s]
 25%|##4       | 192/781 [00:10<00:32, 18.15it/s]
 25%|##4       | 194/781 [00:10<00:32, 18.23it/s]
 25%|##5       | 196/781 [00:11<00:32, 18.20it/s]
 25%|##5       | 198/781 [00:11<00:31, 18.24it/s]
 26%|##5       | 200/781 [00:11<00:31, 18.21it/s]
 26%|##5       | 202/781 [00:11<00:31, 18.27it/s]
 26%|##6       | 204/781 [00:11<00:31, 18.27it/s]
 26%|##6       | 206/781 [00:11<00:31, 18.20it/s]
 27%|##6       | 208/781 [00:11<00:31, 18.22it/s]
 27%|##6       | 210/781 [00:11<00:31, 18.15it/s]
 27%|##7       | 212/781 [00:11<00:31, 18.13it/s]
 27%|##7       | 214/781 [00:12<00:31, 18.16it/s]
 28%|##7       | 216/781 [00:12<00:31, 17.82it/s]
 28%|##7       | 218/781 [00:12<00:31, 17.87it/s]
 28%|##8       | 220/781 [00:12<00:31, 17.99it/s]
 28%|##8       | 222/781 [00:12<00:30, 18.06it/s]
 29%|##8       | 224/781 [00:12<00:30, 18.11it/s]
 29%|##8       | 226/781 [00:12<00:30, 18.16it/s]
 29%|##9       | 228/781 [00:12<00:30, 18.12it/s]
 29%|##9       | 230/781 [00:12<00:30, 17.95it/s]
 30%|##9       | 232/781 [00:13<00:30, 18.04it/s]
 30%|##9       | 234/781 [00:13<00:30, 17.94it/s]
 30%|###       | 236/781 [00:13<00:30, 18.05it/s]
 30%|###       | 238/781 [00:13<00:29, 18.12it/s]
 31%|###       | 240/781 [00:13<00:29, 18.03it/s]
 31%|###       | 242/781 [00:13<00:29, 18.07it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.12it/s]
 31%|###1      | 246/781 [00:13<00:29, 18.17it/s]
 32%|###1      | 248/781 [00:13<00:29, 18.11it/s]
 32%|###2      | 250/781 [00:14<00:29, 18.13it/s]
 32%|###2      | 252/781 [00:14<00:29, 18.19it/s]
 33%|###2      | 254/781 [00:14<00:28, 18.24it/s]
 33%|###2      | 256/781 [00:14<00:28, 18.25it/s]
 33%|###3      | 258/781 [00:14<00:28, 18.14it/s]
 33%|###3      | 260/781 [00:14<00:28, 18.12it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.16it/s]
 34%|###3      | 264/781 [00:14<00:28, 18.15it/s]
 34%|###4      | 266/781 [00:14<00:28, 18.10it/s]
 34%|###4      | 268/781 [00:15<00:28, 18.16it/s]
 35%|###4      | 270/781 [00:15<00:28, 18.23it/s]
 35%|###4      | 272/781 [00:15<00:27, 18.26it/s]
 35%|###5      | 274/781 [00:15<00:27, 18.21it/s]
 35%|###5      | 276/781 [00:15<00:27, 18.17it/s]
 36%|###5      | 278/781 [00:15<00:27, 18.22it/s]
 36%|###5      | 280/781 [00:15<00:27, 17.92it/s]
 36%|###6      | 282/781 [00:15<00:27, 17.97it/s]
 36%|###6      | 284/781 [00:15<00:27, 17.97it/s]
 37%|###6      | 286/781 [00:16<00:27, 17.92it/s]
 37%|###6      | 288/781 [00:16<00:27, 17.97it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.91it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.91it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.80it/s]
 38%|###7      | 296/781 [00:16<00:27, 17.75it/s]
 38%|###8      | 298/781 [00:16<00:27, 17.44it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.68it/s]
 39%|###8      | 302/781 [00:16<00:27, 17.68it/s]
 39%|###8      | 304/781 [00:17<00:26, 17.71it/s]
 39%|###9      | 306/781 [00:17<00:26, 17.66it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.66it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.59it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.54it/s]
 40%|####      | 314/781 [00:17<00:26, 17.58it/s]
 40%|####      | 316/781 [00:17<00:26, 17.56it/s]
 41%|####      | 318/781 [00:17<00:26, 17.57it/s]
 41%|####      | 320/781 [00:17<00:26, 17.46it/s]
 41%|####1     | 322/781 [00:18<00:25, 17.69it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.84it/s]
 42%|####1     | 326/781 [00:18<00:25, 17.93it/s]
 42%|####1     | 328/781 [00:18<00:25, 18.00it/s]
 42%|####2     | 330/781 [00:18<00:24, 18.05it/s]
 43%|####2     | 332/781 [00:18<00:24, 18.13it/s]
 43%|####2     | 334/781 [00:18<00:24, 18.12it/s]
 43%|####3     | 336/781 [00:18<00:24, 18.13it/s]
 43%|####3     | 338/781 [00:18<00:24, 18.06it/s]
 44%|####3     | 340/781 [00:19<00:24, 18.14it/s]
 44%|####3     | 342/781 [00:19<00:24, 18.13it/s]
 44%|####4     | 344/781 [00:19<00:24, 17.77it/s]
 44%|####4     | 346/781 [00:19<00:24, 17.58it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.77it/s]
 45%|####4     | 350/781 [00:19<00:24, 17.74it/s]
 45%|####5     | 352/781 [00:19<00:24, 17.75it/s]
 45%|####5     | 354/781 [00:19<00:23, 17.83it/s]
 46%|####5     | 356/781 [00:19<00:23, 17.83it/s]
 46%|####5     | 358/781 [00:20<00:23, 17.94it/s]
 46%|####6     | 360/781 [00:20<00:23, 17.99it/s]
 46%|####6     | 362/781 [00:20<00:23, 17.83it/s]
 47%|####6     | 364/781 [00:20<00:23, 17.81it/s]
 47%|####6     | 366/781 [00:20<00:23, 17.83it/s]
 47%|####7     | 368/781 [00:20<00:23, 17.75it/s]
 47%|####7     | 370/781 [00:20<00:23, 17.45it/s]
 48%|####7     | 372/781 [00:20<00:23, 17.70it/s]
 48%|####7     | 374/781 [00:20<00:22, 17.88it/s]
 48%|####8     | 376/781 [00:21<00:22, 17.94it/s]
 48%|####8     | 378/781 [00:21<00:22, 17.81it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.95it/s]
 49%|####8     | 382/781 [00:21<00:22, 18.08it/s]
 49%|####9     | 384/781 [00:21<00:21, 18.09it/s]
 49%|####9     | 386/781 [00:21<00:21, 18.10it/s]
 50%|####9     | 388/781 [00:21<00:21, 17.95it/s]
 50%|####9     | 390/781 [00:21<00:21, 17.84it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.81it/s]
 50%|#####     | 394/781 [00:22<00:21, 17.82it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.84it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.82it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.82it/s]
 51%|#####1    | 402/781 [00:22<00:21, 17.70it/s]
 52%|#####1    | 404/781 [00:22<00:21, 17.78it/s]
 52%|#####1    | 406/781 [00:22<00:21, 17.61it/s]
 52%|#####2    | 408/781 [00:22<00:21, 17.71it/s]
 52%|#####2    | 410/781 [00:22<00:21, 17.45it/s]
 53%|#####2    | 412/781 [00:23<00:20, 17.63it/s]
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/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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Validation Progress:  48%|####7     | 21/44 [00:22<00:25,  1.09s/it]
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Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.12s/it]
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Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
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Validation Progress:  64%|######3   | 28/44 [00:29<00:17,  1.11s/it]
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Validation Progress:  66%|######5   | 29/44 [00:30<00:16,  1.08s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.11s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
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Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
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Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.10s/it]
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Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
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Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
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Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
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Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
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Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
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Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
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Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.15s/it]
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Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.15s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
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Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
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Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
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Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
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Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
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 22%|##1       | 168/781 [00:08<00:32, 19.06it/s]
 22%|##1       | 170/781 [00:08<00:31, 19.10it/s]
 22%|##2       | 172/781 [00:09<00:31, 19.17it/s]
 22%|##2       | 174/781 [00:09<00:31, 19.15it/s]
 23%|##2       | 176/781 [00:09<00:31, 19.12it/s]
 23%|##2       | 178/781 [00:09<00:31, 19.16it/s]
 23%|##3       | 180/781 [00:09<00:31, 18.98it/s]
 23%|##3       | 182/781 [00:09<00:31, 18.88it/s]
 24%|##3       | 184/781 [00:09<00:31, 18.88it/s]
 24%|##3       | 186/781 [00:09<00:31, 18.94it/s]
 24%|##4       | 188/781 [00:09<00:31, 19.07it/s]
 24%|##4       | 190/781 [00:10<00:30, 19.08it/s]
 25%|##4       | 192/781 [00:10<00:30, 19.18it/s]
 25%|##4       | 194/781 [00:10<00:30, 19.17it/s]
 25%|##5       | 196/781 [00:10<00:30, 19.09it/s]
 25%|##5       | 198/781 [00:10<00:30, 19.04it/s]
 26%|##5       | 200/781 [00:10<00:30, 19.09it/s]
 26%|##5       | 202/781 [00:10<00:30, 19.19it/s]
 26%|##6       | 204/781 [00:10<00:30, 19.06it/s]
 26%|##6       | 206/781 [00:10<00:30, 19.13it/s]
 27%|##6       | 208/781 [00:10<00:30, 19.04it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.91it/s]
 27%|##7       | 212/781 [00:11<00:30, 18.74it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.84it/s]
 28%|##7       | 216/781 [00:11<00:29, 18.99it/s]
 28%|##7       | 218/781 [00:11<00:29, 19.07it/s]
 28%|##8       | 220/781 [00:11<00:29, 19.09it/s]
 28%|##8       | 222/781 [00:11<00:30, 18.50it/s]
 29%|##8       | 224/781 [00:11<00:29, 18.67it/s]
 29%|##8       | 226/781 [00:11<00:29, 18.75it/s]
 29%|##9       | 228/781 [00:12<00:29, 19.02it/s]
 29%|##9       | 230/781 [00:12<00:28, 19.15it/s]
 30%|##9       | 232/781 [00:12<00:28, 19.36it/s]
 30%|##9       | 234/781 [00:12<00:28, 19.43it/s]
 30%|###       | 236/781 [00:12<00:28, 19.45it/s]
 30%|###       | 238/781 [00:12<00:28, 19.22it/s]
 31%|###       | 240/781 [00:12<00:28, 19.27it/s]
 31%|###       | 242/781 [00:12<00:27, 19.36it/s]
 31%|###1      | 244/781 [00:12<00:27, 19.37it/s]
 31%|###1      | 246/781 [00:12<00:27, 19.51it/s]
 32%|###1      | 248/781 [00:13<00:27, 19.60it/s]
 32%|###2      | 250/781 [00:13<00:27, 19.59it/s]
 32%|###2      | 252/781 [00:13<00:26, 19.61it/s]
 33%|###2      | 254/781 [00:13<00:26, 19.68it/s]
 33%|###2      | 256/781 [00:13<00:26, 19.54it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.31it/s]
 33%|###3      | 260/781 [00:13<00:26, 19.32it/s]
 34%|###3      | 262/781 [00:13<00:26, 19.37it/s]
 34%|###3      | 264/781 [00:13<00:27, 19.12it/s]
 34%|###4      | 266/781 [00:13<00:26, 19.33it/s]
 34%|###4      | 268/781 [00:14<00:26, 19.29it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.29it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.32it/s]
 35%|###5      | 274/781 [00:14<00:26, 19.43it/s]
 35%|###5      | 277/781 [00:14<00:25, 19.63it/s]
 36%|###5      | 279/781 [00:14<00:25, 19.71it/s]
 36%|###5      | 281/781 [00:14<00:25, 19.78it/s]
 36%|###6      | 283/781 [00:14<00:25, 19.80it/s]
 36%|###6      | 285/781 [00:14<00:25, 19.79it/s]
 37%|###6      | 287/781 [00:15<00:25, 19.61it/s]
 37%|###7      | 289/781 [00:15<00:25, 19.60it/s]
 37%|###7      | 291/781 [00:15<00:24, 19.66it/s]
 38%|###7      | 294/781 [00:15<00:24, 19.80it/s]
 38%|###8      | 297/781 [00:15<00:24, 19.83it/s]
 38%|###8      | 299/781 [00:15<00:24, 19.70it/s]
 39%|###8      | 301/781 [00:15<00:24, 19.56it/s]
 39%|###8      | 303/781 [00:15<00:24, 19.44it/s]
 39%|###9      | 305/781 [00:15<00:24, 19.39it/s]
 39%|###9      | 307/781 [00:16<00:24, 19.45it/s]
 40%|###9      | 309/781 [00:16<00:24, 19.37it/s]
 40%|###9      | 311/781 [00:16<00:24, 19.47it/s]
 40%|####      | 313/781 [00:16<00:24, 19.41it/s]
 40%|####      | 315/781 [00:16<00:23, 19.51it/s]
 41%|####      | 317/781 [00:16<00:23, 19.64it/s]
 41%|####      | 319/781 [00:16<00:23, 19.73it/s]
 41%|####1     | 321/781 [00:16<00:23, 19.73it/s]
 41%|####1     | 323/781 [00:16<00:23, 19.63it/s]
 42%|####1     | 325/781 [00:16<00:23, 19.53it/s]
 42%|####1     | 327/781 [00:17<00:23, 19.42it/s]
 42%|####2     | 329/781 [00:17<00:23, 19.32it/s]
 42%|####2     | 331/781 [00:17<00:23, 19.11it/s]
 43%|####2     | 333/781 [00:17<00:23, 19.24it/s]
 43%|####2     | 335/781 [00:17<00:23, 19.38it/s]
 43%|####3     | 337/781 [00:17<00:22, 19.46it/s]
 43%|####3     | 339/781 [00:17<00:22, 19.61it/s]
 44%|####3     | 341/781 [00:17<00:22, 19.67it/s]
 44%|####3     | 343/781 [00:17<00:22, 19.54it/s]
 44%|####4     | 345/781 [00:18<00:22, 19.51it/s]
 44%|####4     | 347/781 [00:18<00:22, 19.56it/s]
 45%|####4     | 349/781 [00:18<00:22, 19.63it/s]
 45%|####4     | 351/781 [00:18<00:21, 19.58it/s]
 45%|####5     | 353/781 [00:18<00:21, 19.64it/s]
 45%|####5     | 355/781 [00:18<00:21, 19.46it/s]
 46%|####5     | 357/781 [00:18<00:21, 19.32it/s]
 46%|####6     | 360/781 [00:18<00:21, 19.58it/s]
 46%|####6     | 362/781 [00:18<00:21, 19.66it/s]
 47%|####6     | 364/781 [00:18<00:21, 19.71it/s]
 47%|####6     | 366/781 [00:19<00:21, 19.60it/s]
 47%|####7     | 368/781 [00:19<00:21, 19.53it/s]
 47%|####7     | 370/781 [00:19<00:21, 19.37it/s]
 48%|####7     | 372/781 [00:19<00:21, 19.03it/s]
 48%|####7     | 374/781 [00:19<00:21, 19.12it/s]
 48%|####8     | 376/781 [00:19<00:21, 18.75it/s]
 48%|####8     | 378/781 [00:19<00:22, 18.12it/s]
 49%|####8     | 380/781 [00:19<00:22, 18.10it/s]
 49%|####8     | 382/781 [00:19<00:22, 17.90it/s]
 49%|####9     | 384/781 [00:20<00:22, 18.02it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.33it/s]
 50%|####9     | 388/781 [00:20<00:21, 18.44it/s]
 50%|####9     | 390/781 [00:20<00:21, 18.47it/s]
 50%|#####     | 392/781 [00:20<00:20, 18.67it/s]
 50%|#####     | 394/781 [00:20<00:20, 18.71it/s]
 51%|#####     | 396/781 [00:20<00:20, 18.81it/s]
 51%|#####     | 398/781 [00:20<00:20, 18.93it/s]
 51%|#####1    | 400/781 [00:20<00:20, 18.92it/s]
 51%|#####1    | 402/781 [00:21<00:20, 18.46it/s]
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 52%|#####1    | 406/781 [00:21<00:20, 18.64it/s]
 52%|#####2    | 408/781 [00:21<00:19, 18.91it/s]
 52%|#####2    | 410/781 [00:21<00:19, 19.00it/s]
 53%|#####2    | 412/781 [00:21<00:19, 19.01it/s]
 53%|#####3    | 414/781 [00:21<00:19, 19.05it/s]
 53%|#####3    | 416/781 [00:21<00:19, 19.09it/s]
 54%|#####3    | 418/781 [00:21<00:19, 19.10it/s]
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 54%|#####4    | 422/781 [00:22<00:18, 18.96it/s]
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 55%|#####4    | 426/781 [00:22<00:18, 19.35it/s]
 55%|#####4    | 428/781 [00:22<00:18, 19.35it/s]
 55%|#####5    | 430/781 [00:22<00:18, 19.42it/s]
 55%|#####5    | 432/781 [00:22<00:17, 19.54it/s]
 56%|#####5    | 434/781 [00:22<00:17, 19.60it/s]
 56%|#####5    | 436/781 [00:22<00:17, 19.66it/s]
 56%|#####6    | 438/781 [00:22<00:17, 19.74it/s]
 56%|#####6    | 440/781 [00:23<00:17, 19.69it/s]
 57%|#####6    | 442/781 [00:23<00:17, 19.77it/s]
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 57%|#####7    | 446/781 [00:23<00:17, 19.69it/s]
 57%|#####7    | 448/781 [00:23<00:16, 19.74it/s]
 58%|#####7    | 451/781 [00:23<00:16, 19.63it/s]
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 59%|#####9    | 461/781 [00:24<00:17, 18.71it/s]
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 60%|#####9    | 465/781 [00:24<00:17, 18.40it/s]
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 60%|######    | 469/781 [00:24<00:17, 18.12it/s]
 60%|######    | 471/781 [00:24<00:17, 18.18it/s]
 61%|######    | 473/781 [00:24<00:16, 18.22it/s]
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 61%|######1   | 477/781 [00:24<00:16, 18.19it/s]
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 62%|######1   | 481/781 [00:25<00:16, 18.24it/s]
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 62%|######2   | 487/781 [00:25<00:15, 18.50it/s]
 63%|######2   | 489/781 [00:25<00:15, 18.62it/s]
 63%|######2   | 491/781 [00:25<00:15, 18.85it/s]
 63%|######3   | 493/781 [00:25<00:15, 18.96it/s]
 63%|######3   | 495/781 [00:25<00:15, 18.97it/s]
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 66%|######6   | 517/781 [00:27<00:13, 19.09it/s]
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 67%|######7   | 525/781 [00:27<00:13, 19.00it/s]
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 68%|######7   | 529/781 [00:27<00:13, 18.92it/s]
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 68%|######8   | 533/781 [00:27<00:12, 19.20it/s]
 69%|######8   | 535/781 [00:28<00:12, 19.06it/s]
 69%|######8   | 537/781 [00:28<00:12, 19.19it/s]
 69%|######9   | 539/781 [00:28<00:12, 19.22it/s]
 69%|######9   | 541/781 [00:28<00:12, 19.26it/s]
 70%|######9   | 543/781 [00:28<00:12, 19.16it/s]
 70%|######9   | 545/781 [00:28<00:12, 18.93it/s]
 70%|#######   | 547/781 [00:28<00:12, 19.00it/s]
 70%|#######   | 549/781 [00:28<00:12, 18.87it/s]
 71%|#######   | 551/781 [00:28<00:12, 18.91it/s]
 71%|#######   | 553/781 [00:28<00:12, 18.92it/s]
 71%|#######1  | 555/781 [00:29<00:11, 19.00it/s]
 71%|#######1  | 557/781 [00:29<00:11, 19.10it/s]
 72%|#######1  | 559/781 [00:29<00:11, 19.13it/s]
 72%|#######1  | 561/781 [00:29<00:11, 19.10it/s]
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 72%|#######2  | 565/781 [00:29<00:11, 18.99it/s]
 73%|#######2  | 567/781 [00:29<00:11, 18.99it/s]
 73%|#######2  | 569/781 [00:29<00:11, 18.93it/s]
 73%|#######3  | 571/781 [00:29<00:11, 18.71it/s]
 73%|#######3  | 573/781 [00:30<00:11, 18.20it/s]
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 78%|#######7  | 609/781 [00:31<00:08, 19.28it/s]
 78%|#######8  | 611/781 [00:32<00:08, 19.27it/s]
 78%|#######8  | 613/781 [00:32<00:08, 19.12it/s]
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 80%|#######9  | 621/781 [00:32<00:08, 19.22it/s]
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 80%|########  | 625/781 [00:32<00:08, 19.10it/s]
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100%|##########| 781/781 [00:41<00:00, 19.00it/s]




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 70%|#######   | 110/157 [00:06<00:02, 16.12it/s]
 71%|#######1  | 112/157 [00:07<00:02, 16.12it/s]
 73%|#######2  | 114/157 [00:07<00:02, 16.10it/s]
 74%|#######3  | 116/157 [00:07<00:02, 16.10it/s]
 75%|#######5  | 118/157 [00:07<00:02, 16.10it/s]
 76%|#######6  | 120/157 [00:07<00:02, 16.13it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.15it/s]
 79%|#######8  | 124/157 [00:07<00:02, 16.15it/s]
 80%|########  | 126/157 [00:07<00:01, 16.17it/s]
 82%|########1 | 128/157 [00:08<00:01, 16.07it/s]
 83%|########2 | 130/157 [00:08<00:01, 16.07it/s]
 84%|########4 | 132/157 [00:08<00:01, 16.11it/s]
 85%|########5 | 134/157 [00:08<00:01, 16.12it/s]
 87%|########6 | 136/157 [00:08<00:01, 16.12it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.06it/s]
 89%|########9 | 140/157 [00:08<00:01, 16.05it/s]
 90%|######### | 142/157 [00:08<00:00, 16.01it/s]
 92%|#########1| 144/157 [00:09<00:00, 15.67it/s]
 93%|#########2| 146/157 [00:09<00:00, 15.72it/s]
 94%|#########4| 148/157 [00:09<00:00, 15.66it/s]
 96%|#########5| 150/157 [00:09<00:00, 15.68it/s]
 97%|#########6| 152/157 [00:09<00:00, 15.66it/s]
 98%|#########8| 154/157 [00:09<00:00, 15.70it/s]
 99%|#########9| 156/157 [00:09<00:00, 15.80it/s]
100%|##########| 157/157 [00:09<00:00, 15.87it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:50, 15.57it/s]
  1%|          | 4/781 [00:00<00:46, 16.81it/s]
  1%|          | 6/781 [00:00<00:45, 17.09it/s]
  1%|1         | 8/781 [00:00<00:44, 17.42it/s]
  1%|1         | 10/781 [00:00<00:44, 17.42it/s]
  2%|1         | 12/781 [00:00<00:43, 17.54it/s]
  2%|1         | 14/781 [00:00<00:43, 17.59it/s]
  2%|2         | 16/781 [00:00<00:43, 17.52it/s]
  2%|2         | 18/781 [00:01<00:43, 17.41it/s]
  3%|2         | 20/781 [00:01<00:43, 17.37it/s]
  3%|2         | 22/781 [00:01<00:43, 17.60it/s]
  3%|3         | 24/781 [00:01<00:42, 17.76it/s]
  3%|3         | 26/781 [00:01<00:42, 17.91it/s]
  4%|3         | 28/781 [00:01<00:41, 18.01it/s]
  4%|3         | 30/781 [00:01<00:41, 18.03it/s]
  4%|4         | 32/781 [00:01<00:41, 17.86it/s]
  4%|4         | 34/781 [00:01<00:41, 17.95it/s]
  5%|4         | 36/781 [00:02<00:41, 18.07it/s]
  5%|4         | 38/781 [00:02<00:41, 18.10it/s]
  5%|5         | 40/781 [00:02<00:40, 18.12it/s]
  5%|5         | 42/781 [00:02<00:40, 18.14it/s]
  6%|5         | 44/781 [00:02<00:40, 18.17it/s]
  6%|5         | 46/781 [00:02<00:40, 18.18it/s]
  6%|6         | 48/781 [00:02<00:40, 18.13it/s]
  6%|6         | 50/781 [00:02<00:40, 18.14it/s]
  7%|6         | 52/781 [00:02<00:40, 18.02it/s]
  7%|6         | 54/781 [00:03<00:40, 18.07it/s]
  7%|7         | 56/781 [00:03<00:40, 18.00it/s]
  7%|7         | 58/781 [00:03<00:40, 17.97it/s]
  8%|7         | 60/781 [00:03<00:40, 17.93it/s]
  8%|7         | 62/781 [00:03<00:40, 17.68it/s]
  8%|8         | 64/781 [00:03<00:40, 17.67it/s]
  8%|8         | 66/781 [00:03<00:40, 17.68it/s]
  9%|8         | 68/781 [00:03<00:40, 17.57it/s]
  9%|8         | 70/781 [00:03<00:40, 17.62it/s]
  9%|9         | 72/781 [00:04<00:40, 17.63it/s]
  9%|9         | 74/781 [00:04<00:39, 17.79it/s]
 10%|9         | 76/781 [00:04<00:39, 17.77it/s]
 10%|9         | 78/781 [00:04<00:39, 17.78it/s]
 10%|#         | 80/781 [00:04<00:39, 17.84it/s]
 10%|#         | 82/781 [00:04<00:39, 17.80it/s]
 11%|#         | 84/781 [00:04<00:39, 17.75it/s]
 11%|#1        | 86/781 [00:04<00:38, 17.91it/s]
 11%|#1        | 88/781 [00:04<00:38, 18.03it/s]
 12%|#1        | 90/781 [00:05<00:38, 17.95it/s]
 12%|#1        | 92/781 [00:05<00:38, 17.88it/s]
 12%|#2        | 94/781 [00:05<00:38, 17.92it/s]
 12%|#2        | 96/781 [00:05<00:38, 17.83it/s]
 13%|#2        | 98/781 [00:05<00:38, 17.59it/s]
 13%|#2        | 100/781 [00:05<00:38, 17.77it/s]
 13%|#3        | 102/781 [00:05<00:37, 17.90it/s]
 13%|#3        | 104/781 [00:05<00:37, 18.00it/s]
 14%|#3        | 106/781 [00:05<00:37, 17.94it/s]
 14%|#3        | 108/781 [00:06<00:37, 17.89it/s]
 14%|#4        | 110/781 [00:06<00:37, 17.90it/s]
 14%|#4        | 112/781 [00:06<00:37, 17.78it/s]
 15%|#4        | 114/781 [00:06<00:37, 17.74it/s]
 15%|#4        | 116/781 [00:06<00:37, 17.85it/s]
 15%|#5        | 118/781 [00:06<00:36, 17.94it/s]
 15%|#5        | 120/781 [00:06<00:36, 17.94it/s]
 16%|#5        | 122/781 [00:06<00:36, 17.91it/s]
 16%|#5        | 124/781 [00:06<00:36, 17.89it/s]
 16%|#6        | 126/781 [00:07<00:36, 18.00it/s]
 16%|#6        | 128/781 [00:07<00:36, 18.05it/s]
 17%|#6        | 130/781 [00:07<00:35, 18.10it/s]
 17%|#6        | 132/781 [00:07<00:36, 17.91it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.88it/s]
 17%|#7        | 136/781 [00:07<00:35, 17.95it/s]
 18%|#7        | 138/781 [00:07<00:35, 17.91it/s]
 18%|#7        | 140/781 [00:07<00:35, 17.87it/s]
 18%|#8        | 142/781 [00:07<00:35, 17.96it/s]
 18%|#8        | 144/781 [00:08<00:35, 18.01it/s]
 19%|#8        | 146/781 [00:08<00:35, 18.07it/s]
 19%|#8        | 148/781 [00:08<00:34, 18.16it/s]
 19%|#9        | 150/781 [00:08<00:34, 18.10it/s]
 19%|#9        | 152/781 [00:08<00:34, 17.97it/s]
 20%|#9        | 154/781 [00:08<00:34, 17.93it/s]
 20%|#9        | 156/781 [00:08<00:34, 17.95it/s]
 20%|##        | 158/781 [00:08<00:34, 17.93it/s]
 20%|##        | 160/781 [00:08<00:34, 18.03it/s]
 21%|##        | 162/781 [00:09<00:34, 18.10it/s]
 21%|##        | 164/781 [00:09<00:34, 18.14it/s]
 21%|##1       | 166/781 [00:09<00:34, 18.07it/s]
 22%|##1       | 168/781 [00:09<00:33, 18.03it/s]
 22%|##1       | 170/781 [00:09<00:34, 17.87it/s]
 22%|##2       | 172/781 [00:09<00:34, 17.83it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.94it/s]
 23%|##2       | 176/781 [00:09<00:33, 17.96it/s]
 23%|##2       | 178/781 [00:09<00:33, 17.96it/s]
 23%|##3       | 180/781 [00:10<00:33, 17.87it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.69it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.71it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.86it/s]
 24%|##4       | 188/781 [00:10<00:32, 17.98it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.85it/s]
 25%|##4       | 192/781 [00:10<00:32, 17.90it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.83it/s]
 25%|##5       | 196/781 [00:10<00:33, 17.70it/s]
 25%|##5       | 198/781 [00:11<00:33, 17.63it/s]
 26%|##5       | 200/781 [00:11<00:32, 17.79it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.81it/s]
 26%|##6       | 204/781 [00:11<00:32, 17.88it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.67it/s]
 27%|##6       | 208/781 [00:11<00:32, 17.70it/s]
 27%|##6       | 210/781 [00:11<00:31, 17.89it/s]
 27%|##7       | 212/781 [00:11<00:31, 18.00it/s]
 27%|##7       | 214/781 [00:11<00:31, 18.04it/s]
 28%|##7       | 216/781 [00:12<00:31, 18.11it/s]
 28%|##7       | 218/781 [00:12<00:31, 18.09it/s]
 28%|##8       | 220/781 [00:12<00:30, 18.10it/s]
 28%|##8       | 222/781 [00:12<00:31, 18.02it/s]
 29%|##8       | 224/781 [00:12<00:30, 17.99it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.87it/s]
 29%|##9       | 228/781 [00:12<00:31, 17.79it/s]
 29%|##9       | 230/781 [00:12<00:31, 17.77it/s]
 30%|##9       | 232/781 [00:12<00:31, 17.53it/s]
 30%|##9       | 234/781 [00:13<00:31, 17.60it/s]
 30%|###       | 236/781 [00:13<00:30, 17.69it/s]
 30%|###       | 238/781 [00:13<00:30, 17.82it/s]
 31%|###       | 240/781 [00:13<00:30, 17.66it/s]
 31%|###       | 242/781 [00:13<00:30, 17.74it/s]
 31%|###1      | 244/781 [00:13<00:30, 17.75it/s]
 31%|###1      | 246/781 [00:13<00:30, 17.62it/s]
 32%|###1      | 248/781 [00:13<00:30, 17.76it/s]
 32%|###2      | 250/781 [00:14<00:29, 17.85it/s]
 32%|###2      | 252/781 [00:14<00:29, 17.83it/s]
 33%|###2      | 254/781 [00:14<00:29, 17.81it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.86it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.97it/s]
 33%|###3      | 260/781 [00:14<00:28, 17.97it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.04it/s]
 34%|###3      | 264/781 [00:14<00:28, 18.08it/s]
 34%|###4      | 266/781 [00:14<00:28, 18.08it/s]
 34%|###4      | 268/781 [00:15<00:28, 18.11it/s]
 35%|###4      | 270/781 [00:15<00:28, 17.87it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.82it/s]
 35%|###5      | 274/781 [00:15<00:28, 17.75it/s]
 35%|###5      | 276/781 [00:15<00:28, 18.00it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.92it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.88it/s]
 36%|###6      | 282/781 [00:15<00:28, 17.63it/s]
 36%|###6      | 284/781 [00:15<00:27, 17.81it/s]
 37%|###6      | 286/781 [00:16<00:27, 17.91it/s]
 37%|###6      | 288/781 [00:16<00:27, 18.00it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.90it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.88it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.84it/s]
 38%|###7      | 296/781 [00:16<00:27, 17.79it/s]
 38%|###8      | 298/781 [00:16<00:27, 17.71it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.66it/s]
 39%|###8      | 302/781 [00:16<00:26, 17.78it/s]
 39%|###8      | 304/781 [00:17<00:26, 17.89it/s]
 39%|###9      | 306/781 [00:17<00:26, 17.99it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.54it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.64it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.69it/s]
 40%|####      | 314/781 [00:17<00:26, 17.82it/s]
 40%|####      | 316/781 [00:17<00:26, 17.86it/s]
 41%|####      | 318/781 [00:17<00:25, 17.94it/s]
 41%|####      | 320/781 [00:17<00:26, 17.69it/s]
 41%|####1     | 322/781 [00:18<00:25, 17.71it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.87it/s]
 42%|####1     | 326/781 [00:18<00:25, 17.88it/s]
 42%|####1     | 328/781 [00:18<00:25, 17.89it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.54it/s]
 43%|####2     | 332/781 [00:18<00:25, 17.65it/s]
 43%|####2     | 334/781 [00:18<00:25, 17.74it/s]
 43%|####3     | 336/781 [00:18<00:25, 17.69it/s]
 43%|####3     | 338/781 [00:18<00:25, 17.68it/s]
 44%|####3     | 340/781 [00:19<00:25, 17.56it/s]
 44%|####3     | 342/781 [00:19<00:24, 17.59it/s]
 44%|####4     | 344/781 [00:19<00:25, 17.32it/s]
 44%|####4     | 346/781 [00:19<00:24, 17.53it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.60it/s]
 45%|####4     | 350/781 [00:19<00:24, 17.73it/s]
 45%|####5     | 352/781 [00:19<00:23, 17.89it/s]
 45%|####5     | 354/781 [00:19<00:23, 17.96it/s]
 46%|####5     | 356/781 [00:19<00:23, 18.06it/s]
 46%|####5     | 358/781 [00:20<00:23, 18.13it/s]
 46%|####6     | 360/781 [00:20<00:23, 17.98it/s]
 46%|####6     | 362/781 [00:20<00:23, 17.96it/s]
 47%|####6     | 364/781 [00:20<00:23, 17.80it/s]
 47%|####6     | 366/781 [00:20<00:23, 17.79it/s]
 47%|####7     | 368/781 [00:20<00:23, 17.76it/s]
 47%|####7     | 370/781 [00:20<00:23, 17.76it/s]
 48%|####7     | 372/781 [00:20<00:22, 17.86it/s]
 48%|####7     | 374/781 [00:20<00:22, 17.82it/s]
 48%|####8     | 376/781 [00:21<00:22, 17.90it/s]
 48%|####8     | 378/781 [00:21<00:22, 17.75it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.80it/s]
 49%|####8     | 382/781 [00:21<00:22, 17.64it/s]
 49%|####9     | 384/781 [00:21<00:22, 17.60it/s]
 49%|####9     | 386/781 [00:21<00:22, 17.76it/s]
 50%|####9     | 388/781 [00:21<00:22, 17.71it/s]
 50%|####9     | 390/781 [00:21<00:22, 17.72it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.85it/s]
 50%|#####     | 394/781 [00:22<00:21, 17.87it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.98it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.77it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.83it/s]
 51%|#####1    | 402/781 [00:22<00:21, 17.97it/s]
 52%|#####1    | 404/781 [00:22<00:20, 18.04it/s]
 52%|#####1    | 406/781 [00:22<00:20, 18.05it/s]
 52%|#####2    | 408/781 [00:22<00:20, 18.03it/s]
 52%|#####2    | 410/781 [00:22<00:20, 17.90it/s]
 53%|#####2    | 412/781 [00:23<00:20, 17.86it/s]
 53%|#####3    | 414/781 [00:23<00:20, 17.75it/s]
 53%|#####3    | 416/781 [00:23<00:20, 17.94it/s]
 54%|#####3    | 418/781 [00:23<00:20, 17.89it/s]
 54%|#####3    | 420/781 [00:23<00:20, 17.86it/s]
 54%|#####4    | 422/781 [00:23<00:20, 17.83it/s]
 54%|#####4    | 424/781 [00:23<00:19, 17.86it/s]
 55%|#####4    | 426/781 [00:23<00:19, 17.80it/s]
 55%|#####4    | 428/781 [00:23<00:19, 17.78it/s]
 55%|#####5    | 430/781 [00:24<00:19, 17.73it/s]
 55%|#####5    | 432/781 [00:24<00:19, 17.80it/s]
 56%|#####5    | 434/781 [00:24<00:19, 17.94it/s]
 56%|#####5    | 436/781 [00:24<00:19, 18.01it/s]
 56%|#####6    | 438/781 [00:24<00:19, 18.04it/s]
 56%|#####6    | 440/781 [00:24<00:18, 17.96it/s]
 57%|#####6    | 442/781 [00:24<00:18, 18.04it/s]
 57%|#####6    | 444/781 [00:24<00:18, 18.07it/s]
 57%|#####7    | 446/781 [00:24<00:18, 17.99it/s]
 57%|#####7    | 448/781 [00:25<00:18, 18.06it/s]
 58%|#####7    | 450/781 [00:25<00:18, 18.07it/s]
 58%|#####7    | 452/781 [00:25<00:18, 18.10it/s]
 58%|#####8    | 454/781 [00:25<00:18, 18.07it/s]
 58%|#####8    | 456/781 [00:25<00:17, 18.09it/s]
 59%|#####8    | 458/781 [00:25<00:17, 18.08it/s]
 59%|#####8    | 460/781 [00:25<00:17, 18.12it/s]
 59%|#####9    | 462/781 [00:25<00:17, 18.14it/s]
 59%|#####9    | 464/781 [00:25<00:17, 18.17it/s]
 60%|#####9    | 466/781 [00:26<00:17, 18.03it/s]
 60%|#####9    | 468/781 [00:26<00:17, 18.02it/s]
 60%|######    | 470/781 [00:26<00:17, 18.07it/s]
 60%|######    | 472/781 [00:26<00:17, 18.04it/s]
 61%|######    | 474/781 [00:26<00:17, 18.05it/s]
 61%|######    | 476/781 [00:26<00:16, 18.06it/s]
 61%|######1   | 478/781 [00:26<00:16, 17.97it/s]
 61%|######1   | 480/781 [00:26<00:16, 17.88it/s]
 62%|######1   | 482/781 [00:26<00:16, 17.87it/s]
 62%|######1   | 484/781 [00:27<00:16, 18.00it/s]
 62%|######2   | 486/781 [00:27<00:16, 18.09it/s]
 62%|######2   | 488/781 [00:27<00:16, 18.01it/s]
 63%|######2   | 490/781 [00:27<00:16, 18.09it/s]
 63%|######2   | 492/781 [00:27<00:16, 17.95it/s]
 63%|######3   | 494/781 [00:27<00:16, 17.85it/s]
 64%|######3   | 496/781 [00:27<00:16, 17.73it/s]
 64%|######3   | 498/781 [00:27<00:15, 17.84it/s]
 64%|######4   | 500/781 [00:27<00:15, 17.92it/s]
 64%|######4   | 502/781 [00:28<00:15, 17.85it/s]
 65%|######4   | 504/781 [00:28<00:15, 17.78it/s]
 65%|######4   | 506/781 [00:28<00:15, 17.90it/s]
 65%|######5   | 508/781 [00:28<00:15, 17.81it/s]
 65%|######5   | 510/781 [00:28<00:15, 17.75it/s]
 66%|######5   | 512/781 [00:28<00:15, 17.89it/s]
 66%|######5   | 514/781 [00:28<00:15, 17.64it/s]
 66%|######6   | 516/781 [00:28<00:14, 17.74it/s]
 66%|######6   | 518/781 [00:29<00:14, 17.91it/s]
 67%|######6   | 520/781 [00:29<00:14, 17.92it/s]
 67%|######6   | 522/781 [00:29<00:14, 17.83it/s]
 67%|######7   | 524/781 [00:29<00:14, 17.77it/s]
 67%|######7   | 526/781 [00:29<00:14, 17.91it/s]
 68%|######7   | 528/781 [00:29<00:14, 17.99it/s]
 68%|######7   | 530/781 [00:29<00:13, 18.05it/s]
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=======================================================   RESTART [11-16 10:31:41]   =======================================================







=======================================================   RESTART [11-16 10:31:41]   =======================================================







=======================================================   RESTART [11-16 10:31:41]   =======================================================







=======================================================   RESTART [11-16 10:31:41]   =======================================================
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:

model.safetensors:   0%|          | 0.00/346M [00:00<?, ?B/s]
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model.safetensors:  70%|######9   | 241M/346M [00:01<00:00, 237MB/s]
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model.safetensors:  88%|########7 | 304M/346M [00:01<00:00, 231MB/s]
model.safetensors:  97%|#########6| 336M/346M [00:01<00:00, 230MB/s]
model.safetensors: 100%|##########| 346M/346M [00:01<00:00, 220MB/s]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
wandb: Currently logged in as: kaiqiu. Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.18.3
wandb: Run data is saved locally in /home/user/VAR/wandb/run-20241115_183329-eg1yp4d7
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run pleasant-dew-410
wandb:  View project at https://wandb.ai/kaiqiu/VAR
wandb:  View run at https://wandb.ai/kaiqiu/VAR/runs/eg1yp4d7
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_3 0.0291 ms 100.0%
  triton_mm_2 0.0299 ms 97.3%
  triton_mm_1 0.0300 ms 96.9%
  triton_mm_4 0.0305 ms 95.3%
  triton_mm_12 0.0306 ms 94.9%
  triton_mm_7 0.0308 ms 94.5%
  triton_mm_11 0.0311 ms 93.3%
  triton_mm_9 0.0312 ms 93.2%
  triton_mm_10 0.0312 ms 93.0%
  triton_mm_8 0.0313 ms 92.8%
SingleProcess AUTOTUNE benchmarking takes 1.9934 seconds and 0.0170 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_25 0.0247 ms 100.0%
  triton_mm_33 0.0247 ms 99.9%
  triton_mm_21 0.0254 ms 97.1%
  triton_mm_24 0.0257 ms 96.0%
  triton_mm_29 0.0259 ms 95.5%
  triton_mm_28 0.0272 ms 90.9%
  triton_mm_18 0.0272 ms 90.8%
  triton_mm_20 0.0275 ms 90.0%
  triton_mm_19 0.0281 ms 87.9%
  bias_addmm 0.0283 ms 87.3%
SingleProcess AUTOTUNE benchmarking takes 2.1110 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2160 ms 100.0%
  triton_mm_51 0.2202 ms 98.1%
  bias_addmm 0.2526 ms 85.5%
  triton_mm_52 0.2538 ms 85.1%
  triton_mm_45 0.2581 ms 83.7%
  triton_mm_47 0.2675 ms 80.8%
  triton_mm_43 0.2718 ms 79.5%
  addmm 0.2729 ms 79.2%
  triton_mm_44 0.2997 ms 72.1%
  triton_mm_48 0.3078 ms 70.2%
SingleProcess AUTOTUNE benchmarking takes 2.6068 seconds and 0.0105 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0895 ms 100.0%
  triton_mm_69 0.0908 ms 98.6%
  bias_addmm 0.0971 ms 92.2%
  triton_mm_66 0.0979 ms 91.4%
  triton_mm_64 0.0981 ms 91.2%
  triton_mm_71 0.1000 ms 89.5%
  triton_mm_62 0.1017 ms 88.0%
  addmm 0.1095 ms 81.8%
  triton_mm_63 0.1120 ms 79.9%
  triton_mm_67 0.1124 ms 79.6%
SingleProcess AUTOTUNE benchmarking takes 2.4654 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2726 ms 100.0%
  triton_mm_88 0.2874 ms 94.8%
  triton_mm_89 0.2875 ms 94.8%
  triton_mm_90 0.3291 ms 82.8%
  triton_mm_83 0.3332 ms 81.8%
  addmm 0.3557 ms 76.6%
  triton_mm_81 0.3561 ms 76.5%
  triton_mm_85 0.3572 ms 76.3%
  triton_mm_82 0.3945 ms 69.1%
  triton_mm_86 0.4060 ms 67.1%
SingleProcess AUTOTUNE benchmarking takes 2.6352 seconds and 0.0092 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2820 ms 100.0%
  triton_mm_108 0.2977 ms 94.7%
  triton_mm_107 0.3053 ms 92.4%
  addmm 0.3150 ms 89.5%
  triton_mm_109 0.3161 ms 89.2%
  triton_mm_104 0.3516 ms 80.2%
  triton_mm_102 0.3541 ms 79.6%
  triton_mm_100 0.3669 ms 76.9%
  triton_mm_103 0.3673 ms 76.8%
  triton_mm_105 0.4005 ms 70.4%
SingleProcess AUTOTUNE benchmarking takes 2.6329 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0150 ms 100.0%
  triton_mm_1606 0.0155 ms 96.8%
  mm 0.0156 ms 96.7%
  triton_mm_1610 0.0159 ms 94.6%
  triton_mm_1614 0.0171 ms 87.9%
  triton_mm_1601 0.0174 ms 86.2%
  triton_mm_1600 0.0179 ms 84.2%
  triton_mm_1599 0.0180 ms 83.6%
  triton_mm_1605 0.0182 ms 82.5%
  triton_mm_1609 0.0197 ms 76.2%
SingleProcess AUTOTUNE benchmarking takes 7.2797 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1632 0.5387 ms 100.0%
  bias_addmm 0.5436 ms 99.1%
  triton_mm_1631 0.5471 ms 98.5%
  triton_mm_1633 0.6131 ms 87.9%
  triton_mm_1626 0.6448 ms 83.5%
  addmm 0.6784 ms 79.4%
  triton_mm_1628 0.6820 ms 79.0%
  triton_mm_1624 0.6966 ms 77.3%
  triton_mm_1629 0.7652 ms 70.4%
  triton_mm_1625 0.7682 ms 70.1%
SingleProcess AUTOTUNE benchmarking takes 11.3560 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.4897 ms 100.0%
  triton_mm_1669 0.5301 ms 92.4%
  triton_mm_1670 0.5549 ms 88.2%
  triton_mm_1671 0.5798 ms 84.4%
  triton_mm_1664 0.6531 ms 75.0%
  triton_mm_1662 0.6753 ms 72.5%
  triton_mm_1666 0.6825 ms 71.7%
  triton_mm_1667 0.7045 ms 69.5%
  triton_mm_1665 0.7121 ms 68.8%
  triton_mm_1663 0.7252 ms 67.5%
SingleProcess AUTOTUNE benchmarking takes 2.5712 seconds and 0.0374 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2760 ms 100.0%
  triton_mm_1743 0.2835 ms 97.4%
  triton_mm_1742 0.2852 ms 96.8%
  triton_mm_1741 0.2876 ms 96.0%
  triton_mm_1736 0.3394 ms 81.3%
  triton_mm_1734 0.3423 ms 80.6%
  triton_mm_1738 0.3584 ms 77.0%
  triton_mm_1737 0.3693 ms 74.7%
  triton_mm_1735 0.3902 ms 70.7%
  triton_mm_1739 0.3906 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.5069 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1696 0.0118 ms 100.0%
  triton_mm_1700 0.0118 ms 99.7%
  triton_mm_1704 0.0125 ms 94.4%
  triton_mm_1693 0.0127 ms 92.9%
  triton_mm_1695 0.0127 ms 92.9%
  triton_mm_1697 0.0127 ms 92.7%
  triton_mm_1698 0.0128 ms 92.5%
  triton_mm_1702 0.0128 ms 92.5%
  triton_mm_1699 0.0128 ms 92.2%
  triton_mm_1694 0.0128 ms 92.0%
SingleProcess AUTOTUNE benchmarking takes 1.9993 seconds and 0.0007 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0168 ms 100.0%
  triton_mm_1680 0.0171 ms 98.1%
  mm 0.0190 ms 88.1%
  triton_mm_1684 0.0212 ms 79.3%
  triton_mm_1675 0.0221 ms 75.8%
  triton_mm_1674 0.0234 ms 71.6%
  triton_mm_1688 0.0238 ms 70.5%
  triton_mm_1679 0.0249 ms 67.3%
  triton_mm_1673 0.0261 ms 64.1%
  triton_mm_1683 0.0267 ms 62.8%
SingleProcess AUTOTUNE benchmarking takes 2.0385 seconds and 0.0008 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5184 ms 100.0%
  triton_mm_1650 0.5424 ms 95.6%
  triton_mm_1651 0.5510 ms 94.1%
  triton_mm_1652 0.5640 ms 91.9%
  triton_mm_1647 0.6388 ms 81.2%
  triton_mm_1643 0.6543 ms 79.2%
  triton_mm_1645 0.6591 ms 78.6%
  triton_mm_1646 0.6737 ms 76.9%
  triton_mm_1644 0.7007 ms 74.0%
  triton_mm_1648 0.7038 ms 73.6%
SingleProcess AUTOTUNE benchmarking takes 9.2991 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1723 0.2668 ms 100.0%
  mm 0.2683 ms 99.5%
  triton_mm_1722 0.2686 ms 99.3%
  triton_mm_1724 0.3082 ms 86.6%
  triton_mm_1715 0.3301 ms 80.8%
  triton_mm_1717 0.3346 ms 79.7%
  triton_mm_1719 0.3388 ms 78.8%
  triton_mm_1716 0.3596 ms 74.2%
  triton_mm_1720 0.3768 ms 70.8%
  triton_mm_1718 0.4183 ms 63.8%
SingleProcess AUTOTUNE benchmarking takes 2.4959 seconds and 0.0008 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2139 ms 100.0%
  triton_mm_1837 0.2150 ms 99.5%
  triton_mm_1836 0.2197 ms 97.4%
  triton_mm_1838 0.2338 ms 91.5%
  triton_mm_1833 0.2484 ms 86.1%
  triton_mm_1829 0.2538 ms 84.3%
  triton_mm_1831 0.2580 ms 82.9%
  triton_mm_1830 0.2815 ms 76.0%
  triton_mm_1832 0.2851 ms 75.0%
  triton_mm_1834 0.2893 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.4778 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2781 ms 100.0%
  triton_mm_1779 0.2796 ms 99.5%
  triton_mm_1780 0.2830 ms 98.2%
  triton_mm_1781 0.2897 ms 96.0%
  triton_mm_1776 0.3337 ms 83.3%
  triton_mm_1772 0.3456 ms 80.5%
  triton_mm_1774 0.3461 ms 80.3%
  triton_mm_1775 0.3731 ms 74.5%
  triton_mm_1777 0.3767 ms 73.8%
  triton_mm_1773 0.3881 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.5136 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2156 ms 100.0%
  triton_mm_1855 0.2707 ms 79.6%
  triton_mm_1850 0.2740 ms 78.7%
  triton_mm_1856 0.2764 ms 78.0%
  triton_mm_1857 0.2792 ms 77.2%
  triton_mm_1848 0.2812 ms 76.7%
  triton_mm_1852 0.2924 ms 73.7%
  triton_mm_1851 0.3052 ms 70.6%
  triton_mm_1853 0.3132 ms 68.8%
  triton_mm_1849 0.3235 ms 66.6%
SingleProcess AUTOTUNE benchmarking takes 2.4826 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0972 ms 100.0%
  triton_mm_1819 0.0994 ms 97.8%
  triton_mm_1812 0.1050 ms 92.5%
  triton_mm_1818 0.1085 ms 89.5%
  triton_mm_1809 0.1176 ms 82.7%
  triton_mm_1810 0.1196 ms 81.3%
  triton_mm_1814 0.1208 ms 80.5%
  triton_mm_1817 0.1229 ms 79.1%
  triton_mm_1813 0.1270 ms 76.5%
  triton_mm_1815 0.1301 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.3772 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2866 ms 100.0%
  triton_mm_1760 0.2906 ms 98.6%
  triton_mm_1761 0.2993 ms 95.8%
  triton_mm_1762 0.3068 ms 93.4%
  triton_mm_1757 0.3349 ms 85.6%
  triton_mm_1755 0.3403 ms 84.2%
  triton_mm_1753 0.3426 ms 83.7%
  triton_mm_1756 0.3608 ms 79.4%
  triton_mm_1754 0.3766 ms 76.1%
  triton_mm_1758 0.3830 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 2.5101 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0835 ms 100.0%
  mm 0.0841 ms 99.3%
  triton_mm_1798 0.0856 ms 97.5%
  triton_mm_1795 0.0923 ms 90.5%
  triton_mm_1800 0.0943 ms 88.6%
  triton_mm_1791 0.0948 ms 88.1%
  triton_mm_1793 0.0959 ms 87.1%
  triton_mm_1792 0.1026 ms 81.4%
  triton_mm_1796 0.1050 ms 79.5%
  triton_mm_1794 0.1242 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 2.3643 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2660 ms 100.0%
  triton_mm_1908 0.2689 ms 98.9%
  triton_mm_1909 0.2716 ms 97.9%
  triton_mm_1910 0.3105 ms 85.7%
  triton_mm_1901 0.3314 ms 80.3%
  triton_mm_1903 0.3334 ms 79.8%
  triton_mm_1905 0.3386 ms 78.5%
  triton_mm_1902 0.3511 ms 75.7%
  triton_mm_1906 0.3771 ms 70.5%
  triton_mm_1904 0.4186 ms 63.5%
SingleProcess AUTOTUNE benchmarking takes 2.4979 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2869 ms 100.0%
  triton_mm_1946 0.2915 ms 98.5%
  triton_mm_1947 0.2987 ms 96.1%
  triton_mm_1948 0.3103 ms 92.5%
  triton_mm_1943 0.3370 ms 85.1%
  triton_mm_1941 0.3393 ms 84.6%
  triton_mm_1939 0.3435 ms 83.5%
  triton_mm_1942 0.3612 ms 79.4%
  triton_mm_1940 0.3770 ms 76.1%
  triton_mm_1944 0.3843 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5093 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1881 0.0183 ms 100.0%
  triton_mm_1888 0.0185 ms 99.0%
  triton_mm_1883 0.0190 ms 96.1%
  triton_mm_1887 0.0192 ms 95.3%
  triton_mm_1882 0.0193 ms 94.7%
  triton_mm_1880 0.0196 ms 93.2%
  triton_mm_1885 0.0198 ms 92.6%
  triton_mm_1886 0.0198 ms 92.3%
  triton_mm_1890 0.0198 ms 92.3%
  triton_mm_1884 0.0199 ms 92.0%
SingleProcess AUTOTUNE benchmarking takes 5.4545 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2742 ms 100.0%
  triton_mm_1928 0.2844 ms 96.4%
  triton_mm_1927 0.2872 ms 95.5%
  triton_mm_1929 0.2903 ms 94.4%
  triton_mm_1922 0.3412 ms 80.4%
  triton_mm_1920 0.3446 ms 79.6%
  triton_mm_1924 0.3508 ms 78.2%
  triton_mm_1923 0.3692 ms 74.3%
  triton_mm_1925 0.3877 ms 70.7%
  triton_mm_1921 0.3930 ms 69.8%
SingleProcess AUTOTUNE benchmarking takes 2.5135 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2770 ms 100.0%
  triton_mm_1965 0.2812 ms 98.5%
  triton_mm_1966 0.2870 ms 96.5%
  triton_mm_1967 0.2890 ms 95.8%
  triton_mm_1962 0.3339 ms 82.9%
  triton_mm_1958 0.3353 ms 82.6%
  triton_mm_1960 0.3471 ms 79.8%
  triton_mm_1961 0.3743 ms 74.0%
  triton_mm_1963 0.3759 ms 73.7%
  triton_mm_1959 0.3896 ms 71.1%
SingleProcess AUTOTUNE benchmarking takes 2.5104 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0285 ms 100.0%
  mm 0.0292 ms 97.9%
  triton_mm_1866 0.0310 ms 92.1%
  triton_mm_1870 0.0408 ms 70.0%
  triton_mm_1861 0.0511 ms 55.8%
  triton_mm_1874 0.0516 ms 55.3%
  triton_mm_1860 0.0561 ms 50.9%
  triton_mm_1865 0.0595 ms 48.0%
  triton_mm_1869 0.0630 ms 45.3%
  triton_mm_1859 0.0654 ms 43.7%
SingleProcess AUTOTUNE benchmarking takes 6.4618 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2150 ms 100.0%
  triton_mm_2041 0.2702 ms 79.6%
  triton_mm_2036 0.2721 ms 79.0%
  triton_mm_2042 0.2764 ms 77.8%
  triton_mm_2034 0.2781 ms 77.3%
  triton_mm_2043 0.2790 ms 77.1%
  triton_mm_2038 0.2897 ms 74.2%
  triton_mm_2037 0.3027 ms 71.1%
  triton_mm_2039 0.3134 ms 68.6%
  triton_mm_2035 0.3205 ms 67.1%
SingleProcess AUTOTUNE benchmarking takes 2.4833 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0968 ms 100.0%
  triton_mm_2005 0.0990 ms 97.7%
  triton_mm_1998 0.1044 ms 92.6%
  triton_mm_2004 0.1085 ms 89.2%
  triton_mm_1995 0.1183 ms 81.8%
  triton_mm_1996 0.1207 ms 80.2%
  triton_mm_2000 0.1208 ms 80.1%
  triton_mm_2003 0.1239 ms 78.1%
  triton_mm_1999 0.1272 ms 76.0%
  triton_mm_2001 0.1309 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.3859 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0833 ms 100.0%
  triton_mm_1985 0.0842 ms 99.0%
  triton_mm_1984 0.0849 ms 98.1%
  triton_mm_1981 0.0924 ms 90.1%
  triton_mm_1977 0.0948 ms 87.9%
  triton_mm_1986 0.0950 ms 87.7%
  triton_mm_1979 0.0957 ms 87.1%
  triton_mm_1978 0.1019 ms 81.8%
  triton_mm_1982 0.1059 ms 78.7%
  triton_mm_1980 0.1247 ms 66.8%
SingleProcess AUTOTUNE benchmarking takes 2.3731 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2134 ms 100.0%
  triton_mm_2023 0.2151 ms 99.2%
  triton_mm_2022 0.2201 ms 97.0%
  triton_mm_2024 0.2339 ms 91.2%
  triton_mm_2019 0.2476 ms 86.2%
  triton_mm_2017 0.2556 ms 83.5%
  triton_mm_2015 0.2595 ms 82.2%
  triton_mm_2018 0.2827 ms 75.5%
  triton_mm_2016 0.2827 ms 75.5%
  triton_mm_2020 0.2844 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.4749 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2643 ms 100.0%
  triton_mm_2094 0.2704 ms 97.7%
  triton_mm_2095 0.2716 ms 97.3%
  triton_mm_2096 0.3096 ms 85.4%
  triton_mm_2087 0.3312 ms 79.8%
  triton_mm_2089 0.3358 ms 78.7%
  triton_mm_2091 0.3387 ms 78.0%
  triton_mm_2088 0.3519 ms 75.1%
  triton_mm_2092 0.3774 ms 70.0%
  triton_mm_2090 0.4194 ms 63.0%
SingleProcess AUTOTUNE benchmarking takes 2.5077 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2867 ms 100.0%
  triton_mm_2132 0.2905 ms 98.7%
  triton_mm_2133 0.2998 ms 95.6%
  triton_mm_2134 0.3082 ms 93.0%
  triton_mm_2129 0.3384 ms 84.7%
  triton_mm_2127 0.3386 ms 84.7%
  triton_mm_2125 0.3433 ms 83.5%
  triton_mm_2128 0.3613 ms 79.3%
  triton_mm_2126 0.3773 ms 76.0%
  triton_mm_2130 0.3820 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5184 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2067 0.0183 ms 100.0%
  triton_mm_2069 0.0183 ms 99.8%
  triton_mm_2071 0.0189 ms 96.6%
  triton_mm_2072 0.0190 ms 96.1%
  triton_mm_2070 0.0191 ms 95.8%
  triton_mm_2073 0.0192 ms 95.2%
  triton_mm_2068 0.0194 ms 94.4%
  triton_mm_2074 0.0195 ms 93.9%
  triton_mm_2077 0.0205 ms 89.3%
  triton_mm_2066 0.0205 ms 89.2%
SingleProcess AUTOTUNE benchmarking takes 2.0206 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0291 ms 100.0%
  triton_mm_2048 0.0292 ms 99.6%
  triton_mm_2052 0.0310 ms 93.7%
  triton_mm_2056 0.0399 ms 72.8%
  triton_mm_2060 0.0507 ms 57.4%
  triton_mm_2047 0.0519 ms 56.0%
  triton_mm_2046 0.0553 ms 52.6%
  triton_mm_2051 0.0595 ms 48.9%
  triton_mm_2055 0.0631 ms 46.1%
  triton_mm_2045 0.0654 ms 44.5%
SingleProcess AUTOTUNE benchmarking takes 2.0373 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2145 ms 100.0%
  triton_mm_2227 0.2708 ms 79.2%
  triton_mm_2222 0.2732 ms 78.5%
  triton_mm_2228 0.2770 ms 77.4%
  triton_mm_2229 0.2800 ms 76.6%
  triton_mm_2220 0.2810 ms 76.3%
  triton_mm_2224 0.2912 ms 73.6%
  triton_mm_2223 0.3055 ms 70.2%
  triton_mm_2225 0.3165 ms 67.8%
  triton_mm_2221 0.3205 ms 66.9%
SingleProcess AUTOTUNE benchmarking takes 2.4833 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0974 ms 100.0%
  triton_mm_2191 0.0983 ms 99.1%
  triton_mm_2184 0.1052 ms 92.7%
  triton_mm_2190 0.1090 ms 89.4%
  triton_mm_2181 0.1174 ms 83.0%
  triton_mm_2182 0.1200 ms 81.2%
  triton_mm_2186 0.1215 ms 80.2%
  triton_mm_2189 0.1238 ms 78.7%
  triton_mm_2185 0.1273 ms 76.5%
  triton_mm_2187 0.1301 ms 74.9%
SingleProcess AUTOTUNE benchmarking takes 2.3685 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2665 ms 100.0%
  triton_mm_2281 0.2687 ms 99.2%
  triton_mm_2280 0.2692 ms 99.0%
  triton_mm_2282 0.3082 ms 86.5%
  triton_mm_2273 0.3326 ms 80.1%
  triton_mm_2275 0.3364 ms 79.2%
  triton_mm_2277 0.3387 ms 78.7%
  triton_mm_2274 0.3530 ms 75.5%
  triton_mm_2278 0.3769 ms 70.7%
  triton_mm_2276 0.4188 ms 63.6%
SingleProcess AUTOTUNE benchmarking takes 2.5041 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2868 ms 100.0%
  triton_mm_2318 0.2922 ms 98.2%
  triton_mm_2319 0.3001 ms 95.6%
  triton_mm_2320 0.3091 ms 92.8%
  triton_mm_2315 0.3376 ms 85.0%
  triton_mm_2313 0.3426 ms 83.7%
  triton_mm_2311 0.3473 ms 82.6%
  triton_mm_2314 0.3607 ms 79.5%
  triton_mm_2312 0.3774 ms 76.0%
  triton_mm_2316 0.3865 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.5103 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2253 0.0183 ms 100.0%
  triton_mm_2255 0.0183 ms 100.0%
  triton_mm_2257 0.0190 ms 96.5%
  triton_mm_2259 0.0192 ms 95.2%
  triton_mm_2254 0.0195 ms 93.9%
  triton_mm_2260 0.0196 ms 93.5%
  triton_mm_2256 0.0199 ms 92.1%
  triton_mm_2258 0.0199 ms 91.9%
  triton_mm_2252 0.0204 ms 89.8%
  triton_mm_2263 0.0204 ms 89.7%
SingleProcess AUTOTUNE benchmarking takes 2.0030 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2234 0.0286 ms 100.0%
  mm 0.0290 ms 98.4%
  triton_mm_2238 0.0310 ms 92.0%
  triton_mm_2242 0.0407 ms 70.1%
  triton_mm_2246 0.0508 ms 56.2%
  triton_mm_2233 0.0518 ms 55.1%
  triton_mm_2232 0.0552 ms 51.7%
  triton_mm_2237 0.0594 ms 48.1%
  triton_mm_2241 0.0629 ms 45.4%
  triton_mm_2231 0.0647 ms 44.1%
SingleProcess AUTOTUNE benchmarking takes 2.0338 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0977 ms 100.0%
  triton_mm_2377 0.0991 ms 98.6%
  triton_mm_2370 0.1044 ms 93.6%
  triton_mm_2376 0.1086 ms 90.0%
  triton_mm_2367 0.1181 ms 82.7%
  triton_mm_2368 0.1204 ms 81.2%
  triton_mm_2372 0.1211 ms 80.7%
  triton_mm_2375 0.1241 ms 78.8%
  triton_mm_2371 0.1265 ms 77.2%
  triton_mm_2373 0.1310 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.3717 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2647 ms 100.0%
  triton_mm_2466 0.2680 ms 98.8%
  triton_mm_2467 0.2695 ms 98.2%
  triton_mm_2468 0.3095 ms 85.5%
  triton_mm_2459 0.3319 ms 79.7%
  triton_mm_2461 0.3387 ms 78.1%
  triton_mm_2463 0.3417 ms 77.5%
  triton_mm_2460 0.3550 ms 74.6%
  triton_mm_2464 0.3765 ms 70.3%
  triton_mm_2462 0.4186 ms 63.2%
SingleProcess AUTOTUNE benchmarking takes 2.5048 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2874 ms 100.0%
  triton_mm_2504 0.2912 ms 98.7%
  triton_mm_2505 0.2988 ms 96.2%
  triton_mm_2506 0.3093 ms 92.9%
  triton_mm_2501 0.3386 ms 84.9%
  triton_mm_2499 0.3397 ms 84.6%
  triton_mm_2497 0.3438 ms 83.6%
  triton_mm_2500 0.3612 ms 79.6%
  triton_mm_2498 0.3773 ms 76.2%
  triton_mm_2502 0.3821 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5083 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2441 0.0183 ms 100.0%
  triton_mm_2440 0.0185 ms 98.8%
  triton_mm_2443 0.0189 ms 96.6%
  triton_mm_2439 0.0190 ms 96.1%
  triton_mm_2444 0.0191 ms 95.8%
  triton_mm_2442 0.0191 ms 95.7%
  triton_mm_2445 0.0192 ms 95.2%
  triton_mm_2446 0.0195 ms 94.1%
  triton_mm_2438 0.0197 ms 93.0%
  triton_mm_2448 0.0199 ms 92.1%
SingleProcess AUTOTUNE benchmarking takes 2.0122 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2420 0.0285 ms 100.0%
  mm 0.0291 ms 97.9%
  triton_mm_2424 0.0310 ms 91.8%
  triton_mm_2428 0.0411 ms 69.4%
  triton_mm_2432 0.0508 ms 56.1%
  triton_mm_2419 0.0511 ms 55.7%
  triton_mm_2418 0.0553 ms 51.5%
  triton_mm_2423 0.0594 ms 47.9%
  triton_mm_2427 0.0630 ms 45.2%
  triton_mm_2417 0.0649 ms 43.9%
SingleProcess AUTOTUNE benchmarking takes 2.0288 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0978 ms 100.0%
  triton_mm_2563 0.0991 ms 98.7%
  triton_mm_2556 0.1044 ms 93.6%
  triton_mm_2562 0.1087 ms 90.0%
  triton_mm_2553 0.1182 ms 82.7%
  triton_mm_2554 0.1204 ms 81.2%
  triton_mm_2558 0.1211 ms 80.7%
  triton_mm_2561 0.1241 ms 78.8%
  triton_mm_2557 0.1266 ms 77.3%
  triton_mm_2559 0.1309 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.3739 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2646 ms 100.0%
  triton_mm_2653 0.2678 ms 98.8%
  triton_mm_2652 0.2695 ms 98.2%
  triton_mm_2654 0.3082 ms 85.9%
  triton_mm_2645 0.3318 ms 79.8%
  triton_mm_2649 0.3384 ms 78.2%
  triton_mm_2647 0.3406 ms 77.7%
  triton_mm_2646 0.3571 ms 74.1%
  triton_mm_2650 0.3769 ms 70.2%
  triton_mm_2648 0.4189 ms 63.2%
SingleProcess AUTOTUNE benchmarking takes 2.4977 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2867 ms 100.0%
  triton_mm_2690 0.2911 ms 98.5%
  triton_mm_2691 0.3002 ms 95.5%
  triton_mm_2692 0.3093 ms 92.7%
  triton_mm_2687 0.3380 ms 84.8%
  triton_mm_2685 0.3428 ms 83.6%
  triton_mm_2683 0.3473 ms 82.5%
  triton_mm_2686 0.3613 ms 79.3%
  triton_mm_2684 0.3774 ms 76.0%
  triton_mm_2688 0.3838 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5046 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2632 0.0185 ms 100.0%
  triton_mm_2626 0.0185 ms 99.8%
  triton_mm_2625 0.0191 ms 97.0%
  triton_mm_2627 0.0192 ms 96.5%
  triton_mm_2624 0.0196 ms 94.3%
  triton_mm_2629 0.0197 ms 93.8%
  triton_mm_2628 0.0198 ms 93.2%
  triton_mm_2630 0.0199 ms 93.1%
  triton_mm_2634 0.0199 ms 93.1%
  triton_mm_2631 0.0200 ms 92.6%
SingleProcess AUTOTUNE benchmarking takes 2.0064 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2606 0.0285 ms 100.0%
  mm 0.0291 ms 98.1%
  triton_mm_2610 0.0320 ms 89.2%
  triton_mm_2614 0.0411 ms 69.3%
  triton_mm_2618 0.0508 ms 56.1%
  triton_mm_2605 0.0518 ms 55.0%
  triton_mm_2604 0.0560 ms 50.9%
  triton_mm_2609 0.0602 ms 47.4%
  triton_mm_2613 0.0630 ms 45.2%
  triton_mm_2603 0.0654 ms 43.6%
SingleProcess AUTOTUNE benchmarking takes 2.0337 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0977 ms 100.0%
  triton_mm_2749 0.0991 ms 98.6%
  triton_mm_2742 0.1044 ms 93.6%
  triton_mm_2748 0.1087 ms 89.9%
  triton_mm_2739 0.1181 ms 82.7%
  triton_mm_2740 0.1205 ms 81.1%
  triton_mm_2744 0.1217 ms 80.3%
  triton_mm_2747 0.1242 ms 78.7%
  triton_mm_2743 0.1265 ms 77.3%
  triton_mm_2745 0.1301 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.3804 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2662 ms 100.0%
  triton_mm_2838 0.2693 ms 98.8%
  triton_mm_2839 0.2708 ms 98.3%
  triton_mm_2840 0.3084 ms 86.3%
  triton_mm_2831 0.3318 ms 80.2%
  triton_mm_2833 0.3364 ms 79.1%
  triton_mm_2835 0.3389 ms 78.5%
  triton_mm_2832 0.3547 ms 75.0%
  triton_mm_2836 0.3736 ms 71.3%
  triton_mm_2834 0.4194 ms 63.5%
SingleProcess AUTOTUNE benchmarking takes 2.5050 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2887 ms 100.0%
  triton_mm_2876 0.2911 ms 99.2%
  triton_mm_2877 0.3000 ms 96.2%
  triton_mm_2878 0.3092 ms 93.4%
  triton_mm_2873 0.3386 ms 85.3%
  triton_mm_2869 0.3435 ms 84.0%
  triton_mm_2871 0.3488 ms 82.8%
  triton_mm_2872 0.3610 ms 80.0%
  triton_mm_2870 0.3740 ms 77.2%
  triton_mm_2874 0.3825 ms 75.5%
SingleProcess AUTOTUNE benchmarking takes 2.5106 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2813 0.0183 ms 100.0%
  triton_mm_2812 0.0186 ms 98.6%
  triton_mm_2815 0.0190 ms 96.5%
  triton_mm_2814 0.0190 ms 96.1%
  triton_mm_2811 0.0191 ms 96.0%
  triton_mm_2816 0.0191 ms 96.0%
  triton_mm_2817 0.0192 ms 95.2%
  triton_mm_2818 0.0194 ms 94.2%
  triton_mm_2810 0.0196 ms 93.2%
  triton_mm_2820 0.0199 ms 92.1%
SingleProcess AUTOTUNE benchmarking takes 2.0153 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0291 ms 100.0%
  triton_mm_2792 0.0292 ms 99.6%
  triton_mm_2796 0.0318 ms 91.4%
  triton_mm_2800 0.0410 ms 71.0%
  triton_mm_2804 0.0507 ms 57.4%
  triton_mm_2791 0.0519 ms 56.1%
  triton_mm_2790 0.0553 ms 52.6%
  triton_mm_2795 0.0602 ms 48.3%
  triton_mm_2799 0.0631 ms 46.1%
  triton_mm_2789 0.0654 ms 44.5%
SingleProcess AUTOTUNE benchmarking takes 2.0413 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0978 ms 100.0%
  triton_mm_2935 0.0991 ms 98.7%
  triton_mm_2928 0.1044 ms 93.7%
  triton_mm_2934 0.1087 ms 90.0%
  triton_mm_2925 0.1181 ms 82.8%
  triton_mm_2926 0.1204 ms 81.2%
  triton_mm_2930 0.1217 ms 80.3%
  triton_mm_2933 0.1235 ms 79.2%
  triton_mm_2929 0.1266 ms 77.3%
  triton_mm_2931 0.1301 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.3744 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_3121 0.0983 ms 98.6%
  triton_mm_3114 0.1044 ms 92.9%
  triton_mm_3120 0.1091 ms 88.9%
  triton_mm_3111 0.1181 ms 82.1%
  triton_mm_3112 0.1205 ms 80.5%
  triton_mm_3116 0.1211 ms 80.1%
  triton_mm_3119 0.1242 ms 78.1%
  triton_mm_3115 0.1266 ms 76.6%
  triton_mm_3117 0.1307 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.3840 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0977 ms 100.0%
  triton_mm_3307 0.0983 ms 99.3%
  triton_mm_3300 0.1045 ms 93.5%
  triton_mm_3306 0.1092 ms 89.5%
  triton_mm_3297 0.1182 ms 82.7%
  triton_mm_3298 0.1205 ms 81.1%
  triton_mm_3302 0.1211 ms 80.7%
  triton_mm_3305 0.1242 ms 78.7%
  triton_mm_3301 0.1265 ms 77.2%
  triton_mm_3303 0.1311 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.3924 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0976 ms 100.0%
  triton_mm_3493 0.0991 ms 98.5%
  triton_mm_3486 0.1044 ms 93.5%
  triton_mm_3492 0.1086 ms 89.9%
  triton_mm_3483 0.1181 ms 82.7%
  triton_mm_3484 0.1205 ms 81.0%
  triton_mm_3488 0.1217 ms 80.2%
  triton_mm_3491 0.1241 ms 78.7%
  triton_mm_3487 0.1265 ms 77.2%
  triton_mm_3489 0.1301 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.3943 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0303 ms 100.0%
  triton_mm_4872 0.0502 ms 60.4%
  triton_mm_4879 0.0507 ms 59.7%
  triton_mm_4870 0.0562 ms 54.0%
  triton_mm_4871 0.0628 ms 48.2%
  triton_mm_4878 0.0674 ms 45.0%
  triton_mm_4875 0.0698 ms 43.4%
  triton_mm_4884 0.0730 ms 41.5%
  triton_mm_4883 0.0743 ms 40.8%
  triton_mm_4877 0.0776 ms 39.1%
SingleProcess AUTOTUNE benchmarking takes 6.1589 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_2 0.0292 ms 100.0%
  triton_mm_3 0.0299 ms 98.0%
  triton_mm_7 0.0300 ms 97.3%
  triton_mm_12 0.0306 ms 95.5%
  triton_mm_1 0.0309 ms 94.7%
  triton_mm_4 0.0309 ms 94.7%
  triton_mm_10 0.0311 ms 94.1%
  triton_mm_11 0.0311 ms 93.9%
  triton_mm_9 0.0312 ms 93.6%
  triton_mm_13 0.0313 ms 93.5%
SingleProcess AUTOTUNE benchmarking takes 1.9478 seconds and 0.0142 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_33 0.0246 ms 100.0%
  triton_mm_21 0.0253 ms 97.3%
  triton_mm_25 0.0255 ms 96.5%
  triton_mm_29 0.0257 ms 95.6%
  triton_mm_28 0.0261 ms 94.2%
  triton_mm_24 0.0263 ms 93.7%
  triton_mm_18 0.0268 ms 91.7%
  triton_mm_19 0.0270 ms 91.0%
  bias_addmm 0.0273 ms 90.0%
  triton_mm_20 0.0279 ms 88.2%
SingleProcess AUTOTUNE benchmarking takes 2.1090 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2159 ms 100.0%
  triton_mm_51 0.2222 ms 97.1%
  bias_addmm 0.2521 ms 85.6%
  triton_mm_52 0.2537 ms 85.1%
  triton_mm_45 0.2570 ms 84.0%
  triton_mm_47 0.2673 ms 80.8%
  addmm 0.2686 ms 80.4%
  triton_mm_43 0.2712 ms 79.6%
  triton_mm_44 0.3043 ms 70.9%
  triton_mm_48 0.3058 ms 70.6%
SingleProcess AUTOTUNE benchmarking takes 2.5357 seconds and 0.0165 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0900 ms 100.0%
  triton_mm_69 0.0913 ms 98.6%
  bias_addmm 0.0961 ms 93.7%
  triton_mm_64 0.0974 ms 92.4%
  triton_mm_66 0.0980 ms 91.9%
  triton_mm_71 0.1001 ms 90.0%
  triton_mm_62 0.1015 ms 88.7%
  addmm 0.1092 ms 82.4%
  triton_mm_63 0.1108 ms 81.3%
  triton_mm_67 0.1123 ms 80.2%
SingleProcess AUTOTUNE benchmarking takes 2.4698 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2713 ms 100.0%
  triton_mm_88 0.2879 ms 94.2%
  triton_mm_89 0.2879 ms 94.2%
  triton_mm_90 0.3306 ms 82.1%
  triton_mm_83 0.3371 ms 80.5%
  addmm 0.3544 ms 76.6%
  triton_mm_85 0.3581 ms 75.8%
  triton_mm_81 0.3583 ms 75.7%
  triton_mm_82 0.3945 ms 68.8%
  triton_mm_86 0.4071 ms 66.6%
SingleProcess AUTOTUNE benchmarking takes 2.6615 seconds and 0.0018 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2838 ms 100.0%
  triton_mm_108 0.2970 ms 95.6%
  triton_mm_107 0.3067 ms 92.5%
  addmm 0.3160 ms 89.8%
  triton_mm_109 0.3181 ms 89.2%
  triton_mm_104 0.3502 ms 81.0%
  triton_mm_102 0.3519 ms 80.7%
  triton_mm_100 0.3597 ms 78.9%
  triton_mm_103 0.3636 ms 78.1%
  triton_mm_105 0.3985 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.6328 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2765 ms 100.0%
  triton_mm_181 0.2878 ms 96.1%
  triton_mm_182 0.2931 ms 94.4%
  triton_mm_183 0.3330 ms 83.0%
  triton_mm_176 0.3360 ms 82.3%
  triton_mm_174 0.3587 ms 77.1%
  triton_mm_178 0.3590 ms 77.0%
  addmm 0.3590 ms 77.0%
  triton_mm_175 0.3942 ms 70.1%
  triton_mm_179 0.4056 ms 68.2%
SingleProcess AUTOTUNE benchmarking takes 2.6338 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2845 ms 100.0%
  triton_mm_201 0.2943 ms 96.7%
  triton_mm_200 0.3060 ms 93.0%
  addmm 0.3178 ms 89.5%
  triton_mm_202 0.3213 ms 88.6%
  triton_mm_197 0.3514 ms 81.0%
  triton_mm_195 0.3521 ms 80.8%
  triton_mm_193 0.3597 ms 79.1%
  triton_mm_196 0.3638 ms 78.2%
  triton_mm_198 0.3994 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.6307 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2736 ms 100.0%
  triton_mm_274 0.2878 ms 95.1%
  triton_mm_275 0.2884 ms 94.9%
  triton_mm_276 0.3295 ms 83.0%
  triton_mm_269 0.3337 ms 82.0%
  addmm 0.3506 ms 78.0%
  triton_mm_267 0.3577 ms 76.5%
  triton_mm_271 0.3593 ms 76.1%
  triton_mm_268 0.4024 ms 68.0%
  triton_mm_272 0.4059 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 2.6301 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2845 ms 100.0%
  triton_mm_294 0.2976 ms 95.6%
  triton_mm_293 0.3067 ms 92.8%
  addmm 0.3171 ms 89.7%
  triton_mm_295 0.3178 ms 89.5%
  triton_mm_288 0.3483 ms 81.7%
  triton_mm_290 0.3492 ms 81.5%
  triton_mm_289 0.3616 ms 78.7%
  triton_mm_286 0.3630 ms 78.4%
  triton_mm_291 0.3990 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 2.6337 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0142 ms 100.0%
  triton_mm_1606 0.0146 ms 97.6%
  mm 0.0162 ms 87.7%
  triton_mm_1610 0.0164 ms 87.1%
  triton_mm_1614 0.0170 ms 83.8%
  triton_mm_1601 0.0171 ms 83.3%
  triton_mm_1605 0.0184 ms 77.4%
  triton_mm_1600 0.0186 ms 76.5%
  triton_mm_1599 0.0186 ms 76.4%
  triton_mm_1612 0.0195 ms 73.2%
SingleProcess AUTOTUNE benchmarking takes 7.3844 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1632 0.5440 ms 100.0%
  bias_addmm 0.5482 ms 99.2%
  triton_mm_1631 0.5482 ms 99.2%
  triton_mm_1633 0.6138 ms 88.6%
  triton_mm_1626 0.6557 ms 83.0%
  triton_mm_1628 0.6694 ms 81.3%
  addmm 0.6857 ms 79.3%
  triton_mm_1624 0.7014 ms 77.6%
  triton_mm_1629 0.7644 ms 71.2%
  triton_mm_1625 0.7716 ms 70.5%
SingleProcess AUTOTUNE benchmarking takes 11.3293 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.5154 ms 100.0%
  triton_mm_1669 0.5312 ms 97.0%
  triton_mm_1670 0.5527 ms 93.3%
  triton_mm_1671 0.5791 ms 89.0%
  triton_mm_1664 0.6580 ms 78.3%
  triton_mm_1662 0.6738 ms 76.5%
  triton_mm_1666 0.6773 ms 76.1%
  triton_mm_1667 0.7079 ms 72.8%
  triton_mm_1665 0.7140 ms 72.2%
  triton_mm_1663 0.7189 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 9.5960 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2760 ms 100.0%
  triton_mm_1742 0.2809 ms 98.3%
  triton_mm_1741 0.2862 ms 96.5%
  triton_mm_1743 0.2897 ms 95.3%
  triton_mm_1736 0.3364 ms 82.1%
  triton_mm_1734 0.3429 ms 80.5%
  triton_mm_1738 0.3480 ms 79.3%
  triton_mm_1737 0.3640 ms 75.8%
  triton_mm_1739 0.3857 ms 71.6%
  triton_mm_1735 0.3887 ms 71.0%
SingleProcess AUTOTUNE benchmarking takes 9.5815 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1697 0.0119 ms 100.0%
  triton_mm_1699 0.0119 ms 100.0%
  triton_mm_1696 0.0121 ms 98.4%
  triton_mm_1700 0.0123 ms 96.9%
  triton_mm_1695 0.0124 ms 95.6%
  triton_mm_1693 0.0127 ms 93.5%
  triton_mm_1703 0.0127 ms 93.5%
  triton_mm_1691 0.0128 ms 93.0%
  triton_mm_1694 0.0128 ms 92.7%
  triton_mm_1698 0.0130 ms 91.9%
SingleProcess AUTOTUNE benchmarking takes 5.7136 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0157 ms 100.0%
  triton_mm_1680 0.0175 ms 89.6%
  mm 0.0182 ms 86.1%
  triton_mm_1684 0.0201 ms 78.1%
  triton_mm_1688 0.0225 ms 69.8%
  triton_mm_1675 0.0230 ms 68.4%
  triton_mm_1674 0.0243 ms 64.7%
  triton_mm_1683 0.0256 ms 61.5%
  triton_mm_1679 0.0258 ms 61.0%
  triton_mm_1673 0.0262 ms 60.0%
SingleProcess AUTOTUNE benchmarking takes 2.0371 seconds and 0.0008 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5290 ms 100.0%
  triton_mm_1650 0.5456 ms 97.0%
  triton_mm_1651 0.5516 ms 95.9%
  triton_mm_1652 0.5718 ms 92.5%
  triton_mm_1645 0.6406 ms 82.6%
  triton_mm_1643 0.6536 ms 80.9%
  triton_mm_1647 0.6544 ms 80.8%
  triton_mm_1646 0.6909 ms 76.6%
  triton_mm_1648 0.7097 ms 74.5%
  triton_mm_1644 0.7115 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 9.8143 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1723 0.2660 ms 100.0%
  triton_mm_1722 0.2663 ms 99.9%
  mm 0.2709 ms 98.2%
  triton_mm_1724 0.3037 ms 87.6%
  triton_mm_1715 0.3259 ms 81.6%
  triton_mm_1717 0.3313 ms 80.3%
  triton_mm_1719 0.3327 ms 80.0%
  triton_mm_1716 0.3507 ms 75.9%
  triton_mm_1720 0.3729 ms 71.3%
  triton_mm_1718 0.4188 ms 63.5%
SingleProcess AUTOTUNE benchmarking takes 12.4196 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2137 ms 100.0%
  triton_mm_1837 0.2148 ms 99.5%
  triton_mm_1836 0.2212 ms 96.6%
  triton_mm_1838 0.2340 ms 91.3%
  triton_mm_1833 0.2475 ms 86.4%
  triton_mm_1831 0.2532 ms 84.4%
  triton_mm_1829 0.2532 ms 84.4%
  triton_mm_1830 0.2806 ms 76.2%
  triton_mm_1832 0.2844 ms 75.2%
  triton_mm_1834 0.2888 ms 74.0%
SingleProcess AUTOTUNE benchmarking takes 2.4719 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2770 ms 100.0%
  triton_mm_1780 0.2780 ms 99.7%
  mm 0.2795 ms 99.1%
  triton_mm_1781 0.2867 ms 96.6%
  triton_mm_1776 0.3310 ms 83.7%
  triton_mm_1772 0.3392 ms 81.7%
  triton_mm_1774 0.3419 ms 81.0%
  triton_mm_1775 0.3700 ms 74.9%
  triton_mm_1777 0.3777 ms 73.3%
  triton_mm_1773 0.3845 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 9.8577 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2166 ms 100.0%
  triton_mm_1855 0.2697 ms 80.3%
  triton_mm_1850 0.2697 ms 80.3%
  triton_mm_1852 0.2740 ms 79.1%
  triton_mm_1848 0.2750 ms 78.8%
  triton_mm_1856 0.2761 ms 78.5%
  triton_mm_1857 0.2790 ms 77.6%
  triton_mm_1851 0.3023 ms 71.7%
  triton_mm_1853 0.3133 ms 69.1%
  triton_mm_1849 0.3204 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 9.9040 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0975 ms 100.0%
  triton_mm_1819 0.0992 ms 98.3%
  triton_mm_1812 0.1051 ms 92.8%
  triton_mm_1818 0.1079 ms 90.4%
  triton_mm_1809 0.1180 ms 82.7%
  triton_mm_1810 0.1190 ms 81.9%
  triton_mm_1814 0.1208 ms 80.8%
  triton_mm_1817 0.1228 ms 79.4%
  triton_mm_1813 0.1268 ms 76.9%
  triton_mm_1815 0.1300 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.3892 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2888 ms 100.0%
  triton_mm_1760 0.2930 ms 98.6%
  triton_mm_1761 0.2994 ms 96.5%
  triton_mm_1762 0.3102 ms 93.1%
  triton_mm_1757 0.3332 ms 86.7%
  triton_mm_1755 0.3395 ms 85.1%
  triton_mm_1753 0.3433 ms 84.1%
  triton_mm_1756 0.3591 ms 80.4%
  triton_mm_1754 0.3788 ms 76.2%
  triton_mm_1758 0.3864 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5105 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0833 ms 100.0%
  mm 0.0844 ms 98.6%
  triton_mm_1798 0.0856 ms 97.3%
  triton_mm_1795 0.0919 ms 90.7%
  triton_mm_1791 0.0938 ms 88.8%
  triton_mm_1800 0.0943 ms 88.3%
  triton_mm_1793 0.0945 ms 88.1%
  triton_mm_1792 0.1012 ms 82.3%
  triton_mm_1796 0.1056 ms 78.9%
  triton_mm_1794 0.1232 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.3690 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2662 ms 100.0%
  triton_mm_1908 0.2680 ms 99.3%
  triton_mm_1909 0.2724 ms 97.7%
  triton_mm_1910 0.3101 ms 85.8%
  triton_mm_1901 0.3347 ms 79.5%
  triton_mm_1903 0.3364 ms 79.2%
  triton_mm_1905 0.3410 ms 78.1%
  triton_mm_1902 0.3551 ms 75.0%
  triton_mm_1906 0.3798 ms 70.1%
  triton_mm_1904 0.4222 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.5067 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2882 ms 100.0%
  triton_mm_1946 0.2904 ms 99.2%
  triton_mm_1947 0.3016 ms 95.5%
  triton_mm_1948 0.3135 ms 91.9%
  triton_mm_1943 0.3323 ms 86.7%
  triton_mm_1941 0.3395 ms 84.9%
  triton_mm_1939 0.3428 ms 84.1%
  triton_mm_1942 0.3596 ms 80.1%
  triton_mm_1940 0.3804 ms 75.8%
  triton_mm_1944 0.3870 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.5046 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1881 0.0184 ms 100.0%
  triton_mm_1883 0.0184 ms 100.0%
  triton_mm_1882 0.0185 ms 99.3%
  triton_mm_1888 0.0186 ms 99.1%
  triton_mm_1885 0.0188 ms 98.0%
  triton_mm_1884 0.0190 ms 96.8%
  triton_mm_1887 0.0193 ms 95.4%
  triton_mm_1880 0.0195 ms 94.4%
  triton_mm_1889 0.0198 ms 93.0%
  triton_mm_1886 0.0198 ms 92.7%
SingleProcess AUTOTUNE benchmarking takes 5.7630 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2791 ms 100.0%
  triton_mm_1965 0.2833 ms 98.5%
  triton_mm_1966 0.2919 ms 95.6%
  triton_mm_1967 0.2936 ms 95.1%
  triton_mm_1962 0.3360 ms 83.1%
  triton_mm_1958 0.3474 ms 80.3%
  triton_mm_1960 0.3520 ms 79.3%
  triton_mm_1961 0.3737 ms 74.7%
  triton_mm_1963 0.3840 ms 72.7%
  triton_mm_1959 0.3944 ms 70.8%
SingleProcess AUTOTUNE benchmarking takes 2.5111 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0290 ms 100.0%
  triton_mm_1862 0.0291 ms 99.7%
  triton_mm_1866 0.0319 ms 90.8%
  triton_mm_1870 0.0400 ms 72.5%
  triton_mm_1874 0.0508 ms 57.0%
  triton_mm_1861 0.0514 ms 56.4%
  triton_mm_1860 0.0551 ms 52.6%
  triton_mm_1865 0.0601 ms 48.3%
  triton_mm_1869 0.0619 ms 46.8%
  triton_mm_1859 0.0648 ms 44.7%
SingleProcess AUTOTUNE benchmarking takes 2.0415 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1985 0.0832 ms 100.0%
  mm 0.0833 ms 99.9%
  triton_mm_1984 0.0856 ms 97.3%
  triton_mm_1981 0.0927 ms 89.8%
  triton_mm_1977 0.0947 ms 87.9%
  triton_mm_1986 0.0951 ms 87.5%
  triton_mm_1979 0.0953 ms 87.3%
  triton_mm_1978 0.1018 ms 81.7%
  triton_mm_1982 0.1048 ms 79.4%
  triton_mm_1980 0.1226 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.3610 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2158 ms 100.0%
  triton_mm_2023 0.2170 ms 99.4%
  triton_mm_2022 0.2196 ms 98.3%
  triton_mm_2024 0.2366 ms 91.2%
  triton_mm_2019 0.2497 ms 86.4%
  triton_mm_2017 0.2542 ms 84.9%
  triton_mm_2015 0.2544 ms 84.8%
  triton_mm_2016 0.2840 ms 76.0%
  triton_mm_2018 0.2842 ms 75.9%
  triton_mm_2020 0.2889 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4805 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2662 ms 100.0%
  triton_mm_2094 0.2712 ms 98.1%
  triton_mm_2095 0.2740 ms 97.2%
  triton_mm_2096 0.3141 ms 84.7%
  triton_mm_2087 0.3360 ms 79.2%
  triton_mm_2089 0.3364 ms 79.1%
  triton_mm_2091 0.3387 ms 78.6%
  triton_mm_2088 0.3578 ms 74.4%
  triton_mm_2092 0.3816 ms 69.8%
  triton_mm_2090 0.4227 ms 63.0%
SingleProcess AUTOTUNE benchmarking takes 2.5010 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2904 ms 100.0%
  triton_mm_2132 0.2923 ms 99.4%
  triton_mm_2133 0.3022 ms 96.1%
  triton_mm_2134 0.3110 ms 93.4%
  triton_mm_2129 0.3361 ms 86.4%
  triton_mm_2127 0.3424 ms 84.8%
  triton_mm_2125 0.3436 ms 84.5%
  triton_mm_2128 0.3609 ms 80.5%
  triton_mm_2126 0.3806 ms 76.3%
  triton_mm_2130 0.3868 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5045 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2048 0.0291 ms 99.3%
  triton_mm_2052 0.0319 ms 90.8%
  triton_mm_2056 0.0400 ms 72.3%
  triton_mm_2047 0.0514 ms 56.3%
  triton_mm_2060 0.0519 ms 55.8%
  triton_mm_2046 0.0551 ms 52.5%
  triton_mm_2051 0.0601 ms 48.2%
  triton_mm_2055 0.0619 ms 46.7%
  triton_mm_2045 0.0650 ms 44.5%
SingleProcess AUTOTUNE benchmarking takes 2.0319 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2171 0.0832 ms 100.0%
  mm 0.0833 ms 99.9%
  triton_mm_2170 0.0855 ms 97.3%
  triton_mm_2167 0.0925 ms 89.9%
  triton_mm_2163 0.0947 ms 87.8%
  triton_mm_2172 0.0950 ms 87.6%
  triton_mm_2165 0.0954 ms 87.2%
  triton_mm_2164 0.1018 ms 81.7%
  triton_mm_2168 0.1048 ms 79.4%
  triton_mm_2166 0.1225 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.3626 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2150 ms 100.0%
  triton_mm_2209 0.2172 ms 99.0%
  triton_mm_2208 0.2228 ms 96.5%
  triton_mm_2210 0.2363 ms 91.0%
  triton_mm_2205 0.2510 ms 85.6%
  triton_mm_2203 0.2547 ms 84.4%
  triton_mm_2201 0.2560 ms 84.0%
  triton_mm_2202 0.2842 ms 75.6%
  triton_mm_2204 0.2842 ms 75.6%
  triton_mm_2206 0.2908 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.4732 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2669 ms 100.0%
  triton_mm_2280 0.2707 ms 98.6%
  triton_mm_2281 0.2741 ms 97.4%
  triton_mm_2282 0.3155 ms 84.6%
  triton_mm_2273 0.3366 ms 79.3%
  triton_mm_2275 0.3375 ms 79.1%
  triton_mm_2277 0.3410 ms 78.3%
  triton_mm_2274 0.3581 ms 74.5%
  triton_mm_2278 0.3810 ms 70.1%
  triton_mm_2276 0.4216 ms 63.3%
SingleProcess AUTOTUNE benchmarking takes 2.5082 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2904 ms 100.0%
  triton_mm_2318 0.2927 ms 99.2%
  triton_mm_2319 0.2992 ms 97.1%
  triton_mm_2320 0.3111 ms 93.4%
  triton_mm_2315 0.3352 ms 86.6%
  triton_mm_2313 0.3410 ms 85.2%
  triton_mm_2311 0.3426 ms 84.8%
  triton_mm_2314 0.3625 ms 80.1%
  triton_mm_2312 0.3815 ms 76.1%
  triton_mm_2316 0.3900 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.5102 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2234 0.0292 ms 99.1%
  triton_mm_2238 0.0319 ms 90.6%
  triton_mm_2242 0.0407 ms 71.0%
  triton_mm_2233 0.0513 ms 56.3%
  triton_mm_2246 0.0516 ms 56.0%
  triton_mm_2232 0.0551 ms 52.5%
  triton_mm_2237 0.0600 ms 48.1%
  triton_mm_2241 0.0620 ms 46.6%
  triton_mm_2231 0.0655 ms 44.1%
SingleProcess AUTOTUNE benchmarking takes 2.0311 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2667 ms 100.0%
  triton_mm_2466 0.2690 ms 99.1%
  triton_mm_2467 0.2748 ms 97.1%
  triton_mm_2468 0.3125 ms 85.3%
  triton_mm_2459 0.3356 ms 79.5%
  triton_mm_2461 0.3364 ms 79.3%
  triton_mm_2463 0.3399 ms 78.5%
  triton_mm_2460 0.3582 ms 74.4%
  triton_mm_2464 0.3802 ms 70.2%
  triton_mm_2462 0.4219 ms 63.2%
SingleProcess AUTOTUNE benchmarking takes 2.5061 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2889 ms 100.0%
  triton_mm_2504 0.2938 ms 98.3%
  triton_mm_2505 0.3057 ms 94.5%
  triton_mm_2506 0.3161 ms 91.4%
  triton_mm_2501 0.3352 ms 86.2%
  triton_mm_2499 0.3435 ms 84.1%
  triton_mm_2497 0.3454 ms 83.6%
  triton_mm_2500 0.3598 ms 80.3%
  triton_mm_2498 0.3807 ms 75.9%
  triton_mm_2502 0.3858 ms 74.9%
SingleProcess AUTOTUNE benchmarking takes 2.5164 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2420 0.0298 ms 97.1%
  triton_mm_2424 0.0310 ms 93.3%
  triton_mm_2428 0.0410 ms 70.5%
  triton_mm_2432 0.0508 ms 56.9%
  triton_mm_2419 0.0522 ms 55.5%
  triton_mm_2418 0.0551 ms 52.5%
  triton_mm_2423 0.0594 ms 48.7%
  triton_mm_2427 0.0627 ms 46.2%
  triton_mm_2417 0.0648 ms 44.6%
SingleProcess AUTOTUNE benchmarking takes 2.0439 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2644 ms 100.0%
  triton_mm_2652 0.2678 ms 98.7%
  triton_mm_2653 0.2726 ms 97.0%
  triton_mm_2654 0.3117 ms 84.8%
  triton_mm_2645 0.3334 ms 79.3%
  triton_mm_2647 0.3379 ms 78.2%
  triton_mm_2649 0.3424 ms 77.2%
  triton_mm_2646 0.3611 ms 73.2%
  triton_mm_2650 0.3801 ms 69.6%
  triton_mm_2648 0.4217 ms 62.7%
SingleProcess AUTOTUNE benchmarking takes 2.5018 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  triton_mm_2690 0.2884 ms 100.0%
  mm 0.2885 ms 99.9%
  triton_mm_2691 0.3013 ms 95.7%
  triton_mm_2692 0.3094 ms 93.2%
  triton_mm_2687 0.3363 ms 85.7%
  triton_mm_2683 0.3424 ms 84.2%
  triton_mm_2685 0.3543 ms 81.4%
  triton_mm_2686 0.3603 ms 80.0%
  triton_mm_2684 0.3813 ms 75.6%
  triton_mm_2688 0.3860 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5025 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2606 0.0291 ms 99.3%
  triton_mm_2610 0.0317 ms 91.3%
  triton_mm_2614 0.0408 ms 71.0%
  triton_mm_2605 0.0514 ms 56.3%
  triton_mm_2618 0.0515 ms 56.1%
  triton_mm_2604 0.0551 ms 52.5%
  triton_mm_2609 0.0600 ms 48.2%
  triton_mm_2613 0.0619 ms 46.7%
  triton_mm_2603 0.0649 ms 44.6%
SingleProcess AUTOTUNE benchmarking takes 2.0416 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2648 ms 100.0%
  triton_mm_2838 0.2701 ms 98.1%
  triton_mm_2839 0.2740 ms 96.6%
  triton_mm_2840 0.3099 ms 85.4%
  triton_mm_2831 0.3343 ms 79.2%
  triton_mm_2833 0.3377 ms 78.4%
  triton_mm_2835 0.3416 ms 77.5%
  triton_mm_2832 0.3549 ms 74.6%
  triton_mm_2836 0.3817 ms 69.4%
  triton_mm_2834 0.4227 ms 62.6%
SingleProcess AUTOTUNE benchmarking takes 2.5016 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2883 ms 100.0%
  triton_mm_2876 0.2942 ms 98.0%
  triton_mm_2877 0.3017 ms 95.6%
  triton_mm_2878 0.3135 ms 92.0%
  triton_mm_2873 0.3339 ms 86.3%
  triton_mm_2871 0.3431 ms 84.0%
  triton_mm_2869 0.3452 ms 83.5%
  triton_mm_2872 0.3597 ms 80.1%
  triton_mm_2870 0.3777 ms 76.3%
  triton_mm_2874 0.3860 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5057 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2792 0.0291 ms 99.2%
  triton_mm_2796 0.0319 ms 90.7%
  triton_mm_2800 0.0400 ms 72.3%
  triton_mm_2804 0.0508 ms 56.9%
  triton_mm_2791 0.0519 ms 55.6%
  triton_mm_2790 0.0558 ms 51.8%
  triton_mm_2795 0.0600 ms 48.1%
  triton_mm_2799 0.0620 ms 46.6%
  triton_mm_2789 0.0655 ms 44.1%
SingleProcess AUTOTUNE benchmarking takes 2.0396 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2640 ms 100.0%
  triton_mm_3025 0.2717 ms 97.1%
  triton_mm_3024 0.2718 ms 97.1%
  triton_mm_3026 0.3090 ms 85.4%
  triton_mm_3017 0.3329 ms 79.3%
  triton_mm_3019 0.3421 ms 77.2%
  triton_mm_3021 0.3432 ms 76.9%
  triton_mm_3018 0.3576 ms 73.8%
  triton_mm_3022 0.3790 ms 69.6%
  triton_mm_3020 0.4229 ms 62.4%
SingleProcess AUTOTUNE benchmarking takes 2.5102 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2889 ms 100.0%
  triton_mm_3062 0.2924 ms 98.8%
  triton_mm_3063 0.3003 ms 96.2%
  triton_mm_3064 0.3098 ms 93.2%
  triton_mm_3059 0.3355 ms 86.1%
  triton_mm_3055 0.3426 ms 84.3%
  triton_mm_3057 0.3447 ms 83.8%
  triton_mm_3058 0.3597 ms 80.3%
  triton_mm_3056 0.3775 ms 76.5%
  triton_mm_3060 0.3861 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 2.5175 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_2978 0.0292 ms 99.0%
  triton_mm_2982 0.0320 ms 90.4%
  triton_mm_2986 0.0408 ms 70.9%
  triton_mm_2990 0.0508 ms 56.8%
  triton_mm_2977 0.0513 ms 56.3%
  triton_mm_2976 0.0551 ms 52.4%
  triton_mm_2981 0.0600 ms 48.1%
  triton_mm_2985 0.0627 ms 46.1%
  triton_mm_2975 0.0648 ms 44.6%
SingleProcess AUTOTUNE benchmarking takes 2.0393 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2641 ms 100.0%
  triton_mm_3210 0.2693 ms 98.1%
  triton_mm_3211 0.2739 ms 96.4%
  triton_mm_3212 0.3115 ms 84.8%
  triton_mm_3205 0.3365 ms 78.5%
  triton_mm_3203 0.3369 ms 78.4%
  triton_mm_3207 0.3383 ms 78.1%
  triton_mm_3204 0.3588 ms 73.6%
  triton_mm_3208 0.3816 ms 69.2%
  triton_mm_3206 0.4226 ms 62.5%
SingleProcess AUTOTUNE benchmarking takes 2.5114 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2907 ms 100.0%
  triton_mm_3248 0.2932 ms 99.2%
  triton_mm_3249 0.3022 ms 96.2%
  triton_mm_3250 0.3131 ms 92.9%
  triton_mm_3245 0.3354 ms 86.7%
  triton_mm_3241 0.3458 ms 84.1%
  triton_mm_3243 0.3461 ms 84.0%
  triton_mm_3244 0.3597 ms 80.8%
  triton_mm_3242 0.3813 ms 76.2%
  triton_mm_3246 0.3867 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5124 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_3164 0.0299 ms 96.7%
  triton_mm_3168 0.0317 ms 91.3%
  triton_mm_3172 0.0400 ms 72.3%
  triton_mm_3176 0.0508 ms 56.9%
  triton_mm_3163 0.0520 ms 55.5%
  triton_mm_3162 0.0557 ms 51.8%
  triton_mm_3167 0.0594 ms 48.7%
  triton_mm_3171 0.0626 ms 46.2%
  triton_mm_3161 0.0655 ms 44.1%
SingleProcess AUTOTUNE benchmarking takes 2.0426 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2663 ms 100.0%
  triton_mm_3396 0.2719 ms 97.9%
  triton_mm_3397 0.2735 ms 97.4%
  triton_mm_3398 0.3127 ms 85.2%
  triton_mm_3391 0.3361 ms 79.2%
  triton_mm_3393 0.3399 ms 78.3%
  triton_mm_3389 0.3428 ms 77.7%
  triton_mm_3390 0.3585 ms 74.3%
  triton_mm_3394 0.3816 ms 69.8%
  triton_mm_3392 0.4214 ms 63.2%
SingleProcess AUTOTUNE benchmarking takes 2.5092 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2905 ms 100.0%
  triton_mm_3434 0.2938 ms 98.9%
  triton_mm_3435 0.2993 ms 97.0%
  triton_mm_3436 0.3129 ms 92.9%
  triton_mm_3427 0.3415 ms 85.1%
  triton_mm_3429 0.3422 ms 84.9%
  triton_mm_3431 0.3422 ms 84.9%
  triton_mm_3430 0.3602 ms 80.7%
  triton_mm_3428 0.3815 ms 76.2%
  triton_mm_3432 0.3866 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5120 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0289 ms 100.0%
  triton_mm_3350 0.0291 ms 99.3%
  triton_mm_3354 0.0316 ms 91.5%
  triton_mm_3358 0.0404 ms 71.5%
  triton_mm_3349 0.0513 ms 56.4%
  triton_mm_3362 0.0519 ms 55.7%
  triton_mm_3348 0.0551 ms 52.5%
  triton_mm_3353 0.0600 ms 48.2%
  triton_mm_3357 0.0627 ms 46.2%
  triton_mm_3347 0.0649 ms 44.6%
SingleProcess AUTOTUNE benchmarking takes 2.0372 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0300 ms 100.0%
  triton_mm_4872 0.0499 ms 60.2%
  triton_mm_4879 0.0504 ms 59.7%
  triton_mm_4870 0.0563 ms 53.4%
  triton_mm_4871 0.0625 ms 48.1%
  triton_mm_4878 0.0671 ms 44.8%
  triton_mm_4875 0.0696 ms 43.2%
  triton_mm_4883 0.0731 ms 41.1%
  triton_mm_4884 0.0738 ms 40.7%
  triton_mm_4877 0.0769 ms 39.1%
SingleProcess AUTOTUNE benchmarking takes 6.2348 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_4 0.0299 ms 100.0%
  triton_mm_3 0.0299 ms 99.8%
  triton_mm_1 0.0300 ms 99.5%
  triton_mm_2 0.0300 ms 99.4%
  triton_mm_7 0.0304 ms 98.1%
  triton_mm_12 0.0307 ms 97.4%
  triton_mm_11 0.0310 ms 96.2%
  triton_mm_9 0.0311 ms 96.1%
  triton_mm_10 0.0312 ms 95.7%
  triton_mm_8 0.0312 ms 95.6%
SingleProcess AUTOTUNE benchmarking takes 2.2494 seconds and 0.0098 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_29 0.0249 ms 100.0%
  triton_mm_21 0.0254 ms 97.9%
  triton_mm_33 0.0254 ms 97.9%
  triton_mm_25 0.0256 ms 97.2%
  triton_mm_24 0.0264 ms 94.3%
  triton_mm_18 0.0264 ms 94.2%
  triton_mm_20 0.0270 ms 92.1%
  triton_mm_28 0.0272 ms 91.3%
  triton_mm_19 0.0280 ms 88.6%
  bias_addmm 0.0283 ms 87.9%
SingleProcess AUTOTUNE benchmarking takes 2.1137 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2233 ms 100.0%
  triton_mm_51 0.2268 ms 98.5%
  triton_mm_52 0.2569 ms 86.9%
  bias_addmm 0.2621 ms 85.2%
  triton_mm_45 0.2640 ms 84.6%
  triton_mm_47 0.2744 ms 81.4%
  triton_mm_43 0.2765 ms 80.8%
  addmm 0.2797 ms 79.8%
  triton_mm_44 0.3086 ms 72.4%
  triton_mm_48 0.3135 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.6229 seconds and 0.0284 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0899 ms 100.0%
  triton_mm_69 0.0915 ms 98.2%
  bias_addmm 0.0966 ms 93.1%
  triton_mm_64 0.0984 ms 91.3%
  triton_mm_66 0.0987 ms 91.1%
  triton_mm_71 0.1010 ms 89.0%
  triton_mm_62 0.1018 ms 88.3%
  addmm 0.1100 ms 81.8%
  triton_mm_63 0.1127 ms 79.8%
  triton_mm_67 0.1127 ms 79.8%
SingleProcess AUTOTUNE benchmarking takes 2.4732 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2796 ms 100.0%
  triton_mm_88 0.2917 ms 95.9%
  triton_mm_89 0.2924 ms 95.6%
  triton_mm_90 0.3316 ms 84.3%
  triton_mm_83 0.3396 ms 82.3%
  triton_mm_81 0.3594 ms 77.8%
  triton_mm_85 0.3618 ms 77.3%
  addmm 0.3630 ms 77.0%
  triton_mm_82 0.3973 ms 70.4%
  triton_mm_86 0.4084 ms 68.5%
SingleProcess AUTOTUNE benchmarking takes 2.5758 seconds and 0.0190 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2890 ms 100.0%
  triton_mm_108 0.3021 ms 95.7%
  triton_mm_107 0.3118 ms 92.7%
  triton_mm_109 0.3221 ms 89.7%
  addmm 0.3243 ms 89.1%
  triton_mm_104 0.3512 ms 82.3%
  triton_mm_102 0.3528 ms 81.9%
  triton_mm_100 0.3666 ms 78.8%
  triton_mm_103 0.3683 ms 78.5%
  triton_mm_105 0.4025 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6386 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_118 0.0249 ms 100.0%
  triton_mm_122 0.0249 ms 99.9%
  triton_mm_126 0.0255 ms 97.6%
  triton_mm_117 0.0256 ms 97.1%
  triton_mm_114 0.0262 ms 95.0%
  triton_mm_111 0.0272 ms 91.3%
  triton_mm_121 0.0272 ms 91.3%
  bias_addmm 0.0276 ms 90.1%
  triton_mm_113 0.0278 ms 89.3%
  triton_mm_112 0.0279 ms 89.0%
SingleProcess AUTOTUNE benchmarking takes 2.1042 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2793 ms 100.0%
  triton_mm_181 0.2893 ms 96.5%
  triton_mm_182 0.2905 ms 96.1%
  triton_mm_183 0.3298 ms 84.7%
  triton_mm_176 0.3346 ms 83.5%
  triton_mm_174 0.3554 ms 78.6%
  triton_mm_178 0.3559 ms 78.5%
  addmm 0.3609 ms 77.4%
  triton_mm_175 0.3939 ms 70.9%
  triton_mm_179 0.4042 ms 69.1%
SingleProcess AUTOTUNE benchmarking takes 2.6296 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2877 ms 100.0%
  triton_mm_201 0.2994 ms 96.1%
  triton_mm_200 0.3099 ms 92.9%
  triton_mm_202 0.3203 ms 89.8%
  addmm 0.3221 ms 89.3%
  triton_mm_197 0.3501 ms 82.2%
  triton_mm_195 0.3510 ms 82.0%
  triton_mm_193 0.3624 ms 79.4%
  triton_mm_196 0.3663 ms 78.5%
  triton_mm_198 0.3999 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 2.6263 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2777 ms 100.0%
  triton_mm_274 0.2881 ms 96.4%
  triton_mm_275 0.2883 ms 96.3%
  triton_mm_276 0.3277 ms 84.7%
  triton_mm_269 0.3333 ms 83.3%
  triton_mm_271 0.3546 ms 78.3%
  triton_mm_267 0.3548 ms 78.3%
  addmm 0.3595 ms 77.3%
  triton_mm_268 0.3924 ms 70.8%
  triton_mm_272 0.4035 ms 68.8%
SingleProcess AUTOTUNE benchmarking takes 2.6381 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2873 ms 100.0%
  triton_mm_294 0.2991 ms 96.1%
  triton_mm_293 0.3092 ms 92.9%
  triton_mm_295 0.3180 ms 90.3%
  addmm 0.3199 ms 89.8%
  triton_mm_288 0.3480 ms 82.6%
  triton_mm_290 0.3493 ms 82.2%
  triton_mm_286 0.3623 ms 79.3%
  triton_mm_289 0.3655 ms 78.6%
  triton_mm_291 0.3991 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 2.6379 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2877 ms 100.0%
  triton_mm_387 0.2992 ms 96.2%
  triton_mm_386 0.3094 ms 93.0%
  triton_mm_388 0.3185 ms 90.3%
  addmm 0.3212 ms 89.6%
  triton_mm_381 0.3479 ms 82.7%
  triton_mm_383 0.3479 ms 82.7%
  triton_mm_379 0.3605 ms 79.8%
  triton_mm_382 0.3652 ms 78.8%
  triton_mm_384 0.3972 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.6367 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2868 ms 100.0%
  triton_mm_480 0.2982 ms 96.2%
  triton_mm_479 0.3085 ms 92.9%
  triton_mm_481 0.3172 ms 90.4%
  addmm 0.3210 ms 89.3%
  triton_mm_474 0.3469 ms 82.7%
  triton_mm_476 0.3485 ms 82.3%
  triton_mm_472 0.3600 ms 79.7%
  triton_mm_475 0.3648 ms 78.6%
  triton_mm_477 0.3977 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 2.6422 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2864 ms 100.0%
  triton_mm_666 0.2973 ms 96.4%
  triton_mm_665 0.3086 ms 92.8%
  triton_mm_667 0.3178 ms 90.1%
  addmm 0.3208 ms 89.3%
  triton_mm_660 0.3462 ms 82.7%
  triton_mm_662 0.3466 ms 82.7%
  triton_mm_658 0.3603 ms 79.5%
  triton_mm_661 0.3638 ms 78.7%
  triton_mm_663 0.3964 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.6368 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2863 ms 100.0%
  triton_mm_759 0.2983 ms 96.0%
  triton_mm_758 0.3083 ms 92.9%
  triton_mm_760 0.3170 ms 90.3%
  addmm 0.3201 ms 89.4%
  triton_mm_755 0.3464 ms 82.6%
  triton_mm_753 0.3475 ms 82.4%
  triton_mm_751 0.3599 ms 79.5%
  triton_mm_754 0.3636 ms 78.7%
  triton_mm_756 0.3960 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.6421 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0144 ms 100.0%
  triton_mm_1610 0.0153 ms 93.9%
  triton_mm_1606 0.0156 ms 92.6%
  triton_mm_1614 0.0162 ms 88.8%
  mm 0.0164 ms 87.7%
  triton_mm_1605 0.0175 ms 82.3%
  triton_mm_1600 0.0177 ms 81.5%
  triton_mm_1601 0.0180 ms 79.8%
  triton_mm_1599 0.0184 ms 78.3%
  triton_mm_1609 0.0201 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 7.3607 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5427 ms 100.0%
  triton_mm_1632 0.5428 ms 100.0%
  triton_mm_1631 0.5472 ms 99.2%
  triton_mm_1633 0.6172 ms 87.9%
  triton_mm_1626 0.6401 ms 84.8%
  triton_mm_1628 0.6752 ms 80.4%
  addmm 0.6804 ms 79.8%
  triton_mm_1624 0.6927 ms 78.3%
  triton_mm_1629 0.7628 ms 71.1%
  triton_mm_1625 0.7655 ms 70.9%
SingleProcess AUTOTUNE benchmarking takes 11.3982 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.5170 ms 100.0%
  triton_mm_1669 0.5421 ms 95.4%
  triton_mm_1670 0.5602 ms 92.3%
  triton_mm_1671 0.5832 ms 88.6%
  triton_mm_1664 0.6571 ms 78.7%
  triton_mm_1666 0.6621 ms 78.1%
  triton_mm_1662 0.6637 ms 77.9%
  triton_mm_1665 0.7105 ms 72.8%
  triton_mm_1667 0.7118 ms 72.6%
  triton_mm_1663 0.7255 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 12.4285 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2842 ms 100.0%
  triton_mm_1742 0.2892 ms 98.3%
  triton_mm_1741 0.2920 ms 97.3%
  triton_mm_1743 0.2941 ms 96.6%
  triton_mm_1736 0.3448 ms 82.4%
  triton_mm_1734 0.3479 ms 81.7%
  triton_mm_1738 0.3552 ms 80.0%
  triton_mm_1737 0.3714 ms 76.5%
  triton_mm_1739 0.3922 ms 72.4%
  triton_mm_1735 0.3967 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 9.8626 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1696 0.0116 ms 100.0%
  triton_mm_1694 0.0118 ms 98.4%
  triton_mm_1699 0.0118 ms 98.4%
  triton_mm_1702 0.0119 ms 97.8%
  triton_mm_1693 0.0123 ms 94.8%
  triton_mm_1704 0.0123 ms 94.8%
  triton_mm_1691 0.0125 ms 93.1%
  triton_mm_1697 0.0125 ms 93.0%
  triton_mm_1698 0.0125 ms 92.7%
  triton_mm_1695 0.0126 ms 92.1%
SingleProcess AUTOTUNE benchmarking takes 5.8650 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0157 ms 100.0%
  triton_mm_1680 0.0165 ms 95.2%
  mm 0.0182 ms 86.1%
  triton_mm_1684 0.0202 ms 77.8%
  triton_mm_1688 0.0225 ms 69.7%
  triton_mm_1675 0.0228 ms 68.9%
  triton_mm_1674 0.0241 ms 65.2%
  triton_mm_1679 0.0257 ms 61.2%
  triton_mm_1673 0.0262 ms 59.9%
  triton_mm_1683 0.0263 ms 59.7%
SingleProcess AUTOTUNE benchmarking takes 7.7788 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5277 ms 100.0%
  triton_mm_1650 0.5555 ms 95.0%
  triton_mm_1651 0.5634 ms 93.7%
  triton_mm_1652 0.5795 ms 91.1%
  triton_mm_1645 0.6474 ms 81.5%
  triton_mm_1647 0.6492 ms 81.3%
  triton_mm_1643 0.6565 ms 80.4%
  triton_mm_1646 0.6818 ms 77.4%
  triton_mm_1644 0.7072 ms 74.6%
  triton_mm_1648 0.7192 ms 73.4%
SingleProcess AUTOTUNE benchmarking takes 9.8497 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2705 ms 100.0%
  triton_mm_1723 0.2728 ms 99.1%
  mm 0.2733 ms 99.0%
  triton_mm_1724 0.3093 ms 87.4%
  triton_mm_1715 0.3318 ms 81.5%
  triton_mm_1717 0.3350 ms 80.7%
  triton_mm_1719 0.3383 ms 80.0%
  triton_mm_1716 0.3554 ms 76.1%
  triton_mm_1720 0.3783 ms 71.5%
  triton_mm_1718 0.4184 ms 64.7%
SingleProcess AUTOTUNE benchmarking takes 10.3641 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2191 ms 100.0%
  triton_mm_1837 0.2192 ms 100.0%
  triton_mm_1836 0.2254 ms 97.2%
  triton_mm_1838 0.2372 ms 92.4%
  triton_mm_1833 0.2515 ms 87.1%
  triton_mm_1831 0.2559 ms 85.6%
  triton_mm_1829 0.2560 ms 85.6%
  triton_mm_1832 0.2823 ms 77.6%
  triton_mm_1830 0.2848 ms 77.0%
  triton_mm_1834 0.2915 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 9.7930 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2844 ms 100.0%
  mm 0.2855 ms 99.6%
  triton_mm_1780 0.2877 ms 98.8%
  triton_mm_1781 0.2930 ms 97.1%
  triton_mm_1776 0.3387 ms 84.0%
  triton_mm_1772 0.3413 ms 83.3%
  triton_mm_1774 0.3458 ms 82.2%
  triton_mm_1775 0.3756 ms 75.7%
  triton_mm_1777 0.3843 ms 74.0%
  triton_mm_1773 0.3886 ms 73.2%
SingleProcess AUTOTUNE benchmarking takes 10.2096 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2188 ms 100.0%
  triton_mm_1855 0.2751 ms 79.5%
  triton_mm_1850 0.2766 ms 79.1%
  triton_mm_1852 0.2778 ms 78.7%
  triton_mm_1848 0.2798 ms 78.2%
  triton_mm_1856 0.2811 ms 77.8%
  triton_mm_1857 0.2839 ms 77.0%
  triton_mm_1851 0.3064 ms 71.4%
  triton_mm_1853 0.3191 ms 68.6%
  triton_mm_1849 0.3244 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 13.3247 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0998 ms 100.0%
  mm 0.1008 ms 99.0%
  triton_mm_1812 0.1052 ms 94.9%
  triton_mm_1818 0.1083 ms 92.2%
  triton_mm_1809 0.1177 ms 84.8%
  triton_mm_1810 0.1190 ms 83.9%
  triton_mm_1814 0.1204 ms 83.0%
  triton_mm_1817 0.1220 ms 81.8%
  triton_mm_1813 0.1272 ms 78.5%
  triton_mm_1815 0.1312 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.3913 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  triton_mm_1760 0.2957 ms 100.0%
  mm 0.2971 ms 99.5%
  triton_mm_1761 0.3040 ms 97.3%
  triton_mm_1762 0.3134 ms 94.4%
  triton_mm_1757 0.3363 ms 87.9%
  triton_mm_1753 0.3400 ms 87.0%
  triton_mm_1755 0.3404 ms 86.9%
  triton_mm_1756 0.3602 ms 82.1%
  triton_mm_1754 0.3766 ms 78.5%
  triton_mm_1758 0.3863 ms 76.6%
SingleProcess AUTOTUNE benchmarking takes 2.5178 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0830 ms 100.0%
  triton_mm_1799 0.0844 ms 98.4%
  triton_mm_1798 0.0849 ms 97.7%
  triton_mm_1795 0.0917 ms 90.4%
  triton_mm_1791 0.0939 ms 88.3%
  triton_mm_1793 0.0945 ms 87.8%
  triton_mm_1800 0.0950 ms 87.3%
  triton_mm_1792 0.1013 ms 81.9%
  triton_mm_1796 0.1057 ms 78.5%
  triton_mm_1789 0.1243 ms 66.7%
SingleProcess AUTOTUNE benchmarking takes 2.3768 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2708 ms 100.0%
  mm 0.2725 ms 99.3%
  triton_mm_1909 0.2726 ms 99.3%
  triton_mm_1910 0.3096 ms 87.4%
  triton_mm_1901 0.3316 ms 81.7%
  triton_mm_1903 0.3332 ms 81.2%
  triton_mm_1905 0.3385 ms 80.0%
  triton_mm_1902 0.3546 ms 76.4%
  triton_mm_1906 0.3780 ms 71.6%
  triton_mm_1904 0.4176 ms 64.8%
SingleProcess AUTOTUNE benchmarking takes 2.5121 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2941 ms 100.0%
  triton_mm_1946 0.2959 ms 99.4%
  triton_mm_1947 0.3044 ms 96.6%
  triton_mm_1948 0.3133 ms 93.9%
  triton_mm_1943 0.3355 ms 87.7%
  triton_mm_1939 0.3412 ms 86.2%
  triton_mm_1941 0.3415 ms 86.1%
  triton_mm_1942 0.3599 ms 81.7%
  triton_mm_1940 0.3776 ms 77.9%
  triton_mm_1944 0.3866 ms 76.1%
SingleProcess AUTOTUNE benchmarking takes 2.5163 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1885 0.0188 ms 100.0%
  triton_mm_1883 0.0191 ms 98.7%
  triton_mm_1881 0.0191 ms 98.3%
  triton_mm_1884 0.0192 ms 98.0%
  triton_mm_1888 0.0195 ms 96.6%
  triton_mm_1882 0.0195 ms 96.5%
  triton_mm_1880 0.0195 ms 96.4%
  triton_mm_1889 0.0198 ms 94.8%
  triton_mm_1891 0.0198 ms 94.8%
  triton_mm_1887 0.0199 ms 94.5%
SingleProcess AUTOTUNE benchmarking takes 5.7667 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2832 ms 100.0%
  triton_mm_1928 0.2892 ms 97.9%
  triton_mm_1927 0.2928 ms 96.7%
  triton_mm_1929 0.2943 ms 96.2%
  triton_mm_1922 0.3452 ms 82.0%
  triton_mm_1920 0.3493 ms 81.1%
  triton_mm_1924 0.3567 ms 79.4%
  triton_mm_1923 0.3728 ms 76.0%
  triton_mm_1925 0.3930 ms 72.1%
  triton_mm_1921 0.3980 ms 71.1%
SingleProcess AUTOTUNE benchmarking takes 2.5119 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2848 ms 100.0%
  mm 0.2850 ms 99.9%
  triton_mm_1966 0.2885 ms 98.7%
  triton_mm_1967 0.2943 ms 96.8%
  triton_mm_1962 0.3405 ms 83.6%
  triton_mm_1958 0.3464 ms 82.2%
  triton_mm_1960 0.3500 ms 81.4%
  triton_mm_1961 0.3772 ms 75.5%
  triton_mm_1963 0.3848 ms 74.0%
  triton_mm_1959 0.3915 ms 72.7%
SingleProcess AUTOTUNE benchmarking takes 2.5223 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0290 ms 100.0%
  mm 0.0291 ms 99.6%
  triton_mm_1866 0.0317 ms 91.4%
  triton_mm_1870 0.0406 ms 71.4%
  triton_mm_1874 0.0508 ms 57.0%
  triton_mm_1861 0.0511 ms 56.7%
  triton_mm_1860 0.0552 ms 52.5%
  triton_mm_1865 0.0595 ms 48.7%
  triton_mm_1869 0.0622 ms 46.6%
  triton_mm_1859 0.0653 ms 44.4%
SingleProcess AUTOTUNE benchmarking takes 6.6205 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0838 ms 100.0%
  triton_mm_1985 0.0843 ms 99.4%
  triton_mm_1984 0.0851 ms 98.5%
  triton_mm_1981 0.0918 ms 91.3%
  triton_mm_1977 0.0938 ms 89.3%
  triton_mm_1986 0.0943 ms 88.8%
  triton_mm_1979 0.0949 ms 88.2%
  triton_mm_1978 0.1014 ms 82.6%
  triton_mm_1982 0.1057 ms 79.2%
  triton_mm_1975 0.1238 ms 67.7%
SingleProcess AUTOTUNE benchmarking takes 2.3705 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2703 ms 100.0%
  triton_mm_2094 0.2720 ms 99.4%
  triton_mm_2095 0.2731 ms 99.0%
  triton_mm_2096 0.3101 ms 87.2%
  triton_mm_2087 0.3319 ms 81.4%
  triton_mm_2089 0.3346 ms 80.8%
  triton_mm_2091 0.3393 ms 79.7%
  triton_mm_2088 0.3562 ms 75.9%
  triton_mm_2092 0.3781 ms 71.5%
  triton_mm_2090 0.4177 ms 64.7%
SingleProcess AUTOTUNE benchmarking takes 2.5070 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  triton_mm_2132 0.2969 ms 100.0%
  mm 0.2972 ms 99.9%
  triton_mm_2133 0.3040 ms 97.7%
  triton_mm_2134 0.3134 ms 94.8%
  triton_mm_2129 0.3371 ms 88.1%
  triton_mm_2127 0.3409 ms 87.1%
  triton_mm_2125 0.3424 ms 86.7%
  triton_mm_2128 0.3619 ms 82.1%
  triton_mm_2126 0.3783 ms 78.5%
  triton_mm_2130 0.3873 ms 76.7%
SingleProcess AUTOTUNE benchmarking takes 2.5144 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2067 0.0183 ms 100.0%
  triton_mm_2074 0.0186 ms 98.8%
  triton_mm_2068 0.0186 ms 98.5%
  triton_mm_2069 0.0191 ms 96.0%
  triton_mm_2070 0.0192 ms 95.5%
  triton_mm_2071 0.0198 ms 92.7%
  triton_mm_2075 0.0198 ms 92.6%
  triton_mm_2077 0.0198 ms 92.6%
  triton_mm_2073 0.0199 ms 92.0%
  triton_mm_2072 0.0200 ms 91.7%
SingleProcess AUTOTUNE benchmarking takes 2.0071 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2845 ms 100.0%
  triton_mm_2114 0.2900 ms 98.1%
  triton_mm_2113 0.2942 ms 96.7%
  triton_mm_2115 0.2953 ms 96.4%
  triton_mm_2108 0.3466 ms 82.1%
  triton_mm_2106 0.3505 ms 81.2%
  triton_mm_2110 0.3571 ms 79.7%
  triton_mm_2109 0.3740 ms 76.1%
  triton_mm_2111 0.3936 ms 72.3%
  triton_mm_2107 0.3994 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.5155 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2151 0.2851 ms 100.0%
  mm 0.2856 ms 99.8%
  triton_mm_2152 0.2883 ms 98.9%
  triton_mm_2153 0.2945 ms 96.8%
  triton_mm_2148 0.3411 ms 83.6%
  triton_mm_2144 0.3471 ms 82.1%
  triton_mm_2146 0.3514 ms 81.2%
  triton_mm_2147 0.3778 ms 75.5%
  triton_mm_2149 0.3865 ms 73.8%
  triton_mm_2145 0.3934 ms 72.5%
SingleProcess AUTOTUNE benchmarking takes 2.5125 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2048 0.0283 ms 100.0%
  mm 0.0291 ms 97.1%
  triton_mm_2052 0.0309 ms 91.5%
  triton_mm_2056 0.0411 ms 68.9%
  triton_mm_2047 0.0511 ms 55.4%
  triton_mm_2060 0.0518 ms 54.6%
  triton_mm_2046 0.0552 ms 51.2%
  triton_mm_2051 0.0602 ms 47.0%
  triton_mm_2055 0.0629 ms 45.0%
  triton_mm_2045 0.0647 ms 43.7%
SingleProcess AUTOTUNE benchmarking takes 2.0319 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0839 ms 100.0%
  triton_mm_2171 0.0843 ms 99.5%
  triton_mm_2170 0.0859 ms 97.7%
  triton_mm_2167 0.0918 ms 91.4%
  triton_mm_2163 0.0946 ms 88.7%
  triton_mm_2172 0.0950 ms 88.3%
  triton_mm_2165 0.0954 ms 87.9%
  triton_mm_2164 0.1022 ms 82.1%
  triton_mm_2168 0.1050 ms 79.9%
  triton_mm_2161 0.1238 ms 67.7%
SingleProcess AUTOTUNE benchmarking takes 2.3664 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2234 0.0290 ms 100.0%
  mm 0.0291 ms 99.7%
  triton_mm_2238 0.0309 ms 93.7%
  triton_mm_2242 0.0411 ms 70.5%
  triton_mm_2233 0.0511 ms 56.6%
  triton_mm_2246 0.0516 ms 56.1%
  triton_mm_2232 0.0559 ms 51.8%
  triton_mm_2237 0.0595 ms 48.7%
  triton_mm_2241 0.0629 ms 46.0%
  triton_mm_2231 0.0653 ms 44.3%
SingleProcess AUTOTUNE benchmarking takes 2.9576 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0836 ms 100.0%
  triton_mm_2357 0.0843 ms 99.2%
  triton_mm_2356 0.0851 ms 98.3%
  triton_mm_2353 0.0918 ms 91.1%
  triton_mm_2349 0.0938 ms 89.2%
  triton_mm_2351 0.0946 ms 88.5%
  triton_mm_2358 0.0953 ms 87.8%
  triton_mm_2350 0.1014 ms 82.5%
  triton_mm_2354 0.1057 ms 79.2%
  triton_mm_2347 0.1237 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.3857 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2420 0.0283 ms 100.0%
  mm 0.0291 ms 97.2%
  triton_mm_2424 0.0316 ms 89.3%
  triton_mm_2428 0.0409 ms 69.1%
  triton_mm_2432 0.0509 ms 55.5%
  triton_mm_2419 0.0518 ms 54.6%
  triton_mm_2418 0.0559 ms 50.6%
  triton_mm_2423 0.0603 ms 46.9%
  triton_mm_2427 0.0630 ms 44.9%
  triton_mm_2417 0.0646 ms 43.7%
SingleProcess AUTOTUNE benchmarking takes 2.0533 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0832 ms 100.0%
  triton_mm_2543 0.0846 ms 98.3%
  triton_mm_2542 0.0859 ms 96.9%
  triton_mm_2539 0.0925 ms 89.9%
  triton_mm_2535 0.0946 ms 88.0%
  triton_mm_2544 0.0950 ms 87.5%
  triton_mm_2537 0.0956 ms 87.0%
  triton_mm_2536 0.1021 ms 81.5%
  triton_mm_2540 0.1050 ms 79.2%
  triton_mm_2538 0.1235 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 2.3706 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2606 0.0283 ms 100.0%
  mm 0.0291 ms 97.4%
  triton_mm_2610 0.0309 ms 91.7%
  triton_mm_2614 0.0408 ms 69.5%
  triton_mm_2618 0.0508 ms 55.7%
  triton_mm_2605 0.0511 ms 55.4%
  triton_mm_2604 0.0552 ms 51.3%
  triton_mm_2609 0.0595 ms 47.6%
  triton_mm_2613 0.0628 ms 45.1%
  triton_mm_2603 0.0647 ms 43.8%
SingleProcess AUTOTUNE benchmarking takes 2.0523 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0833 ms 100.0%
  triton_mm_2729 0.0843 ms 98.8%
  triton_mm_2728 0.0858 ms 97.0%
  triton_mm_2725 0.0926 ms 89.9%
  triton_mm_2721 0.0939 ms 88.7%
  triton_mm_2723 0.0946 ms 88.0%
  triton_mm_2730 0.0953 ms 87.4%
  triton_mm_2722 0.1015 ms 82.1%
  triton_mm_2726 0.1050 ms 79.3%
  triton_mm_2724 0.1240 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 2.3829 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2792 0.0290 ms 100.0%
  mm 0.0291 ms 99.8%
  triton_mm_2796 0.0309 ms 93.9%
  triton_mm_2800 0.0409 ms 70.9%
  triton_mm_2804 0.0516 ms 56.2%
  triton_mm_2791 0.0517 ms 56.0%
  triton_mm_2790 0.0558 ms 51.9%
  triton_mm_2795 0.0601 ms 48.2%
  triton_mm_2799 0.0629 ms 46.1%
  triton_mm_2789 0.0654 ms 44.3%
SingleProcess AUTOTUNE benchmarking takes 2.0491 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0301 ms 100.0%
  triton_mm_4879 0.0498 ms 60.4%
  triton_mm_4872 0.0500 ms 60.1%
  triton_mm_4870 0.0560 ms 53.7%
  triton_mm_4871 0.0636 ms 47.3%
  triton_mm_4878 0.0672 ms 44.7%
  triton_mm_4875 0.0698 ms 43.1%
  triton_mm_4884 0.0732 ms 41.1%
  triton_mm_4883 0.0744 ms 40.4%
  triton_mm_4877 0.0767 ms 39.2%
SingleProcess AUTOTUNE benchmarking takes 6.5658 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_1 0.0300 ms 100.0%
  triton_mm_3 0.0302 ms 99.2%
  triton_mm_2 0.0305 ms 98.4%
  triton_mm_4 0.0310 ms 96.6%
  triton_mm_7 0.0311 ms 96.4%
  triton_mm_12 0.0316 ms 94.7%
  triton_mm_5 0.0318 ms 94.4%
  triton_mm_10 0.0318 ms 94.3%
  triton_mm_11 0.0320 ms 93.6%
  triton_mm_9 0.0321 ms 93.5%
SingleProcess AUTOTUNE benchmarking takes 2.1013 seconds and 0.0087 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_25 0.0247 ms 100.0%
  triton_mm_29 0.0248 ms 99.5%
  triton_mm_21 0.0252 ms 98.0%
  triton_mm_33 0.0253 ms 97.6%
  triton_mm_24 0.0255 ms 96.9%
  triton_mm_18 0.0260 ms 94.7%
  triton_mm_28 0.0263 ms 93.9%
  triton_mm_20 0.0270 ms 91.4%
  bias_addmm 0.0274 ms 90.1%
  triton_mm_19 0.0279 ms 88.6%
SingleProcess AUTOTUNE benchmarking takes 2.1097 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2139 ms 100.0%
  triton_mm_51 0.2201 ms 97.2%
  triton_mm_52 0.2512 ms 85.2%
  bias_addmm 0.2524 ms 84.7%
  triton_mm_45 0.2594 ms 82.5%
  triton_mm_47 0.2646 ms 80.8%
  triton_mm_43 0.2672 ms 80.0%
  addmm 0.2709 ms 78.9%
  triton_mm_44 0.2997 ms 71.3%
  triton_mm_48 0.3061 ms 69.9%
SingleProcess AUTOTUNE benchmarking takes 2.5625 seconds and 0.0325 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0896 ms 100.0%
  triton_mm_69 0.0909 ms 98.6%
  bias_addmm 0.0972 ms 92.2%
  triton_mm_64 0.0979 ms 91.6%
  triton_mm_66 0.0981 ms 91.3%
  triton_mm_71 0.1002 ms 89.4%
  triton_mm_62 0.1010 ms 88.8%
  addmm 0.1096 ms 81.8%
  triton_mm_63 0.1111 ms 80.7%
  triton_mm_67 0.1125 ms 79.7%
SingleProcess AUTOTUNE benchmarking takes 2.4643 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2709 ms 100.0%
  triton_mm_88 0.2843 ms 95.3%
  triton_mm_89 0.2888 ms 93.8%
  triton_mm_83 0.3299 ms 82.1%
  triton_mm_90 0.3302 ms 82.1%
  triton_mm_81 0.3515 ms 77.1%
  triton_mm_85 0.3544 ms 76.4%
  addmm 0.3550 ms 76.3%
  triton_mm_82 0.3900 ms 69.5%
  triton_mm_86 0.4013 ms 67.5%
SingleProcess AUTOTUNE benchmarking takes 2.6449 seconds and 0.0090 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2794 ms 100.0%
  triton_mm_108 0.2952 ms 94.6%
  triton_mm_107 0.3040 ms 91.9%
  addmm 0.3122 ms 89.5%
  triton_mm_109 0.3136 ms 89.1%
  triton_mm_104 0.3446 ms 81.1%
  triton_mm_102 0.3453 ms 80.9%
  triton_mm_100 0.3570 ms 78.3%
  triton_mm_103 0.3612 ms 77.4%
  triton_mm_105 0.3975 ms 70.3%
SingleProcess AUTOTUNE benchmarking takes 2.6329 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_126 0.0244 ms 100.0%
  triton_mm_118 0.0247 ms 99.0%
  triton_mm_114 0.0252 ms 97.0%
  triton_mm_117 0.0255 ms 96.0%
  triton_mm_122 0.0259 ms 94.3%
  triton_mm_121 0.0263 ms 93.1%
  triton_mm_111 0.0269 ms 90.8%
  triton_mm_112 0.0270 ms 90.6%
  triton_mm_113 0.0279 ms 87.5%
  bias_addmm 0.0284 ms 86.2%
SingleProcess AUTOTUNE benchmarking takes 2.1212 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_143 0.2131 ms 100.0%
  triton_mm_144 0.2192 ms 97.2%
  triton_mm_145 0.2507 ms 85.0%
  bias_addmm 0.2527 ms 84.3%
  triton_mm_138 0.2547 ms 83.7%
  triton_mm_140 0.2630 ms 81.0%
  triton_mm_136 0.2664 ms 80.0%
  addmm 0.2682 ms 79.5%
  triton_mm_137 0.2996 ms 71.1%
  triton_mm_141 0.3029 ms 70.4%
SingleProcess AUTOTUNE benchmarking takes 2.5892 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_163 0.0895 ms 100.0%
  triton_mm_162 0.0915 ms 97.8%
  bias_addmm 0.0969 ms 92.4%
  triton_mm_157 0.0977 ms 91.6%
  triton_mm_159 0.0979 ms 91.4%
  triton_mm_164 0.1009 ms 88.7%
  triton_mm_155 0.1018 ms 88.0%
  addmm 0.1094 ms 81.8%
  triton_mm_156 0.1110 ms 80.6%
  triton_mm_160 0.1124 ms 79.7%
SingleProcess AUTOTUNE benchmarking takes 2.4763 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  bias_addmm 0.2712 ms 100.0%
  triton_mm_181 0.2840 ms 95.5%
  triton_mm_182 0.2872 ms 94.4%
  triton_mm_183 0.3290 ms 82.4%
  triton_mm_176 0.3335 ms 81.3%
  triton_mm_178 0.3540 ms 76.6%
  triton_mm_174 0.3556 ms 76.3%
  addmm 0.3601 ms 75.3%
  triton_mm_175 0.3939 ms 68.8%
  triton_mm_179 0.4051 ms 66.9%
SingleProcess AUTOTUNE benchmarking takes 2.6316 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2820 ms 100.0%
  triton_mm_201 0.2966 ms 95.1%
  triton_mm_200 0.3052 ms 92.4%
  addmm 0.3155 ms 89.4%
  triton_mm_202 0.3165 ms 89.1%
  triton_mm_197 0.3456 ms 81.6%
  triton_mm_195 0.3471 ms 81.2%
  triton_mm_193 0.3576 ms 78.9%
  triton_mm_196 0.3612 ms 78.1%
  triton_mm_198 0.3961 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 2.6401 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_211 0.0247 ms 100.0%
  triton_mm_207 0.0252 ms 98.1%
  triton_mm_219 0.0252 ms 97.8%
  triton_mm_210 0.0254 ms 97.1%
  triton_mm_215 0.0257 ms 96.2%
  triton_mm_204 0.0260 ms 95.0%
  triton_mm_214 0.0270 ms 91.5%
  triton_mm_206 0.0270 ms 91.4%
  triton_mm_205 0.0279 ms 88.5%
  bias_addmm 0.0283 ms 87.4%
SingleProcess AUTOTUNE benchmarking takes 2.0863 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2793 ms 100.0%
  triton_mm_294 0.2948 ms 94.7%
  triton_mm_293 0.3041 ms 91.8%
  addmm 0.3125 ms 89.4%
  triton_mm_295 0.3138 ms 89.0%
  triton_mm_288 0.3440 ms 81.2%
  triton_mm_290 0.3478 ms 80.3%
  triton_mm_286 0.3576 ms 78.1%
  triton_mm_289 0.3633 ms 76.9%
  triton_mm_291 0.3964 ms 70.5%
SingleProcess AUTOTUNE benchmarking takes 2.6320 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_300 0.0252 ms 100.0%
  triton_mm_312 0.0252 ms 99.7%
  triton_mm_308 0.0255 ms 98.6%
  triton_mm_304 0.0256 ms 98.3%
  triton_mm_297 0.0260 ms 96.8%
  triton_mm_303 0.0262 ms 96.2%
  triton_mm_299 0.0270 ms 93.2%
  triton_mm_307 0.0272 ms 92.7%
  triton_mm_298 0.0280 ms 90.0%
  bias_addmm 0.0283 ms 89.1%
SingleProcess AUTOTUNE benchmarking takes 2.0994 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2794 ms 100.0%
  triton_mm_387 0.2942 ms 95.0%
  triton_mm_386 0.3060 ms 91.3%
  addmm 0.3151 ms 88.7%
  triton_mm_388 0.3165 ms 88.3%
  triton_mm_383 0.3446 ms 81.1%
  triton_mm_381 0.3452 ms 81.0%
  triton_mm_382 0.3614 ms 77.3%
  triton_mm_379 0.3643 ms 76.7%
  triton_mm_384 0.3958 ms 70.6%
SingleProcess AUTOTUNE benchmarking takes 2.6416 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_405 0.0244 ms 100.0%
  triton_mm_397 0.0247 ms 98.8%
  triton_mm_401 0.0248 ms 98.3%
  triton_mm_396 0.0255 ms 95.9%
  triton_mm_393 0.0260 ms 94.1%
  triton_mm_400 0.0263 ms 92.8%
  triton_mm_390 0.0269 ms 90.7%
  triton_mm_391 0.0270 ms 90.5%
  triton_mm_392 0.0270 ms 90.4%
  bias_addmm 0.0273 ms 89.3%
SingleProcess AUTOTUNE benchmarking takes 2.0996 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_498 0.0244 ms 100.0%
  triton_mm_486 0.0252 ms 97.0%
  triton_mm_489 0.0255 ms 96.0%
  triton_mm_490 0.0255 ms 95.9%
  triton_mm_494 0.0258 ms 94.7%
  triton_mm_493 0.0263 ms 93.1%
  triton_mm_483 0.0270 ms 90.5%
  bias_addmm 0.0274 ms 89.4%
  triton_mm_484 0.0280 ms 87.4%
  triton_mm_485 0.0281 ms 87.1%
SingleProcess AUTOTUNE benchmarking takes 2.1057 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_591 0.0244 ms 100.0%
  triton_mm_583 0.0247 ms 99.0%
  triton_mm_579 0.0252 ms 97.0%
  triton_mm_582 0.0255 ms 96.0%
  triton_mm_587 0.0259 ms 94.6%
  triton_mm_576 0.0260 ms 94.1%
  triton_mm_578 0.0270 ms 90.5%
  triton_mm_586 0.0270 ms 90.5%
  triton_mm_577 0.0280 ms 87.4%
  bias_addmm 0.0285 ms 85.7%
SingleProcess AUTOTUNE benchmarking takes 2.1202 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_684 0.0244 ms 100.0%
  triton_mm_680 0.0256 ms 95.3%
  triton_mm_676 0.0257 ms 95.2%
  triton_mm_672 0.0263 ms 93.0%
  triton_mm_675 0.0265 ms 92.3%
  triton_mm_669 0.0269 ms 90.8%
  triton_mm_670 0.0270 ms 90.5%
  triton_mm_671 0.0270 ms 90.4%
  triton_mm_679 0.0271 ms 90.2%
  bias_addmm 0.0281 ms 86.9%
SingleProcess AUTOTUNE benchmarking takes 2.1125 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_769 0.0247 ms 100.0%
  triton_mm_765 0.0252 ms 98.1%
  triton_mm_777 0.0253 ms 97.5%
  triton_mm_773 0.0257 ms 96.0%
  triton_mm_762 0.0260 ms 95.0%
  triton_mm_768 0.0264 ms 93.6%
  triton_mm_764 0.0270 ms 91.4%
  triton_mm_772 0.0273 ms 90.5%
  triton_mm_763 0.0279 ms 88.6%
  bias_addmm 0.0280 ms 88.3%
SingleProcess AUTOTUNE benchmarking takes 2.1000 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_866 0.0248 ms 100.0%
  triton_mm_861 0.0254 ms 97.6%
  triton_mm_870 0.0255 ms 97.5%
  triton_mm_862 0.0258 ms 96.4%
  triton_mm_858 0.0262 ms 94.7%
  triton_mm_856 0.0270 ms 92.1%
  triton_mm_855 0.0270 ms 92.0%
  triton_mm_857 0.0270 ms 91.8%
  triton_mm_865 0.0273 ms 91.1%
  bias_addmm 0.0285 ms 87.2%
SingleProcess AUTOTUNE benchmarking takes 2.1216 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1606 0.0149 ms 100.0%
  triton_mm_1602 0.0152 ms 98.2%
  mm 0.0155 ms 96.2%
  triton_mm_1610 0.0166 ms 89.9%
  triton_mm_1614 0.0174 ms 85.6%
  triton_mm_1605 0.0178 ms 83.8%
  triton_mm_1601 0.0180 ms 83.0%
  triton_mm_1600 0.0188 ms 79.6%
  triton_mm_1599 0.0190 ms 78.7%
  triton_mm_1612 0.0198 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 6.9927 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1631 0.5418 ms 100.0%
  bias_addmm 0.5425 ms 99.9%
  triton_mm_1632 0.5441 ms 99.6%
  triton_mm_1633 0.6204 ms 87.3%
  triton_mm_1626 0.6341 ms 85.4%
  triton_mm_1628 0.6728 ms 80.5%
  addmm 0.6782 ms 79.9%
  triton_mm_1624 0.6957 ms 77.9%
  triton_mm_1625 0.7646 ms 70.9%
  triton_mm_1629 0.7658 ms 70.8%
SingleProcess AUTOTUNE benchmarking takes 11.5397 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.5034 ms 100.0%
  triton_mm_1669 0.5261 ms 95.7%
  triton_mm_1670 0.5434 ms 92.6%
  triton_mm_1671 0.5744 ms 87.6%
  triton_mm_1666 0.6505 ms 77.4%
  triton_mm_1664 0.6525 ms 77.1%
  triton_mm_1662 0.6537 ms 77.0%
  triton_mm_1663 0.6895 ms 73.0%
  triton_mm_1667 0.7010 ms 71.8%
  triton_mm_1665 0.7064 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 9.8234 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2766 ms 100.0%
  triton_mm_1742 0.2815 ms 98.3%
  triton_mm_1741 0.2828 ms 97.8%
  triton_mm_1743 0.2835 ms 97.6%
  triton_mm_1736 0.3322 ms 83.3%
  triton_mm_1734 0.3371 ms 82.1%
  triton_mm_1738 0.3449 ms 80.2%
  triton_mm_1737 0.3642 ms 75.9%
  triton_mm_1739 0.3829 ms 72.2%
  triton_mm_1735 0.3853 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 10.0973 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1695 0.0119 ms 100.0%
  triton_mm_1697 0.0119 ms 100.0%
  triton_mm_1698 0.0119 ms 99.7%
  triton_mm_1701 0.0120 ms 98.5%
  triton_mm_1692 0.0126 ms 93.9%
  triton_mm_1703 0.0128 ms 93.0%
  triton_mm_1702 0.0129 ms 92.3%
  triton_mm_1694 0.0130 ms 91.6%
  triton_mm_1696 0.0130 ms 91.4%
  triton_mm_1700 0.0130 ms 91.3%
SingleProcess AUTOTUNE benchmarking takes 2.0158 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1680 0.0166 ms 100.0%
  triton_mm_1676 0.0171 ms 97.0%
  mm 0.0183 ms 90.9%
  triton_mm_1684 0.0201 ms 82.8%
  triton_mm_1675 0.0223 ms 74.5%
  triton_mm_1688 0.0225 ms 73.7%
  triton_mm_1674 0.0236 ms 70.2%
  triton_mm_1679 0.0252 ms 66.0%
  triton_mm_1683 0.0268 ms 61.9%
  triton_mm_1673 0.0271 ms 61.3%
SingleProcess AUTOTUNE benchmarking takes 2.0460 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5243 ms 100.0%
  triton_mm_1650 0.5523 ms 94.9%
  triton_mm_1651 0.5659 ms 92.6%
  triton_mm_1652 0.5788 ms 90.6%
  triton_mm_1645 0.6504 ms 80.6%
  triton_mm_1647 0.6563 ms 79.9%
  triton_mm_1643 0.6644 ms 78.9%
  triton_mm_1646 0.6908 ms 75.9%
  triton_mm_1644 0.7170 ms 73.1%
  triton_mm_1648 0.7214 ms 72.7%
SingleProcess AUTOTUNE benchmarking takes 2.5953 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2681 ms 100.0%
  mm 0.2709 ms 99.0%
  triton_mm_1723 0.2745 ms 97.6%
  triton_mm_1724 0.3127 ms 85.7%
  triton_mm_1717 0.3348 ms 80.1%
  triton_mm_1715 0.3366 ms 79.6%
  triton_mm_1719 0.3405 ms 78.7%
  triton_mm_1716 0.3572 ms 75.1%
  triton_mm_1720 0.3799 ms 70.6%
  triton_mm_1718 0.4209 ms 63.7%
SingleProcess AUTOTUNE benchmarking takes 2.5046 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2128 ms 100.0%
  triton_mm_1837 0.2131 ms 99.9%
  triton_mm_1836 0.2198 ms 96.8%
  triton_mm_1838 0.2317 ms 91.8%
  triton_mm_1833 0.2445 ms 87.0%
  triton_mm_1829 0.2482 ms 85.7%
  triton_mm_1831 0.2485 ms 85.6%
  triton_mm_1830 0.2787 ms 76.3%
  triton_mm_1832 0.2817 ms 75.6%
  triton_mm_1834 0.2857 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 9.7777 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2761 ms 100.0%
  triton_mm_1779 0.2806 ms 98.4%
  triton_mm_1780 0.2847 ms 97.0%
  triton_mm_1781 0.2942 ms 93.8%
  triton_mm_1776 0.3385 ms 81.6%
  triton_mm_1772 0.3444 ms 80.2%
  triton_mm_1774 0.3502 ms 78.8%
  triton_mm_1775 0.3757 ms 73.5%
  triton_mm_1777 0.3820 ms 72.3%
  triton_mm_1773 0.3940 ms 70.1%
SingleProcess AUTOTUNE benchmarking takes 2.5058 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2156 ms 100.0%
  triton_mm_1855 0.2697 ms 79.9%
  triton_mm_1850 0.2698 ms 79.9%
  triton_mm_1852 0.2746 ms 78.5%
  triton_mm_1848 0.2752 ms 78.4%
  triton_mm_1856 0.2771 ms 77.8%
  triton_mm_1857 0.2795 ms 77.1%
  triton_mm_1851 0.3028 ms 71.2%
  triton_mm_1853 0.3142 ms 68.6%
  triton_mm_1849 0.3208 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 9.8162 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0984 ms 100.0%
  mm 0.1012 ms 97.2%
  triton_mm_1812 0.1054 ms 93.4%
  triton_mm_1818 0.1090 ms 90.3%
  triton_mm_1809 0.1187 ms 82.9%
  triton_mm_1810 0.1191 ms 82.6%
  triton_mm_1814 0.1196 ms 82.3%
  triton_mm_1817 0.1228 ms 80.1%
  triton_mm_1813 0.1264 ms 77.9%
  triton_mm_1815 0.1313 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 9.8373 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  triton_mm_1760 0.2855 ms 100.0%
  mm 0.2856 ms 99.9%
  triton_mm_1761 0.2932 ms 97.4%
  triton_mm_1762 0.3012 ms 94.8%
  triton_mm_1757 0.3272 ms 87.3%
  triton_mm_1755 0.3313 ms 86.2%
  triton_mm_1753 0.3338 ms 85.5%
  triton_mm_1756 0.3527 ms 80.9%
  triton_mm_1754 0.3697 ms 77.2%
  triton_mm_1758 0.3739 ms 76.3%
SingleProcess AUTOTUNE benchmarking takes 9.7546 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0834 ms 100.0%
  triton_mm_1799 0.0843 ms 98.9%
  triton_mm_1798 0.0858 ms 97.2%
  triton_mm_1795 0.0918 ms 90.8%
  triton_mm_1791 0.0946 ms 88.1%
  triton_mm_1793 0.0947 ms 88.1%
  triton_mm_1800 0.0953 ms 87.5%
  triton_mm_1792 0.1014 ms 82.2%
  triton_mm_1796 0.1050 ms 79.4%
  triton_mm_1789 0.1234 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.3645 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2649 ms 100.0%
  triton_mm_1908 0.2693 ms 98.4%
  triton_mm_1909 0.2729 ms 97.1%
  triton_mm_1910 0.3112 ms 85.1%
  triton_mm_1903 0.3328 ms 79.6%
  triton_mm_1901 0.3351 ms 79.1%
  triton_mm_1905 0.3400 ms 77.9%
  triton_mm_1902 0.3537 ms 74.9%
  triton_mm_1906 0.3809 ms 69.6%
  triton_mm_1904 0.4222 ms 62.8%
SingleProcess AUTOTUNE benchmarking takes 2.5027 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2884 ms 100.0%
  triton_mm_1946 0.2924 ms 98.6%
  triton_mm_1947 0.3018 ms 95.6%
  triton_mm_1948 0.3137 ms 91.9%
  triton_mm_1943 0.3340 ms 86.3%
  triton_mm_1941 0.3385 ms 85.2%
  triton_mm_1939 0.3454 ms 83.5%
  triton_mm_1942 0.3587 ms 80.4%
  triton_mm_1940 0.3791 ms 76.1%
  triton_mm_1944 0.3861 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5035 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1882 0.0187 ms 100.0%
  triton_mm_1881 0.0194 ms 96.7%
  triton_mm_1884 0.0194 ms 96.7%
  triton_mm_1886 0.0194 ms 96.7%
  triton_mm_1888 0.0194 ms 96.7%
  triton_mm_1883 0.0194 ms 96.6%
  triton_mm_1887 0.0196 ms 95.6%
  triton_mm_1885 0.0197 ms 94.8%
  triton_mm_1890 0.0199 ms 94.2%
  triton_mm_1891 0.0199 ms 94.1%
SingleProcess AUTOTUNE benchmarking takes 5.6030 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2762 ms 100.0%
  triton_mm_1965 0.2813 ms 98.2%
  triton_mm_1966 0.2866 ms 96.4%
  triton_mm_1967 0.2933 ms 94.2%
  triton_mm_1962 0.3362 ms 82.2%
  triton_mm_1960 0.3457 ms 79.9%
  triton_mm_1958 0.3469 ms 79.6%
  triton_mm_1961 0.3752 ms 73.6%
  triton_mm_1963 0.3820 ms 72.3%
  triton_mm_1959 0.3933 ms 70.2%
SingleProcess AUTOTUNE benchmarking takes 2.4994 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0292 ms 100.0%
  mm 0.0297 ms 98.1%
  triton_mm_1866 0.0321 ms 90.9%
  triton_mm_1870 0.0407 ms 71.6%
  triton_mm_1861 0.0514 ms 56.7%
  triton_mm_1874 0.0516 ms 56.5%
  triton_mm_1860 0.0562 ms 51.8%
  triton_mm_1865 0.0605 ms 48.2%
  triton_mm_1869 0.0630 ms 46.2%
  triton_mm_1859 0.0655 ms 44.5%
SingleProcess AUTOTUNE benchmarking takes 6.3911 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2159 ms 100.0%
  triton_mm_2041 0.2692 ms 80.2%
  triton_mm_2036 0.2735 ms 79.0%
  triton_mm_2038 0.2758 ms 78.3%
  triton_mm_2042 0.2770 ms 78.0%
  triton_mm_2034 0.2789 ms 77.4%
  triton_mm_2043 0.2814 ms 76.7%
  triton_mm_2037 0.3053 ms 70.7%
  triton_mm_2039 0.3144 ms 68.7%
  triton_mm_2035 0.3242 ms 66.6%
SingleProcess AUTOTUNE benchmarking takes 2.4822 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_2005 0.0996 ms 97.4%
  triton_mm_1998 0.1044 ms 93.0%
  triton_mm_2004 0.1083 ms 89.6%
  triton_mm_1995 0.1188 ms 81.7%
  triton_mm_1996 0.1203 ms 80.7%
  triton_mm_2000 0.1207 ms 80.4%
  triton_mm_2003 0.1235 ms 78.6%
  triton_mm_1999 0.1263 ms 76.8%
  triton_mm_2001 0.1309 ms 74.1%
SingleProcess AUTOTUNE benchmarking takes 2.3693 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0833 ms 100.0%
  triton_mm_1985 0.0842 ms 98.9%
  triton_mm_1984 0.0849 ms 98.1%
  triton_mm_1981 0.0917 ms 90.8%
  triton_mm_1986 0.0941 ms 88.4%
  triton_mm_1977 0.0948 ms 87.8%
  triton_mm_1979 0.0957 ms 87.0%
  triton_mm_1978 0.1021 ms 81.6%
  triton_mm_1982 0.1053 ms 79.0%
  triton_mm_1980 0.1227 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.3624 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2135 ms 100.0%
  triton_mm_2023 0.2155 ms 99.1%
  triton_mm_2022 0.2209 ms 96.7%
  triton_mm_2024 0.2337 ms 91.4%
  triton_mm_2019 0.2498 ms 85.5%
  triton_mm_2015 0.2539 ms 84.1%
  triton_mm_2017 0.2555 ms 83.6%
  triton_mm_2018 0.2840 ms 75.2%
  triton_mm_2016 0.2844 ms 75.1%
  triton_mm_2020 0.2886 ms 74.0%
SingleProcess AUTOTUNE benchmarking takes 2.4762 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2639 ms 100.0%
  triton_mm_2094 0.2696 ms 97.9%
  triton_mm_2095 0.2700 ms 97.7%
  triton_mm_2096 0.3107 ms 85.0%
  triton_mm_2087 0.3334 ms 79.2%
  triton_mm_2089 0.3349 ms 78.8%
  triton_mm_2091 0.3352 ms 78.7%
  triton_mm_2088 0.3546 ms 74.4%
  triton_mm_2092 0.3811 ms 69.3%
  triton_mm_2090 0.4233 ms 62.4%
SingleProcess AUTOTUNE benchmarking takes 2.5096 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2878 ms 100.0%
  triton_mm_2132 0.2911 ms 98.9%
  triton_mm_2133 0.3000 ms 96.0%
  triton_mm_2134 0.3113 ms 92.5%
  triton_mm_2129 0.3338 ms 86.2%
  triton_mm_2127 0.3414 ms 84.3%
  triton_mm_2125 0.3444 ms 83.6%
  triton_mm_2128 0.3579 ms 80.4%
  triton_mm_2126 0.3775 ms 76.2%
  triton_mm_2130 0.3855 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5095 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2069 0.0185 ms 100.0%
  triton_mm_2074 0.0186 ms 99.7%
  triton_mm_2071 0.0189 ms 98.0%
  triton_mm_2070 0.0193 ms 95.9%
  triton_mm_2072 0.0193 ms 95.7%
  triton_mm_2067 0.0196 ms 94.3%
  triton_mm_2073 0.0196 ms 94.3%
  triton_mm_2068 0.0197 ms 93.8%
  triton_mm_2066 0.0199 ms 92.9%
  triton_mm_2075 0.0199 ms 92.9%
SingleProcess AUTOTUNE benchmarking takes 2.0177 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2127 ms 100.0%
  triton_mm_2209 0.2152 ms 98.8%
  triton_mm_2208 0.2211 ms 96.2%
  triton_mm_2210 0.2354 ms 90.3%
  triton_mm_2205 0.2472 ms 86.0%
  triton_mm_2203 0.2525 ms 84.2%
  triton_mm_2201 0.2537 ms 83.8%
  triton_mm_2202 0.2844 ms 74.8%
  triton_mm_2204 0.2845 ms 74.7%
  triton_mm_2206 0.2891 ms 73.6%
SingleProcess AUTOTUNE benchmarking takes 2.4697 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2648 ms 100.0%
  triton_mm_2280 0.2717 ms 97.4%
  triton_mm_2281 0.2737 ms 96.7%
  triton_mm_2282 0.3106 ms 85.2%
  triton_mm_2273 0.3341 ms 79.2%
  triton_mm_2275 0.3344 ms 79.2%
  triton_mm_2277 0.3393 ms 78.0%
  triton_mm_2274 0.3539 ms 74.8%
  triton_mm_2278 0.3805 ms 69.6%
  triton_mm_2276 0.4227 ms 62.6%
SingleProcess AUTOTUNE benchmarking takes 2.5026 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2878 ms 100.0%
  triton_mm_2318 0.2917 ms 98.7%
  triton_mm_2319 0.3046 ms 94.5%
  triton_mm_2320 0.3132 ms 91.9%
  triton_mm_2315 0.3332 ms 86.4%
  triton_mm_2313 0.3415 ms 84.3%
  triton_mm_2311 0.3429 ms 83.9%
  triton_mm_2314 0.3603 ms 79.9%
  triton_mm_2312 0.3789 ms 76.0%
  triton_mm_2316 0.3865 ms 74.5%
SingleProcess AUTOTUNE benchmarking takes 2.5102 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2260 0.0186 ms 100.0%
  triton_mm_2254 0.0187 ms 99.1%
  triton_mm_2257 0.0188 ms 98.6%
  triton_mm_2253 0.0193 ms 96.2%
  triton_mm_2255 0.0193 ms 95.9%
  triton_mm_2256 0.0202 ms 92.1%
  triton_mm_2258 0.0202 ms 92.0%
  triton_mm_2259 0.0204 ms 91.2%
  triton_mm_2263 0.0205 ms 90.5%
  triton_mm_2252 0.0206 ms 90.1%
SingleProcess AUTOTUNE benchmarking takes 2.0240 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2138 ms 100.0%
  triton_mm_2395 0.2168 ms 98.6%
  triton_mm_2394 0.2207 ms 96.9%
  triton_mm_2396 0.2356 ms 90.7%
  triton_mm_2391 0.2475 ms 86.4%
  triton_mm_2389 0.2539 ms 84.2%
  triton_mm_2387 0.2593 ms 82.5%
  triton_mm_2390 0.2838 ms 75.3%
  triton_mm_2388 0.2847 ms 75.1%
  triton_mm_2392 0.2892 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 2.4826 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2639 ms 100.0%
  triton_mm_2466 0.2663 ms 99.1%
  triton_mm_2467 0.2697 ms 97.8%
  triton_mm_2468 0.3104 ms 85.0%
  triton_mm_2459 0.3304 ms 79.9%
  triton_mm_2461 0.3337 ms 79.1%
  triton_mm_2463 0.3384 ms 78.0%
  triton_mm_2460 0.3602 ms 73.3%
  triton_mm_2464 0.3791 ms 69.6%
  triton_mm_2462 0.4234 ms 62.3%
SingleProcess AUTOTUNE benchmarking takes 2.5077 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2892 ms 100.0%
  triton_mm_2504 0.2900 ms 99.7%
  triton_mm_2505 0.3005 ms 96.2%
  triton_mm_2506 0.3098 ms 93.3%
  triton_mm_2501 0.3338 ms 86.6%
  triton_mm_2499 0.3392 ms 85.2%
  triton_mm_2497 0.3410 ms 84.8%
  triton_mm_2500 0.3577 ms 80.8%
  triton_mm_2498 0.3779 ms 76.5%
  triton_mm_2502 0.3875 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.5113 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2439 0.0185 ms 100.0%
  triton_mm_2443 0.0188 ms 98.5%
  triton_mm_2441 0.0194 ms 95.5%
  triton_mm_2445 0.0196 ms 94.6%
  triton_mm_2446 0.0196 ms 94.3%
  triton_mm_2440 0.0197 ms 94.0%
  triton_mm_2449 0.0199 ms 92.9%
  triton_mm_2442 0.0201 ms 91.9%
  triton_mm_2444 0.0202 ms 91.7%
  triton_mm_2438 0.0206 ms 89.9%
SingleProcess AUTOTUNE benchmarking takes 2.0291 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2127 ms 100.0%
  triton_mm_2581 0.2157 ms 98.6%
  triton_mm_2580 0.2213 ms 96.1%
  triton_mm_2582 0.2340 ms 90.9%
  triton_mm_2577 0.2491 ms 85.4%
  triton_mm_2575 0.2547 ms 83.5%
  triton_mm_2573 0.2572 ms 82.7%
  triton_mm_2576 0.2843 ms 74.8%
  triton_mm_2574 0.2857 ms 74.4%
  triton_mm_2578 0.2873 ms 74.0%
SingleProcess AUTOTUNE benchmarking takes 2.4792 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2650 ms 100.0%
  triton_mm_2653 0.2688 ms 98.6%
  triton_mm_2652 0.2703 ms 98.0%
  triton_mm_2654 0.3101 ms 85.5%
  triton_mm_2645 0.3311 ms 80.0%
  triton_mm_2647 0.3365 ms 78.7%
  triton_mm_2649 0.3400 ms 77.9%
  triton_mm_2646 0.3549 ms 74.7%
  triton_mm_2650 0.3767 ms 70.3%
  triton_mm_2648 0.4229 ms 62.7%
SingleProcess AUTOTUNE benchmarking takes 2.5142 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2878 ms 100.0%
  triton_mm_2690 0.2902 ms 99.2%
  triton_mm_2691 0.2989 ms 96.3%
  triton_mm_2692 0.3062 ms 94.0%
  triton_mm_2683 0.3333 ms 86.4%
  triton_mm_2687 0.3336 ms 86.3%
  triton_mm_2685 0.3388 ms 85.0%
  triton_mm_2686 0.3599 ms 80.0%
  triton_mm_2684 0.3781 ms 76.1%
  triton_mm_2688 0.3840 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5153 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2627 0.0185 ms 100.0%
  triton_mm_2626 0.0187 ms 98.8%
  triton_mm_2629 0.0188 ms 98.3%
  triton_mm_2628 0.0193 ms 95.7%
  triton_mm_2632 0.0195 ms 94.9%
  triton_mm_2625 0.0196 ms 94.4%
  triton_mm_2630 0.0203 ms 91.2%
  triton_mm_2631 0.0205 ms 90.0%
  triton_mm_2623 0.0206 ms 89.8%
  triton_mm_2633 0.0206 ms 89.8%
SingleProcess AUTOTUNE benchmarking takes 2.0335 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2138 ms 100.0%
  triton_mm_2767 0.2154 ms 99.2%
  triton_mm_2766 0.2207 ms 96.9%
  triton_mm_2768 0.2349 ms 91.0%
  triton_mm_2763 0.2489 ms 85.9%
  triton_mm_2761 0.2549 ms 83.9%
  triton_mm_2759 0.2563 ms 83.4%
  triton_mm_2762 0.2842 ms 75.2%
  triton_mm_2760 0.2844 ms 75.2%
  triton_mm_2764 0.2895 ms 73.8%
SingleProcess AUTOTUNE benchmarking takes 2.4785 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2136 ms 100.0%
  triton_mm_2953 0.2169 ms 98.5%
  triton_mm_2952 0.2215 ms 96.4%
  triton_mm_2954 0.2356 ms 90.7%
  triton_mm_2949 0.2473 ms 86.3%
  triton_mm_2947 0.2536 ms 84.2%
  triton_mm_2945 0.2541 ms 84.1%
  triton_mm_2948 0.2815 ms 75.9%
  triton_mm_2946 0.2820 ms 75.7%
  triton_mm_2950 0.2872 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.4801 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0309 ms 100.0%
  triton_mm_4879 0.0500 ms 61.7%
  triton_mm_4872 0.0503 ms 61.4%
  triton_mm_4870 0.0562 ms 55.0%
  triton_mm_4871 0.0627 ms 49.3%
  triton_mm_4878 0.0664 ms 46.5%
  triton_mm_4875 0.0699 ms 44.2%
  triton_mm_4884 0.0738 ms 41.8%
  triton_mm_4883 0.0747 ms 41.3%
  triton_mm_4877 0.0773 ms 40.0%
SingleProcess AUTOTUNE benchmarking takes 6.3476 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8161 ms 100.0%
  mm 0.8256 ms 98.9%
  triton_mm_4987 0.9828 ms 83.0%
  triton_mm_4983 1.0006 ms 81.6%
  triton_mm_4991 1.0586 ms 77.1%
  triton_mm_4988 1.0913 ms 74.8%
  triton_mm_4984 1.1037 ms 73.9%
  triton_mm_4985 1.1324 ms 72.1%
  triton_mm_4980 1.3367 ms 61.1%
  triton_mm_4981 1.4006 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1401 seconds and 0.0013 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8139 ms 100.0%
  mm 0.8287 ms 98.2%
  triton_mm_5080 0.9824 ms 82.8%
  triton_mm_5076 1.0118 ms 80.4%
  triton_mm_5084 1.0597 ms 76.8%
  triton_mm_5081 1.1031 ms 73.8%
  triton_mm_5077 1.1042 ms 73.7%
  triton_mm_5078 1.1428 ms 71.2%
  triton_mm_5073 1.3369 ms 60.9%
  triton_mm_5074 1.4059 ms 57.9%
SingleProcess AUTOTUNE benchmarking takes 2.1473 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.7802 ms 100.0%
  triton_mm_6013 0.8180 ms 95.4%
  triton_mm_6010 0.9944 ms 78.5%
  triton_mm_6006 1.0106 ms 77.2%
  triton_mm_6014 1.0642 ms 73.3%
  triton_mm_6011 1.1069 ms 70.5%
  triton_mm_6007 1.1081 ms 70.4%
  triton_mm_6008 1.1416 ms 68.3%
  triton_mm_6003 1.3368 ms 58.4%
  triton_mm_6004 1.4145 ms 55.2%
SingleProcess AUTOTUNE benchmarking takes 2.1446 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6292 0.8214 ms 100.0%
  mm 0.8252 ms 99.5%
  triton_mm_6289 0.9850 ms 83.4%
  triton_mm_6285 1.0096 ms 81.4%
  triton_mm_6293 1.0553 ms 77.8%
  triton_mm_6290 1.1035 ms 74.4%
  triton_mm_6286 1.1090 ms 74.1%
  triton_mm_6287 1.1407 ms 72.0%
  triton_mm_6282 1.3408 ms 61.3%
  triton_mm_6283 1.4005 ms 58.6%
SingleProcess AUTOTUNE benchmarking takes 2.1356 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0419 ms 100.0%
  triton_mm_4892 0.0427 ms 98.1%
  triton_mm_4896 0.0433 ms 96.6%
  triton_mm_4895 0.0443 ms 94.6%
  triton_mm_4899 0.0444 ms 94.3%
  triton_mm_4887 0.0458 ms 91.4%
  triton_mm_4898 0.0459 ms 91.2%
  triton_mm_4894 0.0469 ms 89.4%
  triton_mm_4888 0.0476 ms 88.0%
  triton_mm_4891 0.0539 ms 77.7%
SingleProcess AUTOTUNE benchmarking takes 1.5835 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4904 0.0397 ms 100.0%
  triton_mm_4905 0.0406 ms 97.8%
  triton_mm_4909 0.0408 ms 97.3%
  triton_mm_4914 0.0410 ms 96.7%
  triton_mm_4906 0.0413 ms 96.0%
  triton_mm_4908 0.0416 ms 95.3%
  triton_mm_4911 0.0417 ms 95.2%
  triton_mm_4910 0.0417 ms 95.2%
  triton_mm_4913 0.0417 ms 95.1%
  triton_mm_4912 0.0419 ms 94.8%
SingleProcess AUTOTUNE benchmarking takes 2.0198 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6306 ms 100.0%
  triton_mm_4935 0.6355 ms 99.2%
  triton_mm_4932 0.7471 ms 84.4%
  triton_mm_4928 0.7569 ms 83.3%
  addmm 0.8021 ms 78.6%
  triton_mm_4936 0.8326 ms 75.7%
  triton_mm_4933 0.8336 ms 75.7%
  triton_mm_4929 0.8399 ms 75.1%
  triton_mm_4930 0.8675 ms 72.7%
  triton_mm_4925 1.0077 ms 62.6%
SingleProcess AUTOTUNE benchmarking takes 2.2332 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2192 ms 100.0%
  mm 0.2311 ms 94.9%
  triton_mm_4951 0.2521 ms 87.0%
  triton_mm_4947 0.2603 ms 84.2%
  triton_mm_4952 0.2765 ms 79.3%
  triton_mm_4955 0.2895 ms 75.7%
  triton_mm_4948 0.2916 ms 75.2%
  triton_mm_4949 0.3094 ms 70.9%
  triton_mm_4944 0.3447 ms 63.6%
  triton_mm_4945 0.3542 ms 61.9%
SingleProcess AUTOTUNE benchmarking takes 1.9960 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8306 ms 100.0%
  mm 0.8649 ms 96.0%
  triton_mm_5010 0.9890 ms 84.0%
  triton_mm_5006 1.0130 ms 82.0%
  triton_mm_5002 1.0422 ms 79.7%
  triton_mm_5007 1.0658 ms 77.9%
  triton_mm_5003 1.1116 ms 74.7%
  triton_mm_5004 1.1377 ms 73.0%
  triton_mm_4999 1.3588 ms 61.1%
  triton_mm_5000 1.3595 ms 61.1%
SingleProcess AUTOTUNE benchmarking takes 2.1488 seconds and 0.0011 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_5958 0.6269 ms 100.0%
  bias_addmm 0.6319 ms 99.2%
  triton_mm_5955 0.7367 ms 85.1%
  triton_mm_5951 0.7503 ms 83.6%
  addmm 0.8046 ms 77.9%
  triton_mm_5959 0.8321 ms 75.3%
  triton_mm_5956 0.8340 ms 75.2%
  triton_mm_5952 0.8445 ms 74.2%
  triton_mm_5953 0.8714 ms 71.9%
  triton_mm_5948 1.0073 ms 62.2%
SingleProcess AUTOTUNE benchmarking takes 2.2455 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_5977 0.2179 ms 100.0%
  mm 0.2324 ms 93.7%
  triton_mm_5974 0.2497 ms 87.3%
  triton_mm_5970 0.2635 ms 82.7%
  triton_mm_5975 0.2758 ms 79.0%
  triton_mm_5978 0.2880 ms 75.7%
  triton_mm_5971 0.2915 ms 74.8%
  triton_mm_5972 0.3089 ms 70.5%
  triton_mm_5967 0.3440 ms 63.3%
  triton_mm_5968 0.3534 ms 61.7%
SingleProcess AUTOTUNE benchmarking takes 2.0054 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0419 ms 100.0%
  triton_mm_5987 0.0427 ms 98.3%
  triton_mm_5991 0.0434 ms 96.7%
  triton_mm_5994 0.0444 ms 94.4%
  triton_mm_5990 0.0450 ms 93.1%
  triton_mm_5982 0.0459 ms 91.4%
  triton_mm_5993 0.0459 ms 91.3%
  triton_mm_5989 0.0469 ms 89.4%
  triton_mm_5983 0.0484 ms 86.7%
  triton_mm_5986 0.0546 ms 76.7%
SingleProcess AUTOTUNE benchmarking takes 1.5986 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_6032 0.8196 ms 100.0%
  mm 0.8684 ms 94.4%
  triton_mm_6033 0.9873 ms 83.0%
  triton_mm_6029 1.0148 ms 80.8%
  triton_mm_6025 1.0336 ms 79.3%
  triton_mm_6030 1.0697 ms 76.6%
  triton_mm_6026 1.1143 ms 73.6%
  triton_mm_6027 1.1309 ms 72.5%
  triton_mm_6022 1.3567 ms 60.4%
  triton_mm_6023 1.3603 ms 60.3%
SingleProcess AUTOTUNE benchmarking takes 2.1613 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0226 ms 100.0%
  triton_mm_6447 0.0232 ms 97.6%
  mm 0.0243 ms 93.3%
  triton_mm_6452 0.0250 ms 90.5%
  triton_mm_6446 0.0256 ms 88.4%
  triton_mm_6459 0.0260 ms 87.0%
  triton_mm_6456 0.0274 ms 82.5%
  triton_mm_6455 0.0284 ms 79.7%
  triton_mm_6458 0.0287 ms 78.7%
  triton_mm_6454 0.0312 ms 72.5%
SingleProcess AUTOTUNE benchmarking takes 1.5846 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5295 ms 100.0%
  bias_addmm 1.5514 ms 98.6%
  triton_mm_6513 1.8675 ms 81.9%
  addmm 1.9261 ms 79.4%
  triton_mm_6509 1.9457 ms 78.6%
  triton_mm_6517 2.0173 ms 75.8%
  triton_mm_6514 2.0743 ms 73.7%
  triton_mm_6510 2.1226 ms 72.1%
  triton_mm_6511 2.1816 ms 70.1%
  triton_mm_6506 2.5219 ms 60.6%
SingleProcess AUTOTUNE benchmarking takes 2.4054 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:09<1:32:50, 129.54s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8139 ms 100.0%
  mm 0.8172 ms 99.6%
  triton_mm_4987 0.9799 ms 83.1%
  triton_mm_4983 0.9882 ms 82.4%
  triton_mm_4991 1.0568 ms 77.0%
  triton_mm_4988 1.0889 ms 74.7%
  triton_mm_4984 1.0980 ms 74.1%
  triton_mm_4985 1.1244 ms 72.4%
  triton_mm_4980 1.3325 ms 61.1%
  triton_mm_4981 1.3978 ms 58.2%
SingleProcess AUTOTUNE benchmarking takes 2.1480 seconds and 0.0013 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8142 ms 100.0%
  mm 0.8166 ms 99.7%
  triton_mm_5080 0.9799 ms 83.1%
  triton_mm_5076 0.9906 ms 82.2%
  triton_mm_5084 1.0573 ms 77.0%
  triton_mm_5077 1.0917 ms 74.6%
  triton_mm_5081 1.0943 ms 74.4%
  triton_mm_5078 1.1236 ms 72.5%
  triton_mm_5073 1.3316 ms 61.1%
  triton_mm_5074 1.3956 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1462 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5176 0.8148 ms 100.0%
  mm 0.8322 ms 97.9%
  triton_mm_5173 0.9804 ms 83.1%
  triton_mm_5169 1.0016 ms 81.3%
  triton_mm_5177 1.0538 ms 77.3%
  triton_mm_5174 1.0896 ms 74.8%
  triton_mm_5170 1.0948 ms 74.4%
  triton_mm_5171 1.1273 ms 72.3%
  triton_mm_5166 1.3298 ms 61.3%
  triton_mm_5167 1.3976 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1414 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6013 0.8156 ms 100.0%
  mm 0.8221 ms 99.2%
  triton_mm_6010 0.9808 ms 83.2%
  triton_mm_6006 1.0010 ms 81.5%
  triton_mm_6014 1.0565 ms 77.2%
  triton_mm_6011 1.1037 ms 73.9%
  triton_mm_6007 1.1193 ms 72.9%
  triton_mm_6008 1.1324 ms 72.0%
  triton_mm_6003 1.3164 ms 62.0%
  triton_mm_6004 1.4041 ms 58.1%
SingleProcess AUTOTUNE benchmarking takes 2.1400 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0411 ms 100.0%
  triton_mm_4892 0.0416 ms 98.9%
  triton_mm_4896 0.0430 ms 95.5%
  triton_mm_4899 0.0437 ms 94.1%
  triton_mm_4895 0.0438 ms 93.8%
  triton_mm_4898 0.0456 ms 90.2%
  triton_mm_4887 0.0459 ms 89.5%
  triton_mm_4894 0.0476 ms 86.5%
  triton_mm_4888 0.0487 ms 84.5%
  triton_mm_4886 0.0529 ms 77.7%
SingleProcess AUTOTUNE benchmarking takes 1.5791 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4905 0.0395 ms 100.0%
  triton_mm_4904 0.0404 ms 97.8%
  triton_mm_4912 0.0408 ms 96.9%
  triton_mm_4903 0.0409 ms 96.6%
  triton_mm_4906 0.0409 ms 96.6%
  triton_mm_4914 0.0412 ms 95.9%
  triton_mm_4915 0.0413 ms 95.6%
  triton_mm_4909 0.0415 ms 95.2%
  triton_mm_4910 0.0415 ms 95.1%
  triton_mm_4911 0.0415 ms 95.1%
SingleProcess AUTOTUNE benchmarking takes 2.0143 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6260 ms 100.0%
  triton_mm_4935 0.6267 ms 99.9%
  triton_mm_4932 0.7435 ms 84.2%
  triton_mm_4928 0.7504 ms 83.4%
  addmm 0.8028 ms 78.0%
  triton_mm_4936 0.8302 ms 75.4%
  triton_mm_4933 0.8328 ms 75.2%
  triton_mm_4929 0.8403 ms 74.5%
  triton_mm_4930 0.8594 ms 72.8%
  triton_mm_4925 1.0023 ms 62.5%
SingleProcess AUTOTUNE benchmarking takes 2.2296 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2180 ms 100.0%
  mm 0.2315 ms 94.2%
  triton_mm_4951 0.2476 ms 88.0%
  triton_mm_4947 0.2604 ms 83.7%
  triton_mm_4952 0.2754 ms 79.1%
  triton_mm_4955 0.2886 ms 75.5%
  triton_mm_4948 0.2914 ms 74.8%
  triton_mm_4949 0.3046 ms 71.5%
  triton_mm_4944 0.3406 ms 64.0%
  triton_mm_4945 0.3515 ms 62.0%
SingleProcess AUTOTUNE benchmarking takes 1.9957 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8284 ms 100.0%
  mm 0.8760 ms 94.6%
  triton_mm_5010 0.9887 ms 83.8%
  triton_mm_5006 0.9999 ms 82.8%
  triton_mm_5002 1.0495 ms 78.9%
  triton_mm_5007 1.0603 ms 78.1%
  triton_mm_5003 1.1104 ms 74.6%
  triton_mm_5004 1.1226 ms 73.8%
  triton_mm_4999 1.3404 ms 61.8%
  triton_mm_5000 1.3601 ms 60.9%
SingleProcess AUTOTUNE benchmarking takes 2.1489 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0232 ms 100.0%
  triton_mm_6447 0.0232 ms 99.9%
  mm 0.0240 ms 96.5%
  triton_mm_6452 0.0247 ms 93.8%
  triton_mm_6459 0.0250 ms 92.7%
  triton_mm_6446 0.0256 ms 90.6%
  triton_mm_6456 0.0270 ms 85.8%
  triton_mm_6458 0.0278 ms 83.2%
  triton_mm_6455 0.0284 ms 81.5%
  triton_mm_6454 0.0310 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 1.5867 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5469 ms 100.0%
  bias_addmm 1.5753 ms 98.2%
  triton_mm_6513 1.8604 ms 83.1%
  triton_mm_6509 1.9335 ms 80.0%
  addmm 1.9340 ms 80.0%
  triton_mm_6517 2.0108 ms 76.9%
  triton_mm_6514 2.0750 ms 74.6%
  triton_mm_6510 2.1008 ms 73.6%
  triton_mm_6511 2.1651 ms 71.4%
  triton_mm_6506 2.5085 ms 61.7%
SingleProcess AUTOTUNE benchmarking takes 2.3980 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:09<1:32:50, 129.55s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8134 ms 100.0%
  mm 0.8164 ms 99.6%
  triton_mm_4987 0.9780 ms 83.2%
  triton_mm_4983 0.9815 ms 82.9%
  triton_mm_4991 1.0598 ms 76.8%
  triton_mm_4984 1.0893 ms 74.7%
  triton_mm_4988 1.0918 ms 74.5%
  triton_mm_4985 1.1255 ms 72.3%
  triton_mm_4980 1.3174 ms 61.7%
  triton_mm_4981 1.3805 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1432 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.8167 ms 100.0%
  triton_mm_5083 0.8168 ms 100.0%
  triton_mm_5080 0.9670 ms 84.5%
  triton_mm_5076 0.9889 ms 82.6%
  triton_mm_5084 1.0555 ms 77.4%
  triton_mm_5081 1.0928 ms 74.7%
  triton_mm_5077 1.0940 ms 74.7%
  triton_mm_5078 1.1224 ms 72.8%
  triton_mm_5073 1.3165 ms 62.0%
  triton_mm_5074 1.3818 ms 59.1%
SingleProcess AUTOTUNE benchmarking takes 2.1410 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.7749 ms 100.0%
  triton_mm_5734 0.8121 ms 95.4%
  triton_mm_5731 0.9781 ms 79.2%
  triton_mm_5727 0.9881 ms 78.4%
  triton_mm_5735 1.0558 ms 73.4%
  triton_mm_5732 1.0925 ms 70.9%
  triton_mm_5728 1.0936 ms 70.9%
  triton_mm_5729 1.1220 ms 69.1%
  triton_mm_5724 1.3288 ms 58.3%
  triton_mm_5725 1.3814 ms 56.1%
SingleProcess AUTOTUNE benchmarking takes 2.1284 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5827 0.8143 ms 100.0%
  mm 0.8243 ms 98.8%
  triton_mm_5824 0.9792 ms 83.2%
  triton_mm_5820 0.9918 ms 82.1%
  triton_mm_5828 1.0553 ms 77.2%
  triton_mm_5825 1.0892 ms 74.8%
  triton_mm_5821 1.0893 ms 74.8%
  triton_mm_5822 1.1259 ms 72.3%
  triton_mm_5817 1.3295 ms 61.2%
  triton_mm_5818 1.3875 ms 58.7%
SingleProcess AUTOTUNE benchmarking takes 2.1473 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6106 0.8138 ms 100.0%
  mm 0.8270 ms 98.4%
  triton_mm_6099 0.9336 ms 87.2%
  triton_mm_6103 0.9934 ms 81.9%
  triton_mm_6107 1.0584 ms 76.9%
  triton_mm_6104 1.0893 ms 74.7%
  triton_mm_6100 1.1008 ms 73.9%
  triton_mm_6101 1.1252 ms 72.3%
  triton_mm_6096 1.3298 ms 61.2%
  triton_mm_6097 1.3807 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1365 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0414 ms 100.0%
  triton_mm_4892 0.0415 ms 99.8%
  triton_mm_4896 0.0429 ms 96.3%
  triton_mm_4899 0.0435 ms 95.1%
  triton_mm_4895 0.0437 ms 94.7%
  triton_mm_4898 0.0444 ms 93.1%
  triton_mm_4887 0.0456 ms 90.7%
  triton_mm_4894 0.0460 ms 90.0%
  triton_mm_4888 0.0474 ms 87.3%
  triton_mm_4891 0.0538 ms 76.9%
SingleProcess AUTOTUNE benchmarking takes 1.5814 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4904 0.0397 ms 100.0%
  triton_mm_4906 0.0402 ms 98.8%
  triton_mm_4905 0.0404 ms 98.1%
  triton_mm_4915 0.0409 ms 97.0%
  triton_mm_4914 0.0412 ms 96.3%
  triton_mm_4909 0.0415 ms 95.7%
  triton_mm_4908 0.0415 ms 95.5%
  triton_mm_4913 0.0416 ms 95.3%
  triton_mm_4912 0.0417 ms 95.2%
  triton_mm_4903 0.0418 ms 94.9%
SingleProcess AUTOTUNE benchmarking takes 2.0173 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6240 ms 100.0%
  triton_mm_4935 0.6288 ms 99.2%
  triton_mm_4932 0.7355 ms 84.8%
  triton_mm_4928 0.7432 ms 84.0%
  addmm 0.7957 ms 78.4%
  triton_mm_4933 0.8229 ms 75.8%
  triton_mm_4936 0.8300 ms 75.2%
  triton_mm_4929 0.8332 ms 74.9%
  triton_mm_4930 0.8670 ms 72.0%
  triton_mm_4925 1.0024 ms 62.2%
SingleProcess AUTOTUNE benchmarking takes 2.2391 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2171 ms 100.0%
  mm 0.2306 ms 94.1%
  triton_mm_4951 0.2455 ms 88.4%
  triton_mm_4947 0.2616 ms 83.0%
  triton_mm_4952 0.2750 ms 78.9%
  triton_mm_4955 0.2883 ms 75.3%
  triton_mm_4948 0.2908 ms 74.6%
  triton_mm_4949 0.3021 ms 71.9%
  triton_mm_4944 0.3391 ms 64.0%
  triton_mm_4945 0.3519 ms 61.7%
SingleProcess AUTOTUNE benchmarking takes 1.9926 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8231 ms 100.0%
  mm 0.8654 ms 95.1%
  triton_mm_5010 0.9889 ms 83.2%
  triton_mm_5006 0.9961 ms 82.6%
  triton_mm_5002 1.0373 ms 79.3%
  triton_mm_5007 1.0573 ms 77.9%
  triton_mm_5003 1.1078 ms 74.3%
  triton_mm_5004 1.1184 ms 73.6%
  triton_mm_4999 1.3270 ms 62.0%
  triton_mm_5000 1.3614 ms 60.5%
SingleProcess AUTOTUNE benchmarking takes 2.1502 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0223 ms 100.0%
  triton_mm_6447 0.0227 ms 98.2%
  mm 0.0240 ms 92.9%
  triton_mm_6452 0.0241 ms 92.4%
  triton_mm_6459 0.0251 ms 89.0%
  triton_mm_6446 0.0256 ms 87.0%
  triton_mm_6456 0.0276 ms 80.8%
  triton_mm_6458 0.0286 ms 77.9%
  triton_mm_6455 0.0296 ms 75.3%
  triton_mm_6454 0.0310 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 1.5783 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5372 ms 100.0%
  bias_addmm 1.5488 ms 99.2%
  triton_mm_6513 1.8583 ms 82.7%
  triton_mm_6509 1.9136 ms 80.3%
  addmm 1.9187 ms 80.1%
  triton_mm_6517 1.9896 ms 77.3%
  triton_mm_6514 2.0691 ms 74.3%
  triton_mm_6510 2.1070 ms 73.0%
  triton_mm_6511 2.1654 ms 71.0%
  triton_mm_6506 2.5381 ms 60.6%
SingleProcess AUTOTUNE benchmarking takes 2.4016 seconds and 0.0012 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:09<1:32:50, 129.56s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.7989 ms 100.0%
  mm 0.8119 ms 98.4%
  triton_mm_4987 0.9588 ms 83.3%
  triton_mm_4983 0.9789 ms 81.6%
  triton_mm_4991 1.0543 ms 75.8%
  triton_mm_4984 1.0696 ms 74.7%
  triton_mm_4988 1.0791 ms 74.0%
  triton_mm_4985 1.1070 ms 72.2%
  triton_mm_4980 1.3049 ms 61.2%
  triton_mm_4981 1.3825 ms 57.8%
SingleProcess AUTOTUNE benchmarking takes 2.1497 seconds and 0.0014 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8014 ms 100.0%
  mm 0.8152 ms 98.3%
  triton_mm_5080 0.9669 ms 82.9%
  triton_mm_5076 0.9779 ms 82.0%
  triton_mm_5084 1.0552 ms 75.9%
  triton_mm_5081 1.0785 ms 74.3%
  triton_mm_5077 1.0812 ms 74.1%
  triton_mm_5078 1.1153 ms 71.9%
  triton_mm_5073 1.3175 ms 60.8%
  triton_mm_5074 1.3838 ms 57.9%
SingleProcess AUTOTUNE benchmarking takes 2.1389 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5920 0.8049 ms 100.0%
  mm 0.8104 ms 99.3%
  triton_mm_5917 0.9679 ms 83.2%
  triton_mm_5913 0.9728 ms 82.7%
  triton_mm_5921 1.0553 ms 76.3%
  triton_mm_5914 1.0779 ms 74.7%
  triton_mm_5918 1.0802 ms 74.5%
  triton_mm_5915 1.1156 ms 72.2%
  triton_mm_5910 1.3165 ms 61.1%
  triton_mm_5911 1.3875 ms 58.0%
SingleProcess AUTOTUNE benchmarking takes 2.1488 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  triton_mm_4892 0.0410 ms 100.0%
  mm 0.0413 ms 99.1%
  triton_mm_4896 0.0417 ms 98.3%
  triton_mm_4899 0.0429 ms 95.6%
  triton_mm_4895 0.0441 ms 92.9%
  triton_mm_4898 0.0449 ms 91.3%
  triton_mm_4887 0.0452 ms 90.7%
  triton_mm_4888 0.0468 ms 87.5%
  triton_mm_4894 0.0470 ms 87.2%
  triton_mm_4886 0.0537 ms 76.3%
SingleProcess AUTOTUNE benchmarking takes 1.5827 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4904 0.0397 ms 100.0%
  triton_mm_4905 0.0406 ms 97.9%
  triton_mm_4909 0.0408 ms 97.4%
  triton_mm_4906 0.0414 ms 96.0%
  triton_mm_4908 0.0417 ms 95.3%
  triton_mm_4912 0.0417 ms 95.2%
  triton_mm_4914 0.0418 ms 95.2%
  triton_mm_4915 0.0420 ms 94.7%
  triton_mm_4903 0.0420 ms 94.6%
  triton_mm_4907 0.0422 ms 94.2%
SingleProcess AUTOTUNE benchmarking takes 2.0131 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6188 ms 100.0%
  triton_mm_4935 0.6224 ms 99.4%
  triton_mm_4932 0.7307 ms 84.7%
  triton_mm_4928 0.7426 ms 83.3%
  addmm 0.7900 ms 78.3%
  triton_mm_4933 0.8158 ms 75.9%
  triton_mm_4929 0.8309 ms 74.5%
  triton_mm_4936 0.8326 ms 74.3%
  triton_mm_4930 0.8613 ms 71.9%
  triton_mm_4925 0.9916 ms 62.4%
SingleProcess AUTOTUNE benchmarking takes 2.2281 seconds and 0.0013 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2191 ms 100.0%
  mm 0.2341 ms 93.6%
  triton_mm_4951 0.2489 ms 88.0%
  triton_mm_4947 0.2616 ms 83.8%
  triton_mm_4952 0.2731 ms 80.2%
  triton_mm_4948 0.2882 ms 76.0%
  triton_mm_4955 0.2884 ms 76.0%
  triton_mm_4949 0.3068 ms 71.4%
  triton_mm_4944 0.3402 ms 64.4%
  triton_mm_4945 0.3520 ms 62.3%
SingleProcess AUTOTUNE benchmarking takes 1.9954 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8162 ms 100.0%
  mm 0.8575 ms 95.2%
  triton_mm_5010 0.9776 ms 83.5%
  triton_mm_5006 0.9836 ms 83.0%
  triton_mm_5002 1.0237 ms 79.7%
  triton_mm_5007 1.0444 ms 78.1%
  triton_mm_5003 1.0918 ms 74.8%
  triton_mm_5004 1.1140 ms 73.3%
  triton_mm_4999 1.3306 ms 61.3%
  triton_mm_5000 1.3361 ms 61.1%
SingleProcess AUTOTUNE benchmarking takes 2.1439 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6448 0.0232 ms 100.0%
  triton_mm_6447 0.0238 ms 97.4%
  mm 0.0243 ms 95.4%
  triton_mm_6452 0.0255 ms 90.7%
  triton_mm_6459 0.0259 ms 89.6%
  triton_mm_6446 0.0265 ms 87.5%
  triton_mm_6456 0.0276 ms 83.8%
  triton_mm_6458 0.0286 ms 81.0%
  triton_mm_6455 0.0288 ms 80.4%
  triton_mm_6454 0.0314 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 1.5647 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5101 ms 100.0%
  bias_addmm 1.5178 ms 99.5%
  triton_mm_6513 1.8173 ms 83.1%
  triton_mm_6509 1.8679 ms 80.8%
  addmm 1.8970 ms 79.6%
  triton_mm_6517 2.0014 ms 75.5%
  triton_mm_6514 2.0617 ms 73.2%
  triton_mm_6510 2.0653 ms 73.1%
  triton_mm_6511 2.1482 ms 70.3%
  triton_mm_6506 2.4854 ms 60.8%
SingleProcess AUTOTUNE benchmarking takes 2.3973 seconds and 0.0012 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:09<1:32:56, 129.68s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:12<38:27, 54.94s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:12<38:27, 54.94s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:12<38:27, 54.95s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:12<38:29, 55.00s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:13<20:42, 30.29s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:13<20:42, 30.30s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:13<20:42, 30.30s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:13<20:43, 30.33s/it]
Validation Progress:   9%|9         | 4/44 [02:14<12:29, 18.75s/it]
Validation Progress:   9%|9         | 4/44 [02:14<12:29, 18.75s/it]
Validation Progress:   9%|9         | 4/44 [02:14<12:29, 18.75s/it]
Validation Progress:   9%|9         | 4/44 [02:14<12:30, 18.77s/it]
Validation Progress:  11%|#1        | 5/44 [02:15<08:04, 12.42s/it]
Validation Progress:  11%|#1        | 5/44 [02:15<08:04, 12.43s/it]
Validation Progress:  11%|#1        | 5/44 [02:15<08:04, 12.42s/it]
Validation Progress:  11%|#1        | 5/44 [02:15<08:04, 12.43s/it]
Validation Progress:  14%|#3        | 6/44 [02:16<05:23,  8.52s/it]
Validation Progress:  14%|#3        | 6/44 [02:16<05:23,  8.52s/it]
Validation Progress:  14%|#3        | 6/44 [02:16<05:23,  8.52s/it]
Validation Progress:  14%|#3        | 6/44 [02:16<05:23,  8.52s/it]
Validation Progress:  16%|#5        | 7/44 [02:17<03:45,  6.08s/it]
Validation Progress:  16%|#5        | 7/44 [02:17<03:45,  6.08s/it]
Validation Progress:  16%|#5        | 7/44 [02:17<03:45,  6.08s/it]
Validation Progress:  16%|#5        | 7/44 [02:17<03:45,  6.09s/it]
Validation Progress:  18%|#8        | 8/44 [02:18<02:40,  4.45s/it]
Validation Progress:  18%|#8        | 8/44 [02:18<02:40,  4.45s/it]
Validation Progress:  18%|#8        | 8/44 [02:18<02:40,  4.45s/it]
Validation Progress:  18%|#8        | 8/44 [02:18<02:40,  4.46s/it]
Validation Progress:  20%|##        | 9/44 [02:19<01:57,  3.37s/it]
Validation Progress:  20%|##        | 9/44 [02:19<01:57,  3.37s/it]
Validation Progress:  20%|##        | 9/44 [02:19<01:57,  3.37s/it]
Validation Progress:  20%|##        | 9/44 [02:19<01:58,  3.37s/it]
Validation Progress:  23%|##2       | 10/44 [02:20<01:28,  2.62s/it]
Validation Progress:  23%|##2       | 10/44 [02:20<01:28,  2.62s/it]
Validation Progress:  23%|##2       | 10/44 [02:20<01:28,  2.62s/it]
Validation Progress:  23%|##2       | 10/44 [02:20<01:29,  2.62s/it]
Validation Progress:  25%|##5       | 11/44 [02:21<01:09,  2.10s/it]
Validation Progress:  25%|##5       | 11/44 [02:21<01:09,  2.11s/it]
Validation Progress:  25%|##5       | 11/44 [02:21<01:10,  2.14s/it]
Validation Progress:  25%|##5       | 11/44 [02:21<01:09,  2.11s/it]
Validation Progress:  27%|##7       | 12/44 [02:22<00:57,  1.79s/it]
Validation Progress:  27%|##7       | 12/44 [02:22<00:56,  1.78s/it]
Validation Progress:  27%|##7       | 12/44 [02:22<00:57,  1.79s/it]
Validation Progress:  27%|##7       | 12/44 [02:22<00:55,  1.75s/it]
Validation Progress:  30%|##9       | 13/44 [02:23<00:47,  1.54s/it]
Validation Progress:  30%|##9       | 13/44 [02:23<00:47,  1.53s/it]
Validation Progress:  30%|##9       | 13/44 [02:23<00:47,  1.54s/it]
Validation Progress:  30%|##9       | 13/44 [02:23<00:46,  1.51s/it]
Validation Progress:  32%|###1      | 14/44 [02:24<00:41,  1.38s/it]
Validation Progress:  32%|###1      | 14/44 [02:24<00:41,  1.37s/it]
Validation Progress:  32%|###1      | 14/44 [02:24<00:41,  1.38s/it]
Validation Progress:  32%|###1      | 14/44 [02:24<00:40,  1.36s/it]
Validation Progress:  34%|###4      | 15/44 [02:25<00:39,  1.36s/it]
Validation Progress:  34%|###4      | 15/44 [02:25<00:39,  1.37s/it]
Validation Progress:  34%|###4      | 15/44 [02:25<00:39,  1.37s/it]
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 12%|#1        | 90/781 [00:05<00:44, 15.68it/s]
 12%|#1        | 92/781 [00:05<00:44, 15.55it/s]
 12%|#2        | 94/781 [00:05<00:43, 15.86it/s]
 12%|#2        | 96/781 [00:05<00:43, 15.64it/s]
 13%|#2        | 98/781 [00:06<00:43, 15.67it/s]
 13%|#2        | 100/781 [00:06<00:43, 15.83it/s]
 13%|#3        | 102/781 [00:06<00:42, 16.04it/s]
 13%|#3        | 104/781 [00:06<00:43, 15.70it/s]
 14%|#3        | 106/781 [00:06<00:43, 15.58it/s]
 14%|#3        | 108/781 [00:06<00:43, 15.33it/s]
 14%|#4        | 110/781 [00:06<00:44, 15.18it/s]
 14%|#4        | 112/781 [00:06<00:43, 15.48it/s]
 15%|#4        | 114/781 [00:07<00:43, 15.32it/s]
 15%|#4        | 116/781 [00:07<00:43, 15.29it/s]
 15%|#5        | 118/781 [00:07<00:42, 15.43it/s]
 15%|#5        | 120/781 [00:07<00:42, 15.57it/s]
 16%|#5        | 122/781 [00:07<00:42, 15.66it/s]
 16%|#5        | 124/781 [00:07<00:41, 15.71it/s]
 16%|#6        | 126/781 [00:07<00:41, 15.96it/s]
 16%|#6        | 128/781 [00:07<00:41, 15.73it/s]
 17%|#6        | 130/781 [00:08<00:41, 15.59it/s]
 17%|#6        | 132/781 [00:08<00:41, 15.72it/s]
 17%|#7        | 134/781 [00:08<00:41, 15.63it/s]
 17%|#7        | 136/781 [00:08<00:41, 15.68it/s]
 18%|#7        | 138/781 [00:08<00:40, 15.99it/s]
 18%|#7        | 140/781 [00:08<00:39, 16.20it/s]
 18%|#8        | 142/781 [00:08<00:39, 16.33it/s]
 18%|#8        | 144/781 [00:08<00:39, 16.23it/s]
 19%|#8        | 146/781 [00:09<00:39, 16.17it/s]
 19%|#8        | 148/781 [00:09<00:39, 15.88it/s]
 19%|#9        | 150/781 [00:09<00:39, 16.09it/s]
 19%|#9        | 152/781 [00:09<00:39, 15.82it/s]
 20%|#9        | 154/781 [00:09<00:39, 15.85it/s]
 20%|#9        | 156/781 [00:09<00:39, 15.86it/s]
 20%|##        | 158/781 [00:09<00:38, 16.13it/s]
 20%|##        | 160/781 [00:09<00:38, 16.09it/s]
 21%|##        | 162/781 [00:10<00:39, 15.84it/s]
 21%|##        | 164/781 [00:10<00:38, 15.83it/s]
 21%|##1       | 166/781 [00:10<00:39, 15.68it/s]
 22%|##1       | 168/781 [00:10<00:38, 15.77it/s]
 22%|##1       | 170/781 [00:10<00:38, 15.87it/s]
 22%|##2       | 172/781 [00:10<00:38, 15.92it/s]
 22%|##2       | 174/781 [00:10<00:38, 15.94it/s]
 23%|##2       | 176/781 [00:11<00:37, 15.99it/s]
 23%|##2       | 178/781 [00:11<00:37, 15.99it/s]
 23%|##3       | 180/781 [00:11<00:37, 16.24it/s]
 23%|##3       | 182/781 [00:11<00:37, 16.18it/s]
 24%|##3       | 184/781 [00:11<00:36, 16.17it/s]
 24%|##3       | 186/781 [00:11<00:36, 16.20it/s]
 24%|##4       | 188/781 [00:11<00:37, 15.92it/s]
 24%|##4       | 190/781 [00:11<00:36, 16.20it/s]
 25%|##4       | 192/781 [00:11<00:36, 15.98it/s]
 25%|##4       | 194/781 [00:12<00:36, 15.90it/s]
 25%|##5       | 196/781 [00:12<00:36, 15.86it/s]
 25%|##5       | 198/781 [00:12<00:36, 15.85it/s]
 26%|##5       | 200/781 [00:12<00:36, 15.81it/s]
 26%|##5       | 202/781 [00:12<00:36, 16.05it/s]
 26%|##6       | 204/781 [00:12<00:35, 16.20it/s]
 26%|##6       | 206/781 [00:12<00:35, 16.09it/s]
 27%|##6       | 208/781 [00:12<00:35, 16.00it/s]
 27%|##6       | 210/781 [00:13<00:35, 16.20it/s]
 27%|##7       | 212/781 [00:13<00:34, 16.37it/s]
 27%|##7       | 214/781 [00:13<00:34, 16.26it/s]
 28%|##7       | 216/781 [00:13<00:35, 15.94it/s]
 28%|##7       | 218/781 [00:13<00:35, 15.74it/s]
 28%|##8       | 220/781 [00:13<00:36, 15.49it/s]
 28%|##8       | 222/781 [00:13<00:35, 15.54it/s]
 29%|##8       | 224/781 [00:14<00:35, 15.56it/s]
 29%|##8       | 226/781 [00:14<00:35, 15.43it/s]
 29%|##9       | 228/781 [00:14<00:36, 15.18it/s]
 29%|##9       | 230/781 [00:14<00:36, 15.19it/s]
 30%|##9       | 232/781 [00:14<00:36, 15.20it/s]
 30%|##9       | 234/781 [00:14<00:35, 15.20it/s]
 30%|###       | 236/781 [00:14<00:35, 15.44it/s]
 30%|###       | 238/781 [00:14<00:35, 15.39it/s]
 31%|###       | 240/781 [00:15<00:35, 15.35it/s]
 31%|###       | 242/781 [00:15<00:35, 15.34it/s]
 31%|###1      | 244/781 [00:15<00:34, 15.74it/s]
 31%|###1      | 246/781 [00:15<00:33, 16.02it/s]
 32%|###1      | 248/781 [00:15<00:33, 15.95it/s]
 32%|###2      | 250/781 [00:15<00:32, 16.17it/s]
 32%|###2      | 252/781 [00:15<00:32, 16.07it/s]
 33%|###2      | 254/781 [00:15<00:33, 15.92it/s]
 33%|###2      | 256/781 [00:16<00:32, 16.11it/s]
 33%|###3      | 258/781 [00:16<00:32, 16.17it/s]
 33%|###3      | 260/781 [00:16<00:32, 16.23it/s]
 34%|###3      | 262/781 [00:16<00:42, 12.17it/s]
 34%|###3      | 264/781 [00:16<00:39, 13.14it/s]
 34%|###4      | 266/781 [00:16<00:37, 13.75it/s]
 34%|###4      | 268/781 [00:16<00:36, 14.23it/s]
 35%|###4      | 270/781 [00:17<00:35, 14.43it/s]
 35%|###4      | 272/781 [00:17<00:34, 14.75it/s]
 35%|###5      | 274/781 [00:17<00:33, 15.28it/s]
 35%|###5      | 276/781 [00:17<00:32, 15.39it/s]
 36%|###5      | 278/781 [00:17<00:32, 15.55it/s]
 36%|###5      | 280/781 [00:17<00:31, 15.73it/s]
 36%|###6      | 282/781 [00:17<00:31, 16.05it/s]
 36%|###6      | 284/781 [00:17<00:30, 16.28it/s]
 37%|###6      | 286/781 [00:18<00:30, 16.41it/s]
 37%|###6      | 288/781 [00:18<00:29, 16.51it/s]
 37%|###7      | 290/781 [00:18<00:30, 16.34it/s]
 37%|###7      | 292/781 [00:18<00:30, 16.23it/s]
 38%|###7      | 294/781 [00:18<00:29, 16.35it/s]
 38%|###7      | 296/781 [00:18<00:29, 16.48it/s]
 38%|###8      | 298/781 [00:18<00:29, 16.31it/s]
 38%|###8      | 300/781 [00:18<00:29, 16.30it/s]
 39%|###8      | 302/781 [00:19<00:29, 16.10it/s]
 39%|###8      | 304/781 [00:19<00:29, 16.28it/s]
 39%|###9      | 306/781 [00:19<00:29, 16.17it/s]
 39%|###9      | 308/781 [00:19<00:29, 16.21it/s]
 40%|###9      | 310/781 [00:19<00:28, 16.36it/s]
 40%|###9      | 312/781 [00:19<00:28, 16.19it/s]
 40%|####      | 314/781 [00:19<00:28, 16.34it/s]
 40%|####      | 316/781 [00:19<00:28, 16.46it/s]
 41%|####      | 318/781 [00:20<00:27, 16.55it/s]
 41%|####      | 320/781 [00:20<00:28, 16.37it/s]
 41%|####1     | 322/781 [00:20<00:27, 16.49it/s]
 41%|####1     | 324/781 [00:20<00:28, 16.13it/s]
 42%|####1     | 326/781 [00:20<00:28, 15.94it/s]
 42%|####1     | 328/781 [00:20<00:28, 16.11it/s]
 42%|####2     | 330/781 [00:20<00:28, 16.08it/s]
 43%|####2     | 332/781 [00:20<00:27, 16.23it/s]
 43%|####2     | 334/781 [00:21<00:28, 15.90it/s]
 43%|####3     | 336/781 [00:21<00:27, 15.90it/s]
 43%|####3     | 338/781 [00:21<00:27, 15.90it/s]
 44%|####3     | 340/781 [00:21<00:27, 15.91it/s]
 44%|####3     | 342/781 [00:21<00:27, 15.70it/s]
 44%|####4     | 344/781 [00:21<00:27, 15.99it/s]
 44%|####4     | 346/781 [00:21<00:26, 16.21it/s]
 45%|####4     | 348/781 [00:21<00:26, 16.15it/s]
 45%|####4     | 350/781 [00:22<00:27, 15.71it/s]
 45%|####5     | 352/781 [00:22<00:27, 15.74it/s]
 45%|####5     | 354/781 [00:22<00:27, 15.81it/s]
 46%|####5     | 356/781 [00:22<00:26, 15.85it/s]
 46%|####5     | 358/781 [00:22<00:26, 15.68it/s]
 46%|####6     | 360/781 [00:22<00:26, 15.99it/s]
 46%|####6     | 362/781 [00:22<00:26, 16.00it/s]
 47%|####6     | 364/781 [00:22<00:25, 16.22it/s]
 47%|####6     | 366/781 [00:23<00:25, 16.41it/s]
 47%|####7     | 368/781 [00:23<00:25, 16.06it/s]
 47%|####7     | 370/781 [00:23<00:25, 16.05it/s]
 48%|####7     | 372/781 [00:23<00:25, 16.04it/s]
 48%|####7     | 374/781 [00:23<00:25, 16.26it/s]
 48%|####8     | 376/781 [00:23<00:25, 15.92it/s]
 48%|####8     | 378/781 [00:23<00:25, 15.60it/s]
 49%|####8     | 380/781 [00:23<00:25, 15.43it/s]
 49%|####8     | 382/781 [00:24<00:25, 15.75it/s]
 49%|####9     | 384/781 [00:24<00:25, 15.82it/s]
 49%|####9     | 386/781 [00:24<00:24, 15.89it/s]
 50%|####9     | 388/781 [00:24<00:25, 15.54it/s]
 50%|####9     | 390/781 [00:24<00:25, 15.44it/s]
 50%|#####     | 392/781 [00:24<00:24, 15.71it/s]
 50%|#####     | 394/781 [00:24<00:24, 15.89it/s]
 51%|#####     | 396/781 [00:24<00:24, 15.80it/s]
 51%|#####     | 398/781 [00:25<00:23, 16.08it/s]
 51%|#####1    | 400/781 [00:25<00:24, 15.85it/s]
 51%|#####1    | 402/781 [00:25<00:23, 16.13it/s]
 52%|#####1    | 404/781 [00:25<00:23, 16.34it/s]
 52%|#####1    | 406/781 [00:25<00:23, 16.20it/s]
 52%|#####2    | 408/781 [00:25<00:22, 16.33it/s]
 52%|#####2    | 410/781 [00:25<00:22, 16.38it/s]
 53%|#####2    | 412/781 [00:25<00:23, 16.03it/s]
 53%|#####3    | 414/781 [00:26<00:23, 15.70it/s]
 53%|#####3    | 416/781 [00:26<00:23, 15.71it/s]
 54%|#####3    | 418/781 [00:26<00:22, 15.80it/s]
 54%|#####3    | 420/781 [00:26<00:22, 16.09it/s]
 54%|#####4    | 422/781 [00:26<00:22, 15.82it/s]
 54%|#####4    | 424/781 [00:26<00:22, 16.00it/s]
 55%|#####4    | 426/781 [00:26<00:22, 16.00it/s]
 55%|#####4    | 428/781 [00:26<00:21, 16.23it/s]
 55%|#####5    | 430/781 [00:27<00:21, 16.01it/s]
 55%|#####5    | 432/781 [00:27<00:21, 15.95it/s]
 56%|#####5    | 434/781 [00:27<00:21, 16.12it/s]
 56%|#####5    | 436/781 [00:27<00:21, 15.89it/s]
 56%|#####6    | 438/781 [00:27<00:21, 15.68it/s]
 56%|#####6    | 440/781 [00:27<00:21, 15.95it/s]
 57%|#####6    | 442/781 [00:27<00:21, 15.97it/s]
 57%|#####6    | 444/781 [00:27<00:20, 16.10it/s]
 57%|#####7    | 446/781 [00:28<00:20, 15.97it/s]
 57%|#####7    | 448/781 [00:28<00:20, 16.17it/s]
 58%|#####7    | 450/781 [00:28<00:20, 16.04it/s]
 58%|#####7    | 452/781 [00:28<00:20, 15.76it/s]
 58%|#####8    | 454/781 [00:28<00:20, 15.96it/s]
 58%|#####8    | 456/781 [00:28<00:20, 16.11it/s]
 59%|#####8    | 458/781 [00:28<00:19, 16.27it/s]
 59%|#####8    | 460/781 [00:28<00:19, 16.39it/s]
 59%|#####9    | 462/781 [00:29<00:19, 16.23it/s]
 59%|#####9    | 464/781 [00:29<00:19, 16.09it/s]
 60%|#####9    | 466/781 [00:29<00:19, 15.81it/s]
 60%|#####9    | 468/781 [00:29<00:20, 15.63it/s]
 60%|######    | 470/781 [00:29<00:19, 15.72it/s]
 60%|######    | 472/781 [00:29<00:19, 15.49it/s]
 61%|######    | 474/781 [00:29<00:19, 15.70it/s]
 61%|######    | 476/781 [00:29<00:19, 15.64it/s]
 61%|######1   | 478/781 [00:30<00:19, 15.63it/s]
 61%|######1   | 480/781 [00:30<00:19, 15.50it/s]
 62%|######1   | 482/781 [00:30<00:18, 15.76it/s]
 62%|######1   | 484/781 [00:30<00:19, 15.50it/s]
 62%|######2   | 486/781 [00:30<00:19, 15.50it/s]
 62%|######2   | 488/781 [00:30<00:19, 15.11it/s]
 63%|######2   | 490/781 [00:30<00:19, 15.01it/s]
 63%|######2   | 492/781 [00:30<00:19, 15.18it/s]
 63%|######3   | 494/781 [00:31<00:18, 15.17it/s]
 64%|######3   | 496/781 [00:31<00:18, 15.13it/s]
 64%|######3   | 498/781 [00:31<00:18, 15.04it/s]
 64%|######4   | 500/781 [00:31<00:18, 15.15it/s]
 64%|######4   | 502/781 [00:31<00:18, 15.22it/s]
 65%|######4   | 504/781 [00:31<00:17, 15.57it/s]
 65%|######4   | 506/781 [00:31<00:17, 15.66it/s]
 65%|######5   | 508/781 [00:32<00:17, 15.54it/s]
 65%|######5   | 510/781 [00:32<00:17, 15.43it/s]
 66%|######5   | 512/781 [00:32<00:17, 15.57it/s]
 66%|######5   | 514/781 [00:32<00:16, 15.89it/s]
 66%|######6   | 516/781 [00:32<00:16, 16.11it/s]
 66%|######6   | 518/781 [00:32<00:16, 15.85it/s]
 67%|######6   | 520/781 [00:33<00:27,  9.52it/s]
 67%|######6   | 522/781 [00:33<00:23, 10.82it/s]
 67%|######7   | 524/781 [00:33<00:21, 11.85it/s]
 67%|######7   | 526/781 [00:33<00:20, 12.70it/s]
 68%|######7   | 528/781 [00:33<00:18, 13.62it/s]
 68%|######7   | 530/781 [00:33<00:17, 14.08it/s]
 68%|######8   | 532/781 [00:33<00:16, 14.79it/s]
 68%|######8   | 534/781 [00:33<00:16, 15.27it/s]
 69%|######8   | 536/781 [00:34<00:15, 15.66it/s]
 69%|######8   | 538/781 [00:34<00:15, 15.74it/s]
 69%|######9   | 540/781 [00:34<00:15, 15.69it/s]
 69%|######9   | 542/781 [00:34<00:14, 15.94it/s]
 70%|######9   | 544/781 [00:34<00:14, 16.14it/s]
 70%|######9   | 546/781 [00:34<00:14, 16.05it/s]
 70%|#######   | 548/781 [00:34<00:14, 16.23it/s]
 70%|#######   | 550/781 [00:34<00:14, 15.81it/s]
 71%|#######   | 552/781 [00:35<00:14, 15.57it/s]
 71%|#######   | 554/781 [00:35<00:14, 15.43it/s]
 71%|#######1  | 556/781 [00:35<00:14, 15.58it/s]
 71%|#######1  | 558/781 [00:35<00:14, 15.45it/s]
 72%|#######1  | 560/781 [00:35<00:14, 15.52it/s]
 72%|#######1  | 562/781 [00:35<00:14, 15.60it/s]
 72%|#######2  | 564/781 [00:35<00:14, 15.49it/s]
 72%|#######2  | 566/781 [00:35<00:13, 15.58it/s]
 73%|#######2  | 568/781 [00:36<00:13, 15.88it/s]
 73%|#######2  | 570/781 [00:36<00:13, 15.89it/s]
 73%|#######3  | 572/781 [00:36<00:13, 15.90it/s]
 73%|#######3  | 574/781 [00:36<00:13, 15.90it/s]
 74%|#######3  | 576/781 [00:36<00:12, 15.84it/s]
 74%|#######4  | 578/781 [00:36<00:12, 16.08it/s]
 74%|#######4  | 580/781 [00:36<00:12, 15.79it/s]
 75%|#######4  | 582/781 [00:36<00:12, 15.84it/s]
 75%|#######4  | 584/781 [00:37<00:12, 15.86it/s]
 75%|#######5  | 586/781 [00:37<00:12, 15.64it/s]
 75%|#######5  | 588/781 [00:37<00:12, 15.25it/s]
 76%|#######5  | 590/781 [00:37<00:12, 15.40it/s]
 76%|#######5  | 592/781 [00:37<00:12, 15.54it/s]
 76%|#######6  | 594/781 [00:37<00:11, 15.85it/s]
 76%|#######6  | 596/781 [00:37<00:11, 15.68it/s]
 77%|#######6  | 598/781 [00:37<00:11, 15.56it/s]
 77%|#######6  | 600/781 [00:38<00:11, 15.59it/s]
 77%|#######7  | 602/781 [00:38<00:11, 15.87it/s]
 77%|#######7  | 604/781 [00:38<00:11, 15.94it/s]
 78%|#######7  | 606/781 [00:38<00:11, 15.73it/s]
 78%|#######7  | 608/781 [00:38<00:11, 15.56it/s]
 78%|#######8  | 610/781 [00:38<00:10, 15.82it/s]
 78%|#######8  | 612/781 [00:38<00:10, 15.56it/s]
 79%|#######8  | 614/781 [00:39<00:10, 15.58it/s]
 79%|#######8  | 616/781 [00:39<00:10, 15.61it/s]
 79%|#######9  | 618/781 [00:39<00:10, 15.87it/s]
 79%|#######9  | 620/781 [00:39<00:10, 16.03it/s]
 80%|#######9  | 622/781 [00:39<00:09, 16.23it/s]
 80%|#######9  | 624/781 [00:39<00:09, 16.17it/s]
 80%|########  | 626/781 [00:39<00:09, 16.21it/s]
 80%|########  | 628/781 [00:39<00:09, 16.12it/s]
 81%|########  | 630/781 [00:40<00:09, 16.05it/s]
 81%|########  | 632/781 [00:40<00:09, 16.23it/s]
 81%|########1 | 634/781 [00:40<00:09, 16.13it/s]
 81%|########1 | 636/781 [00:40<00:08, 16.32it/s]
 82%|########1 | 638/781 [00:40<00:08, 16.20it/s]
 82%|########1 | 640/781 [00:40<00:08, 16.39it/s]
 82%|########2 | 642/781 [00:40<00:08, 16.55it/s]
 82%|########2 | 644/781 [00:40<00:08, 16.35it/s]
 83%|########2 | 646/781 [00:40<00:08, 16.13it/s]
 83%|########2 | 648/781 [00:41<00:08, 16.21it/s]
 83%|########3 | 650/781 [00:41<00:08, 16.22it/s]
 83%|########3 | 652/781 [00:41<00:08, 16.04it/s]
 84%|########3 | 654/781 [00:41<00:07, 16.19it/s]
 84%|########3 | 656/781 [00:41<00:07, 16.24it/s]
 84%|########4 | 658/781 [00:41<00:07, 16.04it/s]
 85%|########4 | 660/781 [00:41<00:07, 16.22it/s]
 85%|########4 | 662/781 [00:41<00:07, 16.33it/s]
 85%|########5 | 664/781 [00:42<00:07, 15.95it/s]
 85%|########5 | 666/781 [00:42<00:07, 16.14it/s]
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=======================================================   RESTART [11-16 12:47:35]   =======================================================







=======================================================   RESTART [11-16 12:47:35]   =======================================================







=======================================================   RESTART [11-16 12:47:35]   =======================================================







=======================================================   RESTART [11-16 12:47:35]   =======================================================
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/utils/misc.py:354: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  ckpt = torch.load(all_ckpt[0], map_location='cpu')
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:

model.safetensors:   0%|          | 0.00/346M [00:00<?, ?B/s]
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model.safetensors:  85%|########4 | 294M/346M [00:01<00:00, 235MB/s]
model.safetensors:  94%|#########3| 325M/346M [00:01<00:00, 239MB/s]
model.safetensors: 100%|##########| 346M/346M [00:01<00:00, 230MB/s]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
wandb: Currently logged in as: kaiqiu. Use `wandb login --relogin` to force relogin
wandb: Tracking run with wandb version 0.18.3
wandb: Run data is saved locally in /home/user/VAR/wandb/run-20241115_204923-wpgabilv
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run autumn-river-411
wandb:  View project at https://wandb.ai/kaiqiu/VAR
wandb:  View run at https://wandb.ai/kaiqiu/VAR/runs/wpgabilv

/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_7 0.0262 ms 100.0%
  triton_mm_9 0.0269 ms 97.3%
  triton_mm_4 0.0272 ms 96.5%
  triton_mm_12 0.0277 ms 94.7%
  triton_mm_6 0.0278 ms 94.2%
  triton_mm_8 0.0278 ms 94.1%
  triton_mm_11 0.0280 ms 93.5%
  triton_mm_2 0.0284 ms 92.3%
  triton_mm_3 0.0294 ms 89.2%
  triton_mm_15 0.0295 ms 88.7%
SingleProcess AUTOTUNE benchmarking takes 2.2408 seconds and 0.0072 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_33 0.0212 ms 100.0%
  triton_mm_24 0.0227 ms 93.7%
  triton_mm_29 0.0228 ms 93.1%
  triton_mm_25 0.0232 ms 91.7%
  bias_addmm 0.0240 ms 88.4%
  triton_mm_21 0.0240 ms 88.4%
  triton_mm_19 0.0242 ms 87.9%
  triton_mm_28 0.0247 ms 86.0%
  triton_mm_18 0.0249 ms 85.2%
  triton_mm_20 0.0258 ms 82.3%
SingleProcess AUTOTUNE benchmarking takes 2.2082 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2223 ms 100.0%
  triton_mm_51 0.2265 ms 98.1%
  triton_mm_52 0.2534 ms 87.7%
  triton_mm_45 0.2652 ms 83.8%
  triton_mm_47 0.2742 ms 81.1%
  triton_mm_43 0.2772 ms 80.2%
  bias_addmm 0.3006 ms 74.0%
  triton_mm_44 0.3084 ms 72.1%
  triton_mm_48 0.3131 ms 71.0%
  addmm 0.3229 ms 68.8%
SingleProcess AUTOTUNE benchmarking takes 2.6410 seconds and 0.0093 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0901 ms 100.0%
  triton_mm_69 0.0907 ms 99.4%
  bias_addmm 0.0963 ms 93.6%
  triton_mm_64 0.0984 ms 91.6%
  triton_mm_66 0.0988 ms 91.2%
  triton_mm_71 0.1008 ms 89.4%
  triton_mm_62 0.1020 ms 88.4%
  addmm 0.1102 ms 81.8%
  triton_mm_63 0.1112 ms 81.1%
  triton_mm_67 0.1132 ms 79.6%
SingleProcess AUTOTUNE benchmarking takes 2.5080 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2947 ms 100.0%
  triton_mm_89 0.2956 ms 99.7%
  bias_addmm 0.3262 ms 90.3%
  triton_mm_90 0.3330 ms 88.5%
  triton_mm_83 0.3400 ms 86.7%
  triton_mm_81 0.3619 ms 81.4%
  triton_mm_85 0.3630 ms 81.2%
  triton_mm_82 0.4008 ms 73.5%
  triton_mm_86 0.4097 ms 71.9%
  addmm 0.4179 ms 70.5%
SingleProcess AUTOTUNE benchmarking takes 2.6231 seconds and 0.0111 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2948 ms 100.0%
  triton_mm_108 0.3056 ms 96.5%
  triton_mm_107 0.3152 ms 93.5%
  triton_mm_109 0.3251 ms 90.7%
  addmm 0.3288 ms 89.7%
  triton_mm_102 0.3556 ms 82.9%
  triton_mm_104 0.3569 ms 82.6%
  triton_mm_103 0.3698 ms 79.7%
  triton_mm_100 0.3709 ms 79.5%
  triton_mm_105 0.4067 ms 72.5%
SingleProcess AUTOTUNE benchmarking takes 2.6563 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_126 0.0212 ms 100.0%
  triton_mm_122 0.0216 ms 97.9%
  triton_mm_117 0.0227 ms 93.5%
  triton_mm_114 0.0228 ms 92.8%
  triton_mm_118 0.0230 ms 92.2%
  triton_mm_111 0.0239 ms 88.5%
  triton_mm_121 0.0247 ms 85.6%
  bias_addmm 0.0252 ms 84.2%
  triton_mm_112 0.0253 ms 83.7%
  triton_mm_113 0.0259 ms 81.9%
SingleProcess AUTOTUNE benchmarking takes 2.2099 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_181 0.2944 ms 100.0%
  triton_mm_182 0.2958 ms 99.5%
  bias_addmm 0.3264 ms 90.2%
  triton_mm_183 0.3334 ms 88.3%
  triton_mm_176 0.3406 ms 86.5%
  triton_mm_174 0.3616 ms 81.4%
  triton_mm_178 0.3635 ms 81.0%
  triton_mm_175 0.4003 ms 73.6%
  triton_mm_179 0.4102 ms 71.8%
  addmm 0.4182 ms 70.4%
SingleProcess AUTOTUNE benchmarking takes 2.6316 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2928 ms 100.0%
  triton_mm_201 0.3061 ms 95.7%
  triton_mm_200 0.3174 ms 92.2%
  triton_mm_202 0.3261 ms 89.8%
  addmm 0.3265 ms 89.7%
  triton_mm_195 0.3565 ms 82.1%
  triton_mm_197 0.3569 ms 82.0%
  triton_mm_196 0.3723 ms 78.6%
  triton_mm_193 0.3727 ms 78.5%
  triton_mm_198 0.4070 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.6477 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_219 0.0226 ms 100.0%
  triton_mm_215 0.0230 ms 98.1%
  triton_mm_211 0.0231 ms 97.8%
  triton_mm_207 0.0231 ms 97.6%
  triton_mm_214 0.0236 ms 95.7%
  triton_mm_210 0.0238 ms 94.8%
  triton_mm_204 0.0239 ms 94.4%
  triton_mm_205 0.0254 ms 88.9%
  triton_mm_206 0.0260 ms 87.1%
  bias_addmm 0.0260 ms 86.7%
SingleProcess AUTOTUNE benchmarking takes 2.1787 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_274 0.2951 ms 100.0%
  triton_mm_275 0.2960 ms 99.7%
  bias_addmm 0.3262 ms 90.4%
  triton_mm_276 0.3333 ms 88.5%
  triton_mm_269 0.3405 ms 86.6%
  triton_mm_267 0.3621 ms 81.5%
  triton_mm_271 0.3624 ms 81.4%
  triton_mm_268 0.3997 ms 73.8%
  triton_mm_272 0.4100 ms 72.0%
  addmm 0.4176 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.6498 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2928 ms 100.0%
  triton_mm_294 0.3055 ms 95.9%
  triton_mm_293 0.3166 ms 92.5%
  addmm 0.3267 ms 89.6%
  triton_mm_295 0.3269 ms 89.6%
  triton_mm_288 0.3566 ms 82.1%
  triton_mm_290 0.3572 ms 82.0%
  triton_mm_289 0.3719 ms 78.7%
  triton_mm_286 0.3725 ms 78.6%
  triton_mm_291 0.4067 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 2.6606 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_312 0.0224 ms 100.0%
  triton_mm_303 0.0227 ms 99.0%
  triton_mm_308 0.0229 ms 97.9%
  triton_mm_304 0.0230 ms 97.5%
  triton_mm_300 0.0230 ms 97.4%
  triton_mm_307 0.0236 ms 95.0%
  triton_mm_297 0.0250 ms 89.9%
  triton_mm_298 0.0253 ms 88.7%
  triton_mm_299 0.0259 ms 86.7%
  bias_addmm 0.0272 ms 82.5%
SingleProcess AUTOTUNE benchmarking takes 2.1980 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_367 0.2935 ms 100.0%
  triton_mm_368 0.2947 ms 99.6%
  bias_addmm 0.3263 ms 90.0%
  triton_mm_369 0.3339 ms 87.9%
  triton_mm_362 0.3415 ms 86.0%
  triton_mm_360 0.3621 ms 81.1%
  triton_mm_364 0.3639 ms 80.7%
  triton_mm_361 0.3993 ms 73.5%
  triton_mm_365 0.4104 ms 71.5%
  addmm 0.4183 ms 70.2%
SingleProcess AUTOTUNE benchmarking takes 2.6476 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2918 ms 100.0%
  triton_mm_387 0.3068 ms 95.1%
  triton_mm_386 0.3160 ms 92.3%
  addmm 0.3260 ms 89.5%
  triton_mm_388 0.3272 ms 89.2%
  triton_mm_381 0.3565 ms 81.9%
  triton_mm_383 0.3578 ms 81.6%
  triton_mm_382 0.3708 ms 78.7%
  triton_mm_379 0.3727 ms 78.3%
  triton_mm_384 0.4075 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6680 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_460 0.2941 ms 100.0%
  triton_mm_461 0.2953 ms 99.6%
  bias_addmm 0.3264 ms 90.1%
  triton_mm_462 0.3348 ms 87.9%
  triton_mm_455 0.3419 ms 86.0%
  triton_mm_453 0.3626 ms 81.1%
  triton_mm_457 0.3642 ms 80.8%
  addmm 0.3713 ms 79.2%
  triton_mm_454 0.4013 ms 73.3%
  triton_mm_458 0.4106 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6524 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2924 ms 100.0%
  triton_mm_480 0.3066 ms 95.4%
  triton_mm_479 0.3156 ms 92.7%
  triton_mm_481 0.3265 ms 89.6%
  addmm 0.3269 ms 89.4%
  triton_mm_474 0.3568 ms 82.0%
  triton_mm_476 0.3577 ms 81.8%
  triton_mm_475 0.3709 ms 78.8%
  triton_mm_472 0.3716 ms 78.7%
  triton_mm_477 0.4076 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6642 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_498 0.0212 ms 100.0%
  triton_mm_489 0.0227 ms 93.6%
  triton_mm_494 0.0229 ms 92.5%
  triton_mm_490 0.0230 ms 92.2%
  triton_mm_486 0.0231 ms 91.7%
  triton_mm_493 0.0236 ms 89.8%
  triton_mm_483 0.0239 ms 88.6%
  triton_mm_484 0.0241 ms 87.9%
  triton_mm_485 0.0247 ms 85.9%
  triton_mm_496 0.0272 ms 78.0%
SingleProcess AUTOTUNE benchmarking takes 2.2071 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_553 0.2940 ms 100.0%
  triton_mm_554 0.2954 ms 99.5%
  bias_addmm 0.3264 ms 90.1%
  triton_mm_555 0.3335 ms 88.1%
  triton_mm_548 0.3408 ms 86.2%
  triton_mm_546 0.3620 ms 81.2%
  triton_mm_550 0.3636 ms 80.8%
  triton_mm_547 0.3995 ms 73.6%
  triton_mm_551 0.4104 ms 71.6%
  addmm 0.4183 ms 70.3%
SingleProcess AUTOTUNE benchmarking takes 2.6489 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2924 ms 100.0%
  triton_mm_573 0.3069 ms 95.3%
  triton_mm_572 0.3170 ms 92.3%
  addmm 0.3268 ms 89.5%
  triton_mm_574 0.3270 ms 89.4%
  triton_mm_569 0.3576 ms 81.8%
  triton_mm_567 0.3579 ms 81.7%
  triton_mm_565 0.3714 ms 78.7%
  triton_mm_568 0.3715 ms 78.7%
  triton_mm_570 0.4080 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.6666 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_646 0.2940 ms 100.0%
  triton_mm_647 0.2955 ms 99.5%
  bias_addmm 0.3262 ms 90.1%
  triton_mm_648 0.3334 ms 88.2%
  triton_mm_641 0.3412 ms 86.2%
  triton_mm_639 0.3618 ms 81.3%
  triton_mm_643 0.3645 ms 80.7%
  addmm 0.3719 ms 79.1%
  triton_mm_640 0.3996 ms 73.6%
  triton_mm_644 0.4114 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 2.6512 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2930 ms 100.0%
  triton_mm_666 0.3057 ms 95.8%
  triton_mm_665 0.3167 ms 92.5%
  triton_mm_667 0.3255 ms 90.0%
  addmm 0.3275 ms 89.5%
  triton_mm_660 0.3576 ms 81.9%
  triton_mm_662 0.3584 ms 81.7%
  triton_mm_661 0.3713 ms 78.9%
  triton_mm_658 0.3715 ms 78.9%
  triton_mm_663 0.4075 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.6565 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_759 0.3060 ms 100.0%
  triton_mm_758 0.3153 ms 97.0%
  triton_mm_760 0.3251 ms 94.1%
  bias_addmm 0.3306 ms 92.5%
  triton_mm_753 0.3553 ms 86.1%
  triton_mm_755 0.3563 ms 85.9%
  addmm 0.3678 ms 83.2%
  triton_mm_754 0.3710 ms 82.5%
  triton_mm_751 0.3720 ms 82.3%
  triton_mm_756 0.4057 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.6400 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0134 ms 100.0%
  triton_mm_1606 0.0141 ms 95.0%
  triton_mm_1610 0.0150 ms 89.1%
  triton_mm_1601 0.0170 ms 78.8%
  triton_mm_1614 0.0174 ms 77.1%
  triton_mm_1599 0.0178 ms 75.2%
  mm 0.0179 ms 75.1%
  triton_mm_1605 0.0185 ms 72.6%
  triton_mm_1600 0.0189 ms 70.9%
  triton_mm_1609 0.0199 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 7.4785 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5553 ms 100.0%
  triton_mm_1632 0.5576 ms 99.6%
  triton_mm_1631 0.5615 ms 98.9%
  triton_mm_1633 0.6301 ms 88.1%
  triton_mm_1626 0.6537 ms 85.0%
  triton_mm_1628 0.6931 ms 80.1%
  addmm 0.6998 ms 79.4%
  triton_mm_1624 0.7084 ms 78.4%
  triton_mm_1629 0.7806 ms 71.1%
  triton_mm_1625 0.7828 ms 70.9%
SingleProcess AUTOTUNE benchmarking takes 11.9064 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.5286 ms 100.0%
  triton_mm_1669 0.5556 ms 95.1%
  triton_mm_1670 0.5736 ms 92.2%
  triton_mm_1671 0.5987 ms 88.3%
  triton_mm_1664 0.6691 ms 79.0%
  triton_mm_1666 0.6830 ms 77.4%
  triton_mm_1662 0.6856 ms 77.1%
  triton_mm_1665 0.7226 ms 73.2%
  triton_mm_1667 0.7303 ms 72.4%
  triton_mm_1663 0.7409 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 9.8134 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2899 ms 100.0%
  triton_mm_1742 0.2960 ms 97.9%
  triton_mm_1741 0.2979 ms 97.3%
  triton_mm_1743 0.3021 ms 96.0%
  triton_mm_1736 0.3538 ms 81.9%
  triton_mm_1734 0.3562 ms 81.4%
  triton_mm_1738 0.3639 ms 79.7%
  triton_mm_1737 0.3792 ms 76.4%
  triton_mm_1739 0.3995 ms 72.6%
  triton_mm_1735 0.4054 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 10.0934 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1697 0.0117 ms 100.0%
  triton_mm_1694 0.0119 ms 98.1%
  triton_mm_1701 0.0119 ms 97.9%
  triton_mm_1693 0.0124 ms 94.1%
  triton_mm_1696 0.0124 ms 94.1%
  triton_mm_1699 0.0124 ms 93.8%
  triton_mm_1695 0.0126 ms 92.9%
  triton_mm_1700 0.0126 ms 92.6%
  triton_mm_1692 0.0128 ms 91.3%
  triton_mm_1702 0.0128 ms 91.0%
SingleProcess AUTOTUNE benchmarking takes 6.0993 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0168 ms 100.0%
  mm 0.0173 ms 97.2%
  triton_mm_1680 0.0177 ms 94.9%
  triton_mm_1684 0.0202 ms 83.5%
  triton_mm_1675 0.0224 ms 75.3%
  triton_mm_1688 0.0234 ms 72.0%
  triton_mm_1674 0.0239 ms 70.5%
  triton_mm_1679 0.0254 ms 66.3%
  triton_mm_1683 0.0259 ms 64.9%
  triton_mm_1673 0.0264 ms 63.8%
SingleProcess AUTOTUNE benchmarking takes 7.7639 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5407 ms 100.0%
  triton_mm_1650 0.5685 ms 95.1%
  triton_mm_1651 0.5792 ms 93.4%
  triton_mm_1652 0.5914 ms 91.4%
  triton_mm_1645 0.6615 ms 81.7%
  triton_mm_1647 0.6669 ms 81.1%
  triton_mm_1643 0.6679 ms 81.0%
  triton_mm_1646 0.6971 ms 77.6%
  triton_mm_1644 0.7233 ms 74.8%
  triton_mm_1648 0.7335 ms 73.7%
SingleProcess AUTOTUNE benchmarking takes 9.7050 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2776 ms 100.0%
  triton_mm_1723 0.2790 ms 99.5%
  mm 0.2813 ms 98.7%
  triton_mm_1724 0.3156 ms 88.0%
  triton_mm_1715 0.3409 ms 81.4%
  triton_mm_1717 0.3435 ms 80.8%
  triton_mm_1719 0.3468 ms 80.0%
  triton_mm_1716 0.3629 ms 76.5%
  triton_mm_1720 0.3850 ms 72.1%
  triton_mm_1718 0.4196 ms 66.2%
SingleProcess AUTOTUNE benchmarking takes 10.3677 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2246 ms 100.0%
  triton_mm_1836 0.2300 ms 97.6%
  triton_mm_1838 0.2418 ms 92.9%
  mm 0.2571 ms 87.4%
  triton_mm_1833 0.2571 ms 87.4%
  triton_mm_1831 0.2619 ms 85.8%
  triton_mm_1829 0.2627 ms 85.5%
  triton_mm_1832 0.2864 ms 78.4%
  triton_mm_1830 0.2900 ms 77.4%
  triton_mm_1834 0.2972 ms 75.6%
SingleProcess AUTOTUNE benchmarking takes 9.8399 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2885 ms 100.0%
  mm 0.2930 ms 98.5%
  triton_mm_1780 0.2940 ms 98.1%
  triton_mm_1781 0.3011 ms 95.8%
  triton_mm_1776 0.3450 ms 83.6%
  triton_mm_1772 0.3530 ms 81.7%
  triton_mm_1774 0.3568 ms 80.8%
  triton_mm_1775 0.3826 ms 75.4%
  triton_mm_1777 0.3915 ms 73.7%
  triton_mm_1773 0.3992 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.5355 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2251 ms 100.0%
  triton_mm_1855 0.2786 ms 80.8%
  triton_mm_1850 0.2836 ms 79.4%
  triton_mm_1852 0.2838 ms 79.3%
  triton_mm_1856 0.2855 ms 78.8%
  triton_mm_1848 0.2867 ms 78.5%
  triton_mm_1857 0.2887 ms 78.0%
  triton_mm_1851 0.3116 ms 72.2%
  triton_mm_1853 0.3252 ms 69.2%
  triton_mm_1849 0.3304 ms 68.1%
SingleProcess AUTOTUNE benchmarking takes 9.9820 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0971 ms 100.0%
  triton_mm_1819 0.0989 ms 98.2%
  triton_mm_1812 0.1043 ms 93.1%
  triton_mm_1818 0.1085 ms 89.6%
  triton_mm_1809 0.1181 ms 82.2%
  triton_mm_1810 0.1184 ms 82.0%
  triton_mm_1814 0.1197 ms 81.1%
  triton_mm_1817 0.1200 ms 81.0%
  triton_mm_1813 0.1279 ms 76.0%
  triton_mm_1815 0.1317 ms 73.8%
SingleProcess AUTOTUNE benchmarking takes 9.8169 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3014 ms 100.0%
  triton_mm_1760 0.3031 ms 99.5%
  triton_mm_1761 0.3106 ms 97.0%
  triton_mm_1762 0.3195 ms 94.3%
  triton_mm_1757 0.3448 ms 87.4%
  triton_mm_1755 0.3484 ms 86.5%
  triton_mm_1753 0.3505 ms 86.0%
  triton_mm_1756 0.3649 ms 82.6%
  triton_mm_1754 0.3860 ms 78.1%
  triton_mm_1758 0.3942 ms 76.5%
SingleProcess AUTOTUNE benchmarking takes 9.6615 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0838 ms 100.0%
  mm 0.0848 ms 98.8%
  triton_mm_1798 0.0852 ms 98.3%
  triton_mm_1795 0.0922 ms 90.9%
  triton_mm_1791 0.0942 ms 88.9%
  triton_mm_1793 0.0948 ms 88.3%
  triton_mm_1800 0.0950 ms 88.1%
  triton_mm_1792 0.1018 ms 82.3%
  triton_mm_1796 0.1051 ms 79.7%
  triton_mm_1794 0.1226 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 10.1015 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2770 ms 100.0%
  triton_mm_1909 0.2799 ms 99.0%
  mm 0.2801 ms 98.9%
  triton_mm_1910 0.3178 ms 87.2%
  triton_mm_1901 0.3396 ms 81.6%
  triton_mm_1903 0.3422 ms 81.0%
  triton_mm_1905 0.3471 ms 79.8%
  triton_mm_1902 0.3633 ms 76.2%
  triton_mm_1906 0.3854 ms 71.9%
  triton_mm_1904 0.4236 ms 65.4%
SingleProcess AUTOTUNE benchmarking takes 2.5265 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1884 0.0177 ms 100.0%
  triton_mm_1881 0.0179 ms 99.3%
  triton_mm_1883 0.0179 ms 99.3%
  triton_mm_1887 0.0180 ms 98.8%
  triton_mm_1880 0.0187 ms 95.0%
  triton_mm_1882 0.0187 ms 94.7%
  triton_mm_1885 0.0188 ms 94.5%
  triton_mm_1890 0.0188 ms 94.4%
  triton_mm_1886 0.0188 ms 94.1%
  triton_mm_1888 0.0197 ms 89.9%
SingleProcess AUTOTUNE benchmarking takes 5.8798 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2924 ms 100.0%
  triton_mm_1928 0.2973 ms 98.4%
  triton_mm_1927 0.2977 ms 98.2%
  triton_mm_1929 0.3031 ms 96.5%
  triton_mm_1922 0.3526 ms 82.9%
  triton_mm_1920 0.3564 ms 82.0%
  triton_mm_1924 0.3640 ms 80.3%
  triton_mm_1923 0.3804 ms 76.9%
  triton_mm_1925 0.4011 ms 72.9%
  triton_mm_1921 0.4051 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 2.5375 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0268 ms 100.0%
  mm 0.0272 ms 98.7%
  triton_mm_1866 0.0308 ms 86.9%
  triton_mm_1870 0.0404 ms 66.3%
  triton_mm_1861 0.0516 ms 51.9%
  triton_mm_1874 0.0519 ms 51.7%
  triton_mm_1860 0.0555 ms 48.3%
  triton_mm_1865 0.0598 ms 44.9%
  triton_mm_1869 0.0629 ms 42.6%
  triton_mm_1859 0.0660 ms 40.6%
SingleProcess AUTOTUNE benchmarking takes 6.5877 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2264 ms 100.0%
  triton_mm_2041 0.2772 ms 81.7%
  triton_mm_2036 0.2832 ms 80.0%
  triton_mm_2042 0.2842 ms 79.7%
  triton_mm_2038 0.2859 ms 79.2%
  triton_mm_2034 0.2861 ms 79.1%
  triton_mm_2043 0.2893 ms 78.3%
  triton_mm_2037 0.3127 ms 72.4%
  triton_mm_2039 0.3249 ms 69.7%
  triton_mm_2035 0.3308 ms 68.4%
SingleProcess AUTOTUNE benchmarking takes 2.5054 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0975 ms 100.0%
  triton_mm_2005 0.0992 ms 98.3%
  triton_mm_1998 0.1053 ms 92.6%
  triton_mm_2004 0.1083 ms 90.0%
  triton_mm_1995 0.1180 ms 82.6%
  triton_mm_1996 0.1196 ms 81.5%
  triton_mm_2000 0.1200 ms 81.2%
  triton_mm_2003 0.1224 ms 79.6%
  triton_mm_1999 0.1272 ms 76.6%
  triton_mm_2001 0.1310 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.4130 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2228 ms 100.0%
  triton_mm_2023 0.2254 ms 98.9%
  triton_mm_2022 0.2307 ms 96.6%
  triton_mm_2024 0.2426 ms 91.9%
  triton_mm_2019 0.2580 ms 86.4%
  triton_mm_2017 0.2624 ms 84.9%
  triton_mm_2015 0.2642 ms 84.3%
  triton_mm_2018 0.2870 ms 77.6%
  triton_mm_2016 0.2903 ms 76.8%
  triton_mm_2020 0.2966 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5083 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2094 0.2762 ms 100.0%
  mm 0.2800 ms 98.6%
  triton_mm_2095 0.2806 ms 98.4%
  triton_mm_2096 0.3182 ms 86.8%
  triton_mm_2089 0.3410 ms 81.0%
  triton_mm_2087 0.3412 ms 80.9%
  triton_mm_2091 0.3481 ms 79.3%
  triton_mm_2088 0.3643 ms 75.8%
  triton_mm_2092 0.3859 ms 71.6%
  triton_mm_2090 0.4218 ms 65.5%
SingleProcess AUTOTUNE benchmarking takes 2.5263 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2072 0.0178 ms 100.0%
  triton_mm_2070 0.0178 ms 99.8%
  triton_mm_2067 0.0186 ms 95.7%
  triton_mm_2069 0.0189 ms 94.1%
  triton_mm_2076 0.0189 ms 94.1%
  triton_mm_2073 0.0190 ms 93.6%
  triton_mm_2074 0.0194 ms 91.7%
  triton_mm_2071 0.0197 ms 90.3%
  triton_mm_2066 0.0198 ms 89.7%
  triton_mm_2068 0.0201 ms 88.5%
SingleProcess AUTOTUNE benchmarking takes 2.1221 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2911 ms 100.0%
  triton_mm_2114 0.2963 ms 98.3%
  triton_mm_2113 0.2984 ms 97.5%
  triton_mm_2115 0.3021 ms 96.4%
  triton_mm_2108 0.3539 ms 82.3%
  triton_mm_2106 0.3574 ms 81.4%
  triton_mm_2110 0.3651 ms 79.7%
  triton_mm_2109 0.3798 ms 76.6%
  triton_mm_2111 0.4019 ms 72.4%
  triton_mm_2107 0.4061 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.5369 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2048 0.0268 ms 100.0%
  mm 0.0270 ms 99.4%
  triton_mm_2052 0.0323 ms 83.2%
  triton_mm_2056 0.0417 ms 64.4%
  triton_mm_2060 0.0511 ms 52.5%
  triton_mm_2047 0.0524 ms 51.2%
  triton_mm_2046 0.0556 ms 48.3%
  triton_mm_2051 0.0598 ms 44.9%
  triton_mm_2055 0.0620 ms 43.3%
  triton_mm_2045 0.0652 ms 41.2%
SingleProcess AUTOTUNE benchmarking takes 2.0865 seconds and 0.0003 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2280 0.2774 ms 100.0%
  triton_mm_2281 0.2799 ms 99.1%
  mm 0.2803 ms 99.0%
  triton_mm_2282 0.3173 ms 87.4%
  triton_mm_2273 0.3401 ms 81.6%
  triton_mm_2275 0.3423 ms 81.0%
  triton_mm_2277 0.3469 ms 80.0%
  triton_mm_2274 0.3631 ms 76.4%
  triton_mm_2278 0.3847 ms 72.1%
  triton_mm_2276 0.4228 ms 65.6%
SingleProcess AUTOTUNE benchmarking takes 2.5297 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2256 0.0178 ms 100.0%
  triton_mm_2253 0.0179 ms 99.3%
  triton_mm_2255 0.0179 ms 99.3%
  triton_mm_2259 0.0180 ms 98.9%
  triton_mm_2258 0.0186 ms 95.7%
  triton_mm_2260 0.0187 ms 95.2%
  triton_mm_2252 0.0187 ms 95.0%
  triton_mm_2254 0.0188 ms 94.7%
  triton_mm_2257 0.0188 ms 94.6%
  triton_mm_2262 0.0198 ms 90.0%
SingleProcess AUTOTUNE benchmarking takes 2.1238 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2899 ms 100.0%
  triton_mm_2300 0.2977 ms 97.4%
  triton_mm_2299 0.2979 ms 97.3%
  triton_mm_2301 0.3026 ms 95.8%
  triton_mm_2294 0.3541 ms 81.9%
  triton_mm_2292 0.3572 ms 81.2%
  triton_mm_2296 0.3650 ms 79.4%
  triton_mm_2295 0.3797 ms 76.3%
  triton_mm_2297 0.3996 ms 72.5%
  triton_mm_2293 0.4067 ms 71.3%
SingleProcess AUTOTUNE benchmarking takes 2.5324 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2234 0.0268 ms 100.0%
  mm 0.0271 ms 99.1%
  triton_mm_2238 0.0309 ms 86.9%
  triton_mm_2242 0.0410 ms 65.5%
  triton_mm_2246 0.0511 ms 52.5%
  triton_mm_2233 0.0524 ms 51.3%
  triton_mm_2232 0.0555 ms 48.4%
  triton_mm_2237 0.0598 ms 44.9%
  triton_mm_2241 0.0620 ms 43.3%
  triton_mm_2231 0.0652 ms 41.2%
SingleProcess AUTOTUNE benchmarking takes 2.0810 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2607 ms 100.0%
  triton_mm_2413 0.2780 ms 93.8%
  triton_mm_2408 0.2822 ms 92.4%
  triton_mm_2410 0.2829 ms 92.2%
  triton_mm_2414 0.2850 ms 91.5%
  triton_mm_2406 0.2871 ms 90.8%
  triton_mm_2415 0.2887 ms 90.3%
  triton_mm_2409 0.3111 ms 83.8%
  triton_mm_2411 0.3253 ms 80.2%
  triton_mm_2407 0.3305 ms 78.9%
SingleProcess AUTOTUNE benchmarking takes 2.5013 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0975 ms 100.0%
  triton_mm_2377 0.0992 ms 98.3%
  triton_mm_2370 0.1055 ms 92.4%
  triton_mm_2376 0.1081 ms 90.2%
  triton_mm_2367 0.1179 ms 82.7%
  triton_mm_2368 0.1198 ms 81.4%
  triton_mm_2372 0.1207 ms 80.8%
  triton_mm_2375 0.1225 ms 79.6%
  triton_mm_2371 0.1274 ms 76.5%
  triton_mm_2373 0.1310 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.4340 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2235 ms 100.0%
  triton_mm_2395 0.2243 ms 99.6%
  triton_mm_2394 0.2315 ms 96.5%
  triton_mm_2396 0.2435 ms 91.8%
  triton_mm_2391 0.2564 ms 87.2%
  triton_mm_2387 0.2627 ms 85.1%
  triton_mm_2389 0.2630 ms 85.0%
  triton_mm_2390 0.2872 ms 77.8%
  triton_mm_2388 0.2911 ms 76.8%
  triton_mm_2392 0.2973 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5175 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0279 ms 100.0%
  triton_mm_4872 0.0507 ms 55.1%
  triton_mm_4879 0.0508 ms 55.0%
  triton_mm_4870 0.0561 ms 49.8%
  triton_mm_4871 0.0642 ms 43.5%
  triton_mm_4878 0.0675 ms 41.4%
  triton_mm_4875 0.0707 ms 39.5%
  triton_mm_4884 0.0745 ms 37.5%
  triton_mm_4883 0.0747 ms 37.4%
  triton_mm_4877 0.0775 ms 36.0%
SingleProcess AUTOTUNE benchmarking takes 6.4796 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_8 0.0267 ms 100.0%
  triton_mm_4 0.0268 ms 99.8%
  triton_mm_9 0.0268 ms 99.8%
  triton_mm_7 0.0269 ms 99.3%
  triton_mm_6 0.0276 ms 96.5%
  triton_mm_11 0.0277 ms 96.2%
  triton_mm_3 0.0280 ms 95.4%
  triton_mm_12 0.0280 ms 95.2%
  triton_mm_2 0.0291 ms 91.6%
  triton_mm_5 0.0299 ms 89.4%
SingleProcess AUTOTUNE benchmarking takes 2.2614 seconds and 0.0144 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_33 0.0222 ms 100.0%
  triton_mm_24 0.0225 ms 98.7%
  triton_mm_29 0.0228 ms 97.5%
  triton_mm_25 0.0228 ms 97.2%
  triton_mm_21 0.0236 ms 93.9%
  triton_mm_18 0.0238 ms 93.3%
  bias_addmm 0.0239 ms 92.9%
  triton_mm_28 0.0244 ms 90.9%
  triton_mm_20 0.0245 ms 90.5%
  triton_mm_19 0.0250 ms 88.7%
SingleProcess AUTOTUNE benchmarking takes 2.2067 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2240 ms 100.0%
  triton_mm_51 0.2281 ms 98.2%
  triton_mm_52 0.2566 ms 87.3%
  triton_mm_45 0.2651 ms 84.5%
  triton_mm_47 0.2748 ms 81.5%
  triton_mm_43 0.2776 ms 80.7%
  bias_addmm 0.3003 ms 74.6%
  triton_mm_44 0.3092 ms 72.4%
  triton_mm_48 0.3129 ms 71.6%
  addmm 0.3227 ms 69.4%
SingleProcess AUTOTUNE benchmarking takes 2.5834 seconds and 0.0168 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0903 ms 100.0%
  triton_mm_69 0.0906 ms 99.7%
  bias_addmm 0.0959 ms 94.1%
  triton_mm_66 0.0980 ms 92.2%
  triton_mm_64 0.0983 ms 91.9%
  triton_mm_71 0.1004 ms 89.9%
  triton_mm_62 0.1012 ms 89.2%
  addmm 0.1099 ms 82.2%
  triton_mm_63 0.1126 ms 80.2%
  triton_mm_67 0.1134 ms 79.7%
SingleProcess AUTOTUNE benchmarking takes 2.5051 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2956 ms 100.0%
  triton_mm_89 0.2971 ms 99.5%
  bias_addmm 0.3275 ms 90.3%
  triton_mm_90 0.3353 ms 88.2%
  triton_mm_83 0.3416 ms 86.5%
  triton_mm_85 0.3646 ms 81.1%
  triton_mm_81 0.3652 ms 80.9%
  triton_mm_82 0.4038 ms 73.2%
  triton_mm_86 0.4151 ms 71.2%
  addmm 0.4184 ms 70.6%
SingleProcess AUTOTUNE benchmarking takes 2.6525 seconds and 0.0054 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2922 ms 100.0%
  triton_mm_108 0.3076 ms 95.0%
  triton_mm_107 0.3163 ms 92.4%
  addmm 0.3251 ms 89.9%
  triton_mm_109 0.3264 ms 89.5%
  triton_mm_104 0.3566 ms 81.9%
  triton_mm_102 0.3594 ms 81.3%
  triton_mm_100 0.3722 ms 78.5%
  triton_mm_103 0.3730 ms 78.3%
  triton_mm_105 0.4079 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6528 seconds and 0.0008 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_126 0.0222 ms 100.0%
  triton_mm_122 0.0228 ms 97.7%
  triton_mm_118 0.0231 ms 96.1%
  triton_mm_117 0.0235 ms 94.7%
  triton_mm_121 0.0235 ms 94.6%
  triton_mm_114 0.0237 ms 93.9%
  triton_mm_112 0.0241 ms 92.3%
  triton_mm_113 0.0246 ms 90.5%
  triton_mm_111 0.0247 ms 89.9%
  bias_addmm 0.0249 ms 89.2%
SingleProcess AUTOTUNE benchmarking takes 2.1995 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_201 0.3072 ms 100.0%
  triton_mm_200 0.3160 ms 97.2%
  triton_mm_202 0.3263 ms 94.1%
  addmm 0.3279 ms 93.7%
  bias_addmm 0.3302 ms 93.0%
  triton_mm_197 0.3567 ms 86.1%
  triton_mm_195 0.3594 ms 85.5%
  triton_mm_196 0.3712 ms 82.8%
  triton_mm_193 0.3731 ms 82.3%
  triton_mm_198 0.4081 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.6400 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_294 0.3056 ms 100.0%
  triton_mm_293 0.3162 ms 96.6%
  addmm 0.3248 ms 94.1%
  triton_mm_295 0.3261 ms 93.7%
  bias_addmm 0.3306 ms 92.4%
  triton_mm_290 0.3551 ms 86.1%
  triton_mm_288 0.3575 ms 85.5%
  triton_mm_286 0.3709 ms 82.4%
  triton_mm_289 0.3712 ms 82.3%
  triton_mm_291 0.4066 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.6404 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0132 ms 100.0%
  triton_mm_1606 0.0138 ms 95.4%
  triton_mm_1610 0.0147 ms 89.6%
  triton_mm_1614 0.0158 ms 83.2%
  triton_mm_1601 0.0167 ms 78.9%
  mm 0.0176 ms 75.0%
  triton_mm_1599 0.0176 ms 74.9%
  triton_mm_1605 0.0181 ms 72.7%
  triton_mm_1600 0.0182 ms 72.3%
  triton_mm_1609 0.0196 ms 67.2%
SingleProcess AUTOTUNE benchmarking takes 7.3236 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5518 ms 100.0%
  triton_mm_1632 0.5559 ms 99.3%
  triton_mm_1631 0.5606 ms 98.4%
  triton_mm_1633 0.6288 ms 87.8%
  triton_mm_1626 0.6516 ms 84.7%
  triton_mm_1628 0.6889 ms 80.1%
  addmm 0.6985 ms 79.0%
  triton_mm_1624 0.7069 ms 78.1%
  triton_mm_1625 0.7753 ms 71.2%
  triton_mm_1629 0.7770 ms 71.0%
SingleProcess AUTOTUNE benchmarking takes 11.1434 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5522 ms 100.0%
  triton_mm_1670 0.5743 ms 96.2%
  mm 0.5873 ms 94.0%
  triton_mm_1671 0.5984 ms 92.3%
  triton_mm_1664 0.6665 ms 82.9%
  triton_mm_1666 0.6766 ms 81.6%
  triton_mm_1662 0.6780 ms 81.4%
  triton_mm_1665 0.7231 ms 76.4%
  triton_mm_1667 0.7261 ms 76.0%
  triton_mm_1663 0.7420 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.5661 seconds and 0.0193 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2896 ms 100.0%
  triton_mm_1742 0.2957 ms 97.9%
  triton_mm_1741 0.2976 ms 97.3%
  triton_mm_1743 0.3008 ms 96.3%
  triton_mm_1736 0.3526 ms 82.1%
  triton_mm_1734 0.3543 ms 81.8%
  triton_mm_1738 0.3630 ms 79.8%
  triton_mm_1737 0.3785 ms 76.5%
  triton_mm_1739 0.3979 ms 72.8%
  triton_mm_1735 0.4041 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.5392 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1696 0.0116 ms 100.0%
  triton_mm_1695 0.0117 ms 98.4%
  triton_mm_1697 0.0117 ms 98.4%
  triton_mm_1694 0.0118 ms 98.1%
  triton_mm_1702 0.0119 ms 96.8%
  triton_mm_1701 0.0120 ms 96.3%
  triton_mm_1698 0.0122 ms 94.8%
  triton_mm_1700 0.0122 ms 94.8%
  triton_mm_1699 0.0124 ms 93.5%
  triton_mm_1691 0.0128 ms 90.3%
SingleProcess AUTOTUNE benchmarking takes 2.1277 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0163 ms 100.0%
  mm 0.0171 ms 95.1%
  triton_mm_1680 0.0173 ms 94.1%
  triton_mm_1684 0.0204 ms 80.0%
  triton_mm_1675 0.0229 ms 71.2%
  triton_mm_1688 0.0234 ms 69.5%
  triton_mm_1674 0.0243 ms 67.0%
  triton_mm_1679 0.0258 ms 63.2%
  triton_mm_1673 0.0260 ms 62.8%
  triton_mm_1683 0.0262 ms 62.3%
SingleProcess AUTOTUNE benchmarking takes 2.1298 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5354 ms 100.0%
  triton_mm_1650 0.5623 ms 95.2%
  triton_mm_1651 0.5702 ms 93.9%
  triton_mm_1652 0.5849 ms 91.5%
  triton_mm_1647 0.6501 ms 82.4%
  triton_mm_1645 0.6527 ms 82.0%
  triton_mm_1643 0.6593 ms 81.2%
  triton_mm_1646 0.6868 ms 78.0%
  triton_mm_1644 0.7135 ms 75.0%
  triton_mm_1648 0.7247 ms 73.9%
SingleProcess AUTOTUNE benchmarking takes 9.5707 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2762 ms 100.0%
  mm 0.2763 ms 100.0%
  triton_mm_1723 0.2782 ms 99.3%
  triton_mm_1724 0.3149 ms 87.7%
  triton_mm_1715 0.3385 ms 81.6%
  triton_mm_1717 0.3411 ms 81.0%
  triton_mm_1719 0.3450 ms 80.1%
  triton_mm_1716 0.3614 ms 76.4%
  triton_mm_1720 0.3800 ms 72.7%
  triton_mm_1718 0.4189 ms 65.9%
SingleProcess AUTOTUNE benchmarking takes 10.3254 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2236 ms 100.0%
  triton_mm_1836 0.2289 ms 97.7%
  triton_mm_1838 0.2411 ms 92.7%
  triton_mm_1833 0.2560 ms 87.3%
  mm 0.2577 ms 86.8%
  triton_mm_1831 0.2605 ms 85.8%
  triton_mm_1829 0.2627 ms 85.1%
  triton_mm_1832 0.2857 ms 78.3%
  triton_mm_1830 0.2887 ms 77.4%
  triton_mm_1834 0.2955 ms 75.7%
SingleProcess AUTOTUNE benchmarking takes 9.7220 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2898 ms 100.0%
  mm 0.2906 ms 99.7%
  triton_mm_1780 0.2936 ms 98.7%
  triton_mm_1781 0.2998 ms 96.7%
  triton_mm_1776 0.3449 ms 84.0%
  triton_mm_1772 0.3519 ms 82.3%
  triton_mm_1774 0.3559 ms 81.4%
  triton_mm_1775 0.3822 ms 75.8%
  triton_mm_1777 0.3917 ms 74.0%
  triton_mm_1773 0.3990 ms 72.6%
SingleProcess AUTOTUNE benchmarking takes 2.5373 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2230 ms 100.0%
  triton_mm_1855 0.2771 ms 80.5%
  triton_mm_1850 0.2828 ms 78.9%
  triton_mm_1856 0.2837 ms 78.6%
  triton_mm_1852 0.2838 ms 78.6%
  triton_mm_1848 0.2871 ms 77.7%
  triton_mm_1857 0.2876 ms 77.5%
  triton_mm_1851 0.3122 ms 71.4%
  triton_mm_1853 0.3242 ms 68.8%
  triton_mm_1849 0.3300 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.5104 seconds and 0.0008 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0967 ms 100.0%
  triton_mm_1819 0.0984 ms 98.2%
  triton_mm_1812 0.1041 ms 92.9%
  triton_mm_1818 0.1079 ms 89.6%
  triton_mm_1809 0.1182 ms 81.8%
  triton_mm_1810 0.1185 ms 81.6%
  triton_mm_1814 0.1197 ms 80.8%
  triton_mm_1817 0.1208 ms 80.0%
  triton_mm_1813 0.1260 ms 76.8%
  triton_mm_1815 0.1300 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.4183 seconds and 0.0009 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2990 ms 100.0%
  triton_mm_1760 0.3033 ms 98.6%
  triton_mm_1761 0.3119 ms 95.9%
  triton_mm_1762 0.3214 ms 93.0%
  triton_mm_1757 0.3439 ms 86.9%
  triton_mm_1755 0.3494 ms 85.6%
  triton_mm_1753 0.3507 ms 85.3%
  triton_mm_1756 0.3659 ms 81.7%
  triton_mm_1754 0.3857 ms 77.5%
  triton_mm_1758 0.3948 ms 75.7%
SingleProcess AUTOTUNE benchmarking takes 2.5326 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0833 ms 100.0%
  mm 0.0838 ms 99.4%
  triton_mm_1798 0.0851 ms 97.9%
  triton_mm_1795 0.0918 ms 90.8%
  triton_mm_1791 0.0942 ms 88.4%
  triton_mm_1800 0.0944 ms 88.3%
  triton_mm_1793 0.0954 ms 87.4%
  triton_mm_1792 0.1024 ms 81.4%
  triton_mm_1796 0.1057 ms 78.8%
  triton_mm_1794 0.1231 ms 67.7%
SingleProcess AUTOTUNE benchmarking takes 2.4168 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1908 0.2769 ms 100.0%
  triton_mm_1909 0.2792 ms 99.2%
  triton_mm_1910 0.3174 ms 87.2%
  mm 0.3199 ms 86.6%
  triton_mm_1901 0.3387 ms 81.7%
  triton_mm_1903 0.3409 ms 81.2%
  triton_mm_1905 0.3464 ms 79.9%
  triton_mm_1902 0.3620 ms 76.5%
  triton_mm_1906 0.3851 ms 71.9%
  triton_mm_1904 0.4240 ms 65.3%
SingleProcess AUTOTUNE benchmarking takes 2.5261 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2986 ms 100.0%
  triton_mm_1946 0.3034 ms 98.4%
  triton_mm_1947 0.3101 ms 96.3%
  triton_mm_1948 0.3197 ms 93.4%
  triton_mm_1943 0.3432 ms 87.0%
  triton_mm_1941 0.3493 ms 85.5%
  triton_mm_1939 0.3506 ms 85.2%
  triton_mm_1942 0.3648 ms 81.8%
  triton_mm_1940 0.3854 ms 77.5%
  triton_mm_1944 0.3945 ms 75.7%
SingleProcess AUTOTUNE benchmarking takes 2.5317 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1881 0.0175 ms 100.0%
  triton_mm_1884 0.0177 ms 99.1%
  triton_mm_1886 0.0177 ms 99.1%
  triton_mm_1883 0.0182 ms 96.4%
  triton_mm_1888 0.0182 ms 96.1%
  triton_mm_1887 0.0183 ms 95.6%
  triton_mm_1880 0.0191 ms 91.8%
  triton_mm_1890 0.0194 ms 90.6%
  triton_mm_1882 0.0194 ms 90.3%
  triton_mm_1885 0.0194 ms 90.3%
SingleProcess AUTOTUNE benchmarking takes 5.7516 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2895 ms 100.0%
  triton_mm_1928 0.2965 ms 97.6%
  triton_mm_1927 0.2981 ms 97.1%
  triton_mm_1929 0.3019 ms 95.9%
  triton_mm_1922 0.3539 ms 81.8%
  triton_mm_1920 0.3546 ms 81.7%
  triton_mm_1924 0.3637 ms 79.6%
  triton_mm_1923 0.3802 ms 76.2%
  triton_mm_1925 0.3988 ms 72.6%
  triton_mm_1921 0.4051 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 2.5357 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0265 ms 100.0%
  mm 0.0269 ms 98.6%
  triton_mm_1866 0.0316 ms 83.8%
  triton_mm_1870 0.0398 ms 66.6%
  triton_mm_1874 0.0508 ms 52.3%
  triton_mm_1861 0.0515 ms 51.5%
  triton_mm_1860 0.0553 ms 47.9%
  triton_mm_1865 0.0595 ms 44.6%
  triton_mm_1869 0.0620 ms 42.8%
  triton_mm_1859 0.0657 ms 40.4%
SingleProcess AUTOTUNE benchmarking takes 2.0841 seconds and 0.0007 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2231 ms 100.0%
  triton_mm_2041 0.2769 ms 80.6%
  triton_mm_2036 0.2827 ms 78.9%
  triton_mm_2038 0.2843 ms 78.5%
  triton_mm_2042 0.2848 ms 78.3%
  triton_mm_2034 0.2868 ms 77.8%
  triton_mm_2043 0.2898 ms 77.0%
  triton_mm_2037 0.3123 ms 71.4%
  triton_mm_2039 0.3258 ms 68.5%
  triton_mm_2035 0.3302 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.5169 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_2005 0.0992 ms 97.8%
  triton_mm_1998 0.1050 ms 92.4%
  triton_mm_2004 0.1086 ms 89.4%
  triton_mm_1995 0.1176 ms 82.5%
  triton_mm_2000 0.1196 ms 81.1%
  triton_mm_1996 0.1200 ms 80.9%
  triton_mm_2003 0.1225 ms 79.2%
  triton_mm_1999 0.1270 ms 76.4%
  triton_mm_2001 0.1308 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.4143 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0830 ms 100.0%
  triton_mm_1985 0.0841 ms 98.7%
  triton_mm_1984 0.0859 ms 96.7%
  triton_mm_1981 0.0927 ms 89.5%
  triton_mm_1986 0.0939 ms 88.4%
  triton_mm_1979 0.0947 ms 87.7%
  triton_mm_1977 0.0952 ms 87.2%
  triton_mm_1978 0.1018 ms 81.6%
  triton_mm_1982 0.1049 ms 79.1%
  triton_mm_1980 0.1239 ms 67.0%
SingleProcess AUTOTUNE benchmarking takes 2.4104 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2236 ms 100.0%
  triton_mm_2023 0.2246 ms 99.6%
  triton_mm_2022 0.2306 ms 97.0%
  triton_mm_2024 0.2425 ms 92.2%
  triton_mm_2019 0.2589 ms 86.4%
  triton_mm_2017 0.2634 ms 84.9%
  triton_mm_2015 0.2648 ms 84.5%
  triton_mm_2018 0.2884 ms 77.5%
  triton_mm_2016 0.2916 ms 76.7%
  triton_mm_2020 0.2983 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5051 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2766 ms 100.0%
  triton_mm_2094 0.2786 ms 99.3%
  triton_mm_2095 0.2793 ms 99.1%
  triton_mm_2096 0.3168 ms 87.3%
  triton_mm_2087 0.3413 ms 81.1%
  triton_mm_2089 0.3427 ms 80.7%
  triton_mm_2091 0.3469 ms 79.8%
  triton_mm_2088 0.3643 ms 75.9%
  triton_mm_2092 0.3859 ms 71.7%
  triton_mm_2090 0.4258 ms 65.0%
SingleProcess AUTOTUNE benchmarking takes 2.5316 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3006 ms 100.0%
  triton_mm_2132 0.3037 ms 99.0%
  triton_mm_2133 0.3120 ms 96.4%
  triton_mm_2134 0.3212 ms 93.6%
  triton_mm_2129 0.3443 ms 87.3%
  triton_mm_2127 0.3505 ms 85.8%
  triton_mm_2125 0.3520 ms 85.4%
  triton_mm_2128 0.3673 ms 81.8%
  triton_mm_2126 0.3871 ms 77.7%
  triton_mm_2130 0.3966 ms 75.8%
SingleProcess AUTOTUNE benchmarking takes 2.5332 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2073 0.0173 ms 100.0%
  triton_mm_2069 0.0175 ms 99.1%
  triton_mm_2067 0.0183 ms 94.6%
  triton_mm_2066 0.0184 ms 94.4%
  triton_mm_2068 0.0184 ms 94.3%
  triton_mm_2070 0.0184 ms 94.3%
  triton_mm_2071 0.0184 ms 94.3%
  triton_mm_2072 0.0185 ms 93.9%
  triton_mm_2074 0.0192 ms 90.6%
  triton_mm_2076 0.0195 ms 89.0%
SingleProcess AUTOTUNE benchmarking takes 2.1369 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0266 ms 100.0%
  triton_mm_2048 0.0275 ms 96.6%
  triton_mm_2052 0.0317 ms 83.8%
  triton_mm_2056 0.0399 ms 66.6%
  triton_mm_2060 0.0508 ms 52.3%
  triton_mm_2047 0.0515 ms 51.6%
  triton_mm_2046 0.0560 ms 47.4%
  triton_mm_2051 0.0601 ms 44.2%
  triton_mm_2055 0.0627 ms 42.3%
  triton_mm_2045 0.0650 ms 40.9%
SingleProcess AUTOTUNE benchmarking takes 2.0894 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2243 ms 100.0%
  triton_mm_2227 0.2781 ms 80.7%
  triton_mm_2222 0.2850 ms 78.7%
  triton_mm_2228 0.2852 ms 78.6%
  triton_mm_2224 0.2871 ms 78.1%
  triton_mm_2220 0.2880 ms 77.9%
  triton_mm_2229 0.2904 ms 77.2%
  triton_mm_2223 0.3136 ms 71.5%
  triton_mm_2225 0.3263 ms 68.7%
  triton_mm_2221 0.3310 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5123 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0971 ms 100.0%
  triton_mm_2191 0.0984 ms 98.6%
  triton_mm_2184 0.1044 ms 93.0%
  triton_mm_2190 0.1079 ms 89.9%
  triton_mm_2181 0.1184 ms 81.9%
  triton_mm_2182 0.1193 ms 81.4%
  triton_mm_2186 0.1203 ms 80.7%
  triton_mm_2189 0.1219 ms 79.6%
  triton_mm_2185 0.1261 ms 76.9%
  triton_mm_2187 0.1300 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4205 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0838 ms 100.0%
  triton_mm_2171 0.0842 ms 99.6%
  triton_mm_2170 0.0860 ms 97.5%
  triton_mm_2167 0.0928 ms 90.3%
  triton_mm_2172 0.0939 ms 89.3%
  triton_mm_2163 0.0947 ms 88.5%
  triton_mm_2165 0.0954 ms 87.9%
  triton_mm_2164 0.1031 ms 81.3%
  triton_mm_2168 0.1051 ms 79.8%
  triton_mm_2161 0.1235 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.4144 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2236 ms 100.0%
  triton_mm_2209 0.2260 ms 98.9%
  triton_mm_2208 0.2304 ms 97.0%
  triton_mm_2210 0.2433 ms 91.9%
  triton_mm_2205 0.2586 ms 86.5%
  triton_mm_2203 0.2632 ms 85.0%
  triton_mm_2201 0.2652 ms 84.3%
  triton_mm_2204 0.2897 ms 77.2%
  triton_mm_2202 0.2910 ms 76.8%
  triton_mm_2206 0.2982 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5089 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2764 ms 100.0%
  triton_mm_2280 0.2778 ms 99.5%
  triton_mm_2281 0.2798 ms 98.8%
  triton_mm_2282 0.3185 ms 86.8%
  triton_mm_2273 0.3400 ms 81.3%
  triton_mm_2275 0.3420 ms 80.8%
  triton_mm_2277 0.3491 ms 79.2%
  triton_mm_2274 0.3647 ms 75.8%
  triton_mm_2278 0.3877 ms 71.3%
  triton_mm_2276 0.4228 ms 65.4%
SingleProcess AUTOTUNE benchmarking takes 2.5222 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3014 ms 100.0%
  triton_mm_2318 0.3045 ms 99.0%
  triton_mm_2319 0.3113 ms 96.8%
  triton_mm_2320 0.3214 ms 93.8%
  triton_mm_2315 0.3448 ms 87.4%
  triton_mm_2313 0.3517 ms 85.7%
  triton_mm_2311 0.3520 ms 85.6%
  triton_mm_2314 0.3670 ms 82.1%
  triton_mm_2312 0.3877 ms 77.7%
  triton_mm_2316 0.3964 ms 76.0%
SingleProcess AUTOTUNE benchmarking takes 2.5296 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2259 0.0174 ms 100.0%
  triton_mm_2253 0.0175 ms 99.3%
  triton_mm_2256 0.0177 ms 98.2%
  triton_mm_2258 0.0177 ms 98.2%
  triton_mm_2255 0.0183 ms 94.9%
  triton_mm_2262 0.0186 ms 93.3%
  triton_mm_2260 0.0187 ms 92.8%
  triton_mm_2254 0.0190 ms 91.6%
  triton_mm_2252 0.0191 ms 91.1%
  triton_mm_2257 0.0195 ms 89.2%
SingleProcess AUTOTUNE benchmarking takes 2.1346 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0266 ms 100.0%
  triton_mm_2234 0.0275 ms 97.0%
  triton_mm_2238 0.0317 ms 84.0%
  triton_mm_2242 0.0398 ms 66.8%
  triton_mm_2233 0.0515 ms 51.7%
  triton_mm_2246 0.0516 ms 51.6%
  triton_mm_2232 0.0553 ms 48.2%
  triton_mm_2237 0.0602 ms 44.2%
  triton_mm_2241 0.0627 ms 42.4%
  triton_mm_2231 0.0658 ms 40.5%
SingleProcess AUTOTUNE benchmarking takes 2.0920 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2233 ms 100.0%
  triton_mm_2413 0.2780 ms 80.3%
  triton_mm_2408 0.2842 ms 78.6%
  triton_mm_2414 0.2863 ms 78.0%
  triton_mm_2410 0.2866 ms 77.9%
  triton_mm_2406 0.2885 ms 77.4%
  triton_mm_2415 0.2908 ms 76.8%
  triton_mm_2409 0.3130 ms 71.3%
  triton_mm_2411 0.3260 ms 68.5%
  triton_mm_2407 0.3309 ms 67.5%
SingleProcess AUTOTUNE benchmarking takes 2.5241 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_2377 0.0984 ms 98.6%
  triton_mm_2370 0.1044 ms 92.9%
  triton_mm_2376 0.1078 ms 90.0%
  triton_mm_2367 0.1178 ms 82.3%
  triton_mm_2368 0.1199 ms 80.9%
  triton_mm_2372 0.1203 ms 80.7%
  triton_mm_2375 0.1218 ms 79.6%
  triton_mm_2371 0.1261 ms 76.9%
  triton_mm_2373 0.1299 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4132 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2357 0.0835 ms 100.0%
  mm 0.0838 ms 99.6%
  triton_mm_2356 0.0852 ms 98.0%
  triton_mm_2353 0.0921 ms 90.6%
  triton_mm_2358 0.0946 ms 88.2%
  triton_mm_2351 0.0948 ms 88.1%
  triton_mm_2349 0.0954 ms 87.5%
  triton_mm_2350 0.1018 ms 82.0%
  triton_mm_2354 0.1059 ms 78.8%
  triton_mm_2352 0.1230 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.4243 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2248 ms 100.0%
  triton_mm_2395 0.2260 ms 99.5%
  triton_mm_2394 0.2306 ms 97.5%
  triton_mm_2396 0.2435 ms 92.3%
  triton_mm_2391 0.2585 ms 87.0%
  triton_mm_2389 0.2633 ms 85.4%
  triton_mm_2387 0.2656 ms 84.6%
  triton_mm_2390 0.2893 ms 77.7%
  triton_mm_2388 0.2913 ms 77.2%
  triton_mm_2392 0.2985 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5128 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2768 ms 100.0%
  triton_mm_2466 0.2786 ms 99.4%
  triton_mm_2467 0.2812 ms 98.5%
  triton_mm_2468 0.3196 ms 86.6%
  triton_mm_2459 0.3406 ms 81.3%
  triton_mm_2461 0.3422 ms 80.9%
  triton_mm_2463 0.3482 ms 79.5%
  triton_mm_2460 0.3647 ms 75.9%
  triton_mm_2464 0.3886 ms 71.2%
  triton_mm_2462 0.4233 ms 65.4%
SingleProcess AUTOTUNE benchmarking takes 2.5337 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3012 ms 100.0%
  triton_mm_2504 0.3038 ms 99.1%
  triton_mm_2505 0.3128 ms 96.3%
  triton_mm_2506 0.3218 ms 93.6%
  triton_mm_2501 0.3451 ms 87.3%
  triton_mm_2499 0.3510 ms 85.8%
  triton_mm_2497 0.3529 ms 85.3%
  triton_mm_2500 0.3682 ms 81.8%
  triton_mm_2498 0.3876 ms 77.7%
  triton_mm_2502 0.3976 ms 75.8%
SingleProcess AUTOTUNE benchmarking takes 2.5334 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2444 0.0177 ms 100.0%
  triton_mm_2445 0.0183 ms 96.9%
  triton_mm_2441 0.0183 ms 96.7%
  triton_mm_2439 0.0183 ms 96.5%
  triton_mm_2440 0.0184 ms 96.2%
  triton_mm_2442 0.0184 ms 96.2%
  triton_mm_2443 0.0184 ms 96.2%
  triton_mm_2448 0.0186 ms 95.2%
  triton_mm_2438 0.0190 ms 92.9%
  triton_mm_2446 0.0192 ms 92.0%
SingleProcess AUTOTUNE benchmarking takes 2.1380 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0267 ms 100.0%
  triton_mm_2420 0.0275 ms 97.0%
  triton_mm_2424 0.0317 ms 84.2%
  triton_mm_2428 0.0398 ms 67.0%
  triton_mm_2432 0.0507 ms 52.6%
  triton_mm_2419 0.0516 ms 51.7%
  triton_mm_2418 0.0553 ms 48.3%
  triton_mm_2423 0.0595 ms 44.9%
  triton_mm_2427 0.0628 ms 42.5%
  triton_mm_2417 0.0657 ms 40.6%
SingleProcess AUTOTUNE benchmarking takes 2.0990 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2240 ms 100.0%
  triton_mm_2599 0.2781 ms 80.5%
  triton_mm_2594 0.2836 ms 79.0%
  triton_mm_2600 0.2854 ms 78.5%
  triton_mm_2596 0.2865 ms 78.2%
  triton_mm_2592 0.2883 ms 77.7%
  triton_mm_2601 0.2903 ms 77.2%
  triton_mm_2595 0.3129 ms 71.6%
  triton_mm_2597 0.3261 ms 68.7%
  triton_mm_2593 0.3308 ms 67.7%
SingleProcess AUTOTUNE benchmarking takes 2.5151 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_2563 0.0991 ms 97.9%
  triton_mm_2556 0.1053 ms 92.2%
  triton_mm_2562 0.1085 ms 89.4%
  triton_mm_2553 0.1178 ms 82.4%
  triton_mm_2558 0.1196 ms 81.1%
  triton_mm_2554 0.1201 ms 80.8%
  triton_mm_2561 0.1225 ms 79.2%
  triton_mm_2557 0.1271 ms 76.4%
  triton_mm_2559 0.1308 ms 74.2%
SingleProcess AUTOTUNE benchmarking takes 2.4182 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0831 ms 100.0%
  triton_mm_2543 0.0835 ms 99.6%
  triton_mm_2542 0.0853 ms 97.4%
  triton_mm_2539 0.0922 ms 90.1%
  triton_mm_2544 0.0946 ms 87.9%
  triton_mm_2535 0.0948 ms 87.7%
  triton_mm_2537 0.0955 ms 87.1%
  triton_mm_2536 0.1027 ms 80.9%
  triton_mm_2540 0.1060 ms 78.4%
  triton_mm_2538 0.1229 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.4219 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2247 ms 100.0%
  triton_mm_2581 0.2255 ms 99.7%
  triton_mm_2580 0.2316 ms 97.0%
  triton_mm_2582 0.2442 ms 92.0%
  triton_mm_2577 0.2595 ms 86.6%
  triton_mm_2575 0.2643 ms 85.0%
  triton_mm_2573 0.2645 ms 85.0%
  triton_mm_2576 0.2890 ms 77.8%
  triton_mm_2574 0.2918 ms 77.0%
  triton_mm_2578 0.2992 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5119 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2631 0.0174 ms 100.0%
  triton_mm_2625 0.0175 ms 99.1%
  triton_mm_2627 0.0183 ms 94.9%
  triton_mm_2628 0.0185 ms 93.9%
  triton_mm_2629 0.0185 ms 93.9%
  triton_mm_2630 0.0185 ms 93.9%
  triton_mm_2624 0.0191 ms 90.8%
  triton_mm_2632 0.0192 ms 90.3%
  triton_mm_2634 0.0194 ms 89.5%
  triton_mm_2626 0.0194 ms 89.4%
SingleProcess AUTOTUNE benchmarking takes 2.1424 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0268 ms 100.0%
  triton_mm_2606 0.0275 ms 97.7%
  triton_mm_2610 0.0306 ms 87.7%
  triton_mm_2614 0.0407 ms 65.9%
  triton_mm_2618 0.0508 ms 52.8%
  triton_mm_2605 0.0515 ms 52.0%
  triton_mm_2604 0.0560 ms 47.9%
  triton_mm_2609 0.0602 ms 44.6%
  triton_mm_2613 0.0620 ms 43.2%
  triton_mm_2603 0.0650 ms 41.3%
SingleProcess AUTOTUNE benchmarking takes 2.1019 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2237 ms 100.0%
  triton_mm_2785 0.2777 ms 80.6%
  triton_mm_2780 0.2840 ms 78.8%
  triton_mm_2786 0.2842 ms 78.7%
  triton_mm_2782 0.2845 ms 78.6%
  triton_mm_2778 0.2875 ms 77.8%
  triton_mm_2787 0.2884 ms 77.6%
  triton_mm_2781 0.3122 ms 71.7%
  triton_mm_2783 0.3257 ms 68.7%
  triton_mm_2779 0.3308 ms 67.6%
SingleProcess AUTOTUNE benchmarking takes 2.5218 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0969 ms 100.0%
  triton_mm_2749 0.0985 ms 98.4%
  triton_mm_2742 0.1043 ms 92.9%
  triton_mm_2748 0.1078 ms 89.9%
  triton_mm_2739 0.1177 ms 82.3%
  triton_mm_2740 0.1200 ms 80.8%
  triton_mm_2744 0.1203 ms 80.5%
  triton_mm_2747 0.1218 ms 79.5%
  triton_mm_2743 0.1261 ms 76.8%
  triton_mm_2745 0.1300 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.4274 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_2729 0.0834 ms 100.0%
  mm 0.0837 ms 99.6%
  triton_mm_2728 0.0852 ms 97.9%
  triton_mm_2725 0.0919 ms 90.7%
  triton_mm_2723 0.0946 ms 88.2%
  triton_mm_2730 0.0947 ms 88.1%
  triton_mm_2721 0.0952 ms 87.7%
  triton_mm_2722 0.1018 ms 82.0%
  triton_mm_2726 0.1058 ms 78.9%
  triton_mm_2724 0.1238 ms 67.4%
SingleProcess AUTOTUNE benchmarking takes 2.4257 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2241 ms 100.0%
  triton_mm_2767 0.2258 ms 99.3%
  triton_mm_2766 0.2307 ms 97.1%
  triton_mm_2768 0.2431 ms 92.2%
  triton_mm_2763 0.2583 ms 86.8%
  triton_mm_2761 0.2634 ms 85.1%
  triton_mm_2759 0.2649 ms 84.6%
  triton_mm_2762 0.2897 ms 77.4%
  triton_mm_2760 0.2913 ms 76.9%
  triton_mm_2764 0.2981 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5119 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0277 ms 100.0%
  triton_mm_4879 0.0495 ms 56.0%
  triton_mm_4872 0.0506 ms 54.7%
  triton_mm_4870 0.0563 ms 49.2%
  triton_mm_4871 0.0637 ms 43.4%
  triton_mm_4878 0.0670 ms 41.3%
  triton_mm_4875 0.0700 ms 39.5%
  triton_mm_4883 0.0736 ms 37.6%
  triton_mm_4884 0.0738 ms 37.5%
  triton_mm_4877 0.0771 ms 35.9%
SingleProcess AUTOTUNE benchmarking takes 6.2142 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_7 0.0259 ms 100.0%
  triton_mm_9 0.0269 ms 96.4%
  triton_mm_11 0.0269 ms 96.4%
  triton_mm_12 0.0270 ms 95.9%
  triton_mm_6 0.0276 ms 93.7%
  triton_mm_8 0.0277 ms 93.6%
  triton_mm_4 0.0281 ms 92.3%
  triton_mm_3 0.0292 ms 88.7%
  triton_mm_2 0.0293 ms 88.4%
  triton_mm_14 0.0301 ms 86.1%
SingleProcess AUTOTUNE benchmarking takes 2.1770 seconds and 0.0182 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_29 0.0215 ms 100.0%
  triton_mm_33 0.0223 ms 96.4%
  triton_mm_21 0.0232 ms 93.0%
  triton_mm_25 0.0232 ms 92.8%
  triton_mm_24 0.0237 ms 90.9%
  triton_mm_19 0.0240 ms 89.6%
  triton_mm_28 0.0246 ms 87.5%
  triton_mm_18 0.0248 ms 86.8%
  bias_addmm 0.0251 ms 85.8%
  triton_mm_20 0.0257 ms 83.7%
SingleProcess AUTOTUNE benchmarking takes 2.2053 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2232 ms 100.0%
  triton_mm_51 0.2263 ms 98.6%
  triton_mm_52 0.2545 ms 87.7%
  triton_mm_45 0.2630 ms 84.9%
  triton_mm_47 0.2718 ms 82.1%
  triton_mm_43 0.2756 ms 81.0%
  bias_addmm 0.2995 ms 74.5%
  triton_mm_44 0.3058 ms 73.0%
  triton_mm_48 0.3102 ms 71.9%
  addmm 0.3216 ms 69.4%
SingleProcess AUTOTUNE benchmarking takes 2.5869 seconds and 0.0176 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0908 ms 100.0%
  triton_mm_69 0.0924 ms 98.2%
  bias_addmm 0.0967 ms 93.9%
  triton_mm_66 0.0987 ms 92.0%
  triton_mm_64 0.0997 ms 91.0%
  triton_mm_71 0.1001 ms 90.7%
  triton_mm_62 0.1031 ms 88.1%
  addmm 0.1109 ms 81.9%
  triton_mm_63 0.1117 ms 81.3%
  triton_mm_67 0.1137 ms 79.9%
SingleProcess AUTOTUNE benchmarking takes 2.5083 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_89 0.2944 ms 100.0%
  triton_mm_88 0.2948 ms 99.9%
  bias_addmm 0.3252 ms 90.5%
  triton_mm_90 0.3359 ms 87.7%
  triton_mm_83 0.3409 ms 86.4%
  triton_mm_81 0.3625 ms 81.2%
  triton_mm_85 0.3636 ms 81.0%
  addmm 0.3685 ms 79.9%
  triton_mm_82 0.4020 ms 73.2%
  triton_mm_86 0.4104 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.6086 seconds and 0.0099 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2915 ms 100.0%
  triton_mm_108 0.3052 ms 95.5%
  triton_mm_107 0.3157 ms 92.3%
  triton_mm_109 0.3257 ms 89.5%
  addmm 0.3261 ms 89.4%
  triton_mm_102 0.3546 ms 82.2%
  triton_mm_104 0.3566 ms 81.7%
  triton_mm_103 0.3715 ms 78.5%
  triton_mm_100 0.3723 ms 78.3%
  triton_mm_105 0.4050 ms 72.0%
SingleProcess AUTOTUNE benchmarking takes 2.6536 seconds and 0.0009 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_126 0.0211 ms 100.0%
  triton_mm_117 0.0226 ms 93.4%
  triton_mm_114 0.0228 ms 92.4%
  triton_mm_118 0.0230 ms 91.9%
  triton_mm_122 0.0230 ms 91.9%
  triton_mm_121 0.0236 ms 89.7%
  bias_addmm 0.0240 ms 87.9%
  triton_mm_112 0.0241 ms 87.5%
  triton_mm_113 0.0246 ms 85.7%
  triton_mm_111 0.0249 ms 84.8%
SingleProcess AUTOTUNE benchmarking takes 2.2019 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_181 0.2945 ms 100.0%
  triton_mm_182 0.2947 ms 99.9%
  bias_addmm 0.3253 ms 90.5%
  triton_mm_183 0.3333 ms 88.3%
  triton_mm_176 0.3393 ms 86.8%
  triton_mm_174 0.3614 ms 81.5%
  triton_mm_178 0.3626 ms 81.2%
  addmm 0.3726 ms 79.0%
  triton_mm_175 0.3988 ms 73.8%
  triton_mm_179 0.4108 ms 71.7%
SingleProcess AUTOTUNE benchmarking takes 2.6249 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2909 ms 100.0%
  triton_mm_201 0.3065 ms 94.9%
  triton_mm_200 0.3170 ms 91.8%
  triton_mm_202 0.3263 ms 89.2%
  addmm 0.3265 ms 89.1%
  triton_mm_197 0.3566 ms 81.6%
  triton_mm_195 0.3571 ms 81.5%
  triton_mm_196 0.3694 ms 78.8%
  triton_mm_193 0.3717 ms 78.3%
  triton_mm_198 0.4061 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6449 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_275 0.2949 ms 100.0%
  triton_mm_274 0.2950 ms 99.9%
  bias_addmm 0.3252 ms 90.7%
  triton_mm_276 0.3343 ms 88.2%
  triton_mm_269 0.3393 ms 86.9%
  triton_mm_267 0.3615 ms 81.6%
  triton_mm_271 0.3627 ms 81.3%
  addmm 0.3687 ms 80.0%
  triton_mm_268 0.4018 ms 73.4%
  triton_mm_272 0.4107 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6331 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2920 ms 100.0%
  triton_mm_294 0.3075 ms 94.9%
  triton_mm_293 0.3168 ms 92.2%
  addmm 0.3264 ms 89.5%
  triton_mm_295 0.3270 ms 89.3%
  triton_mm_288 0.3559 ms 82.0%
  triton_mm_290 0.3568 ms 81.8%
  triton_mm_289 0.3700 ms 78.9%
  triton_mm_286 0.3743 ms 78.0%
  triton_mm_291 0.4067 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6476 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_387 0.3076 ms 100.0%
  triton_mm_386 0.3181 ms 96.7%
  triton_mm_388 0.3267 ms 94.2%
  bias_addmm 0.3283 ms 93.7%
  triton_mm_381 0.3536 ms 87.0%
  triton_mm_383 0.3555 ms 86.5%
  addmm 0.3669 ms 83.8%
  triton_mm_382 0.3708 ms 82.9%
  triton_mm_379 0.3724 ms 82.6%
  triton_mm_384 0.4052 ms 75.9%
SingleProcess AUTOTUNE benchmarking takes 2.6315 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_480 0.3061 ms 100.0%
  triton_mm_479 0.3175 ms 96.4%
  triton_mm_481 0.3259 ms 93.9%
  bias_addmm 0.3283 ms 93.2%
  addmm 0.3351 ms 91.3%
  triton_mm_474 0.3555 ms 86.1%
  triton_mm_476 0.3563 ms 85.9%
  triton_mm_475 0.3698 ms 82.8%
  triton_mm_472 0.3702 ms 82.7%
  triton_mm_477 0.4035 ms 75.9%
SingleProcess AUTOTUNE benchmarking takes 2.6513 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1602 0.0134 ms 100.0%
  triton_mm_1606 0.0154 ms 86.7%
  triton_mm_1610 0.0163 ms 82.0%
  mm 0.0168 ms 79.8%
  triton_mm_1614 0.0174 ms 76.7%
  triton_mm_1605 0.0175 ms 76.6%
  triton_mm_1599 0.0179 ms 74.9%
  triton_mm_1601 0.0180 ms 74.2%
  triton_mm_1600 0.0188 ms 71.2%
  triton_mm_1609 0.0202 ms 66.3%
SingleProcess AUTOTUNE benchmarking takes 7.3265 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  bias_addmm 0.5551 ms 100.0%
  triton_mm_1632 0.5551 ms 100.0%
  triton_mm_1631 0.5608 ms 99.0%
  triton_mm_1633 0.6268 ms 88.6%
  triton_mm_1626 0.6516 ms 85.2%
  triton_mm_1628 0.6961 ms 79.7%
  addmm 0.6980 ms 79.5%
  triton_mm_1624 0.7043 ms 78.8%
  triton_mm_1629 0.7751 ms 71.6%
  triton_mm_1625 0.7796 ms 71.2%
SingleProcess AUTOTUNE benchmarking takes 11.4528 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  triton_mm_1669 0.5547 ms 100.0%
  triton_mm_1670 0.5725 ms 96.9%
  mm 0.5882 ms 94.3%
  triton_mm_1671 0.5973 ms 92.9%
  triton_mm_1664 0.6687 ms 83.0%
  triton_mm_1662 0.6803 ms 81.5%
  triton_mm_1666 0.6854 ms 80.9%
  triton_mm_1665 0.7208 ms 77.0%
  triton_mm_1667 0.7274 ms 76.3%
  triton_mm_1663 0.7368 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 9.4779 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2922 ms 100.0%
  triton_mm_1742 0.2949 ms 99.1%
  triton_mm_1741 0.2965 ms 98.6%
  triton_mm_1743 0.3006 ms 97.2%
  triton_mm_1736 0.3508 ms 83.3%
  triton_mm_1734 0.3542 ms 82.5%
  triton_mm_1738 0.3624 ms 80.6%
  triton_mm_1737 0.3783 ms 77.2%
  triton_mm_1739 0.3976 ms 73.5%
  triton_mm_1735 0.4034 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 10.0902 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1695 0.0115 ms 100.0%
  triton_mm_1699 0.0119 ms 96.2%
  triton_mm_1697 0.0124 ms 92.3%
  triton_mm_1702 0.0125 ms 91.6%
  triton_mm_1696 0.0127 ms 90.8%
  triton_mm_1704 0.0127 ms 90.4%
  triton_mm_1689 0.0127 ms 90.2%
  triton_mm_1694 0.0127 ms 90.2%
  triton_mm_1698 0.0127 ms 90.2%
  triton_mm_1692 0.0128 ms 90.0%
SingleProcess AUTOTUNE benchmarking takes 6.1315 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0168 ms 100.0%
  mm 0.0175 ms 95.8%
  triton_mm_1680 0.0177 ms 95.1%
  triton_mm_1684 0.0215 ms 78.2%
  triton_mm_1688 0.0226 ms 74.5%
  triton_mm_1675 0.0231 ms 72.8%
  triton_mm_1674 0.0237 ms 70.9%
  triton_mm_1679 0.0252 ms 66.7%
  triton_mm_1683 0.0257 ms 65.3%
  triton_mm_1673 0.0273 ms 61.5%
SingleProcess AUTOTUNE benchmarking takes 7.6320 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5396 ms 100.0%
  triton_mm_1650 0.5654 ms 95.4%
  triton_mm_1651 0.5788 ms 93.2%
  triton_mm_1652 0.5908 ms 91.3%
  triton_mm_1645 0.6630 ms 81.4%
  triton_mm_1647 0.6665 ms 81.0%
  triton_mm_1643 0.6683 ms 80.7%
  triton_mm_1646 0.7004 ms 77.0%
  triton_mm_1644 0.7241 ms 74.5%
  triton_mm_1648 0.7356 ms 73.3%
SingleProcess AUTOTUNE benchmarking takes 2.5978 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_1722 0.2763 ms 100.0%
  mm 0.2795 ms 98.8%
  triton_mm_1723 0.2799 ms 98.7%
  triton_mm_1724 0.3167 ms 87.2%
  triton_mm_1715 0.3412 ms 81.0%
  triton_mm_1717 0.3439 ms 80.3%
  triton_mm_1719 0.3475 ms 79.5%
  triton_mm_1716 0.3609 ms 76.5%
  triton_mm_1720 0.3855 ms 71.7%
  triton_mm_1718 0.4234 ms 65.2%
SingleProcess AUTOTUNE benchmarking takes 2.5285 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2245 ms 100.0%
  triton_mm_1836 0.2308 ms 97.3%
  triton_mm_1838 0.2424 ms 92.6%
  triton_mm_1833 0.2566 ms 87.5%
  mm 0.2577 ms 87.1%
  triton_mm_1831 0.2605 ms 86.2%
  triton_mm_1829 0.2619 ms 85.7%
  triton_mm_1832 0.2859 ms 78.5%
  triton_mm_1830 0.2884 ms 77.8%
  triton_mm_1834 0.2947 ms 76.2%
SingleProcess AUTOTUNE benchmarking takes 9.8358 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2912 ms 100.0%
  mm 0.2920 ms 99.7%
  triton_mm_1780 0.2944 ms 98.9%
  triton_mm_1781 0.2998 ms 97.1%
  triton_mm_1776 0.3457 ms 84.2%
  triton_mm_1772 0.3532 ms 82.4%
  triton_mm_1774 0.3571 ms 81.5%
  triton_mm_1775 0.3819 ms 76.2%
  triton_mm_1777 0.3914 ms 74.4%
  triton_mm_1773 0.3986 ms 73.0%
SingleProcess AUTOTUNE benchmarking takes 2.5373 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2265 ms 100.0%
  triton_mm_1855 0.2782 ms 81.4%
  triton_mm_1850 0.2826 ms 80.2%
  triton_mm_1852 0.2839 ms 79.8%
  triton_mm_1856 0.2850 ms 79.5%
  triton_mm_1848 0.2869 ms 78.9%
  triton_mm_1857 0.2901 ms 78.1%
  triton_mm_1851 0.3113 ms 72.8%
  triton_mm_1853 0.3236 ms 70.0%
  triton_mm_1849 0.3291 ms 68.8%
SingleProcess AUTOTUNE benchmarking takes 9.9685 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0980 ms 100.0%
  triton_mm_1812 0.1052 ms 93.2%
  triton_mm_1818 0.1077 ms 91.0%
  triton_mm_1809 0.1187 ms 82.6%
  triton_mm_1810 0.1197 ms 81.8%
  triton_mm_1817 0.1200 ms 81.6%
  triton_mm_1814 0.1201 ms 81.6%
  triton_mm_1819 0.1207 ms 81.2%
  triton_mm_1813 0.1275 ms 76.8%
  triton_mm_1815 0.1310 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 9.7354 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3006 ms 100.0%
  triton_mm_1760 0.3014 ms 99.7%
  triton_mm_1761 0.3065 ms 98.1%
  triton_mm_1762 0.3192 ms 94.2%
  triton_mm_1757 0.3386 ms 88.8%
  triton_mm_1755 0.3437 ms 87.5%
  triton_mm_1753 0.3454 ms 87.0%
  triton_mm_1756 0.3605 ms 83.4%
  triton_mm_1754 0.3806 ms 79.0%
  triton_mm_1758 0.3882 ms 77.5%
SingleProcess AUTOTUNE benchmarking takes 9.8868 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0844 ms 100.0%
  triton_mm_1799 0.0845 ms 99.9%
  triton_mm_1798 0.0861 ms 98.0%
  triton_mm_1795 0.0926 ms 91.2%
  triton_mm_1793 0.0950 ms 88.9%
  triton_mm_1800 0.0951 ms 88.7%
  triton_mm_1791 0.0956 ms 88.3%
  triton_mm_1792 0.1021 ms 82.7%
  triton_mm_1796 0.1051 ms 80.4%
  triton_mm_1794 0.1226 ms 68.9%
SingleProcess AUTOTUNE benchmarking takes 10.1715 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2775 ms 100.0%
  triton_mm_1908 0.2776 ms 99.9%
  triton_mm_1909 0.2793 ms 99.3%
  triton_mm_1910 0.3162 ms 87.8%
  triton_mm_1901 0.3379 ms 82.1%
  triton_mm_1903 0.3415 ms 81.2%
  triton_mm_1905 0.3471 ms 79.9%
  triton_mm_1902 0.3639 ms 76.2%
  triton_mm_1906 0.3841 ms 72.2%
  triton_mm_1904 0.4226 ms 65.7%
SingleProcess AUTOTUNE benchmarking takes 2.5223 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1883 0.0173 ms 100.0%
  triton_mm_1887 0.0173 ms 99.8%
  triton_mm_1884 0.0174 ms 99.4%
  triton_mm_1882 0.0184 ms 93.9%
  triton_mm_1881 0.0185 ms 93.7%
  triton_mm_1886 0.0185 ms 93.4%
  triton_mm_1888 0.0192 ms 90.4%
  triton_mm_1885 0.0192 ms 90.2%
  triton_mm_1880 0.0192 ms 90.0%
  triton_mm_1890 0.0196 ms 88.1%
SingleProcess AUTOTUNE benchmarking takes 5.8775 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2905 ms 100.0%
  mm 0.2923 ms 99.4%
  triton_mm_1966 0.2946 ms 98.6%
  triton_mm_1967 0.3023 ms 96.1%
  triton_mm_1962 0.3475 ms 83.6%
  triton_mm_1958 0.3547 ms 81.9%
  triton_mm_1960 0.3582 ms 81.1%
  triton_mm_1961 0.3835 ms 75.8%
  triton_mm_1963 0.3931 ms 73.9%
  triton_mm_1959 0.3992 ms 72.8%
SingleProcess AUTOTUNE benchmarking takes 2.5281 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_1862 0.0268 ms 100.0%
  mm 0.0270 ms 99.0%
  triton_mm_1866 0.0308 ms 87.0%
  triton_mm_1870 0.0412 ms 65.0%
  triton_mm_1874 0.0509 ms 52.6%
  triton_mm_1861 0.0516 ms 51.9%
  triton_mm_1860 0.0555 ms 48.2%
  triton_mm_1865 0.0605 ms 44.3%
  triton_mm_1869 0.0620 ms 43.2%
  triton_mm_1859 0.0658 ms 40.7%
SingleProcess AUTOTUNE benchmarking takes 6.6769 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2262 ms 100.0%
  triton_mm_2041 0.2786 ms 81.2%
  triton_mm_2036 0.2827 ms 80.0%
  triton_mm_2038 0.2846 ms 79.5%
  triton_mm_2042 0.2854 ms 79.2%
  triton_mm_2034 0.2879 ms 78.6%
  triton_mm_2043 0.2905 ms 77.9%
  triton_mm_2037 0.3117 ms 72.6%
  triton_mm_2039 0.3255 ms 69.5%
  triton_mm_2035 0.3290 ms 68.8%
SingleProcess AUTOTUNE benchmarking takes 2.5126 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0977 ms 100.0%
  triton_mm_2005 0.0987 ms 99.1%
  triton_mm_1998 0.1053 ms 92.8%
  triton_mm_2004 0.1078 ms 90.6%
  triton_mm_1995 0.1188 ms 82.2%
  triton_mm_1996 0.1197 ms 81.6%
  triton_mm_2000 0.1207 ms 81.0%
  triton_mm_2003 0.1221 ms 80.0%
  triton_mm_1999 0.1268 ms 77.1%
  triton_mm_2001 0.1302 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.4097 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2232 ms 100.0%
  triton_mm_2023 0.2263 ms 98.6%
  triton_mm_2022 0.2323 ms 96.1%
  triton_mm_2024 0.2443 ms 91.4%
  triton_mm_2019 0.2578 ms 86.6%
  triton_mm_2017 0.2624 ms 85.1%
  triton_mm_2015 0.2645 ms 84.4%
  triton_mm_2018 0.2868 ms 77.8%
  triton_mm_2016 0.2893 ms 77.2%
  triton_mm_2020 0.2974 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.4960 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2094 0.2788 ms 100.0%
  mm 0.2793 ms 99.8%
  triton_mm_2095 0.2808 ms 99.3%
  triton_mm_2096 0.3181 ms 87.6%
  triton_mm_2087 0.3406 ms 81.8%
  triton_mm_2089 0.3423 ms 81.4%
  triton_mm_2091 0.3481 ms 80.1%
  triton_mm_2088 0.3666 ms 76.1%
  triton_mm_2092 0.3845 ms 72.5%
  triton_mm_2090 0.4229 ms 65.9%
SingleProcess AUTOTUNE benchmarking takes 2.5182 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2070 0.0175 ms 100.0%
  triton_mm_2067 0.0181 ms 96.6%
  triton_mm_2066 0.0183 ms 95.6%
  triton_mm_2071 0.0184 ms 94.8%
  triton_mm_2068 0.0185 ms 94.6%
  triton_mm_2069 0.0185 ms 94.4%
  triton_mm_2073 0.0185 ms 94.3%
  triton_mm_2072 0.0186 ms 94.0%
  triton_mm_2076 0.0187 ms 93.5%
  triton_mm_2074 0.0195 ms 89.7%
SingleProcess AUTOTUNE benchmarking takes 2.1212 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2908 ms 100.0%
  triton_mm_2151 0.2918 ms 99.6%
  triton_mm_2152 0.2967 ms 98.0%
  triton_mm_2153 0.3030 ms 95.9%
  triton_mm_2148 0.3483 ms 83.5%
  triton_mm_2144 0.3551 ms 81.9%
  triton_mm_2146 0.3602 ms 80.7%
  triton_mm_2147 0.3864 ms 75.3%
  triton_mm_2149 0.3926 ms 74.1%
  triton_mm_2145 0.3995 ms 72.8%
SingleProcess AUTOTUNE benchmarking takes 2.5307 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2048 0.0268 ms 100.0%
  mm 0.0270 ms 99.2%
  triton_mm_2052 0.0308 ms 87.1%
  triton_mm_2056 0.0411 ms 65.1%
  triton_mm_2047 0.0516 ms 52.0%
  triton_mm_2060 0.0516 ms 51.9%
  triton_mm_2046 0.0555 ms 48.3%
  triton_mm_2051 0.0597 ms 44.9%
  triton_mm_2055 0.0620 ms 43.2%
  triton_mm_2045 0.0658 ms 40.7%
SingleProcess AUTOTUNE benchmarking takes 2.0804 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2250 ms 100.0%
  triton_mm_2227 0.2789 ms 80.7%
  triton_mm_2222 0.2849 ms 79.0%
  triton_mm_2224 0.2855 ms 78.8%
  triton_mm_2228 0.2858 ms 78.7%
  triton_mm_2220 0.2873 ms 78.3%
  triton_mm_2229 0.2907 ms 77.4%
  triton_mm_2223 0.3131 ms 71.9%
  triton_mm_2225 0.3260 ms 69.0%
  triton_mm_2221 0.3295 ms 68.3%
SingleProcess AUTOTUNE benchmarking takes 2.5097 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0977 ms 100.0%
  triton_mm_2191 0.0987 ms 99.0%
  triton_mm_2184 0.1054 ms 92.7%
  triton_mm_2190 0.1078 ms 90.6%
  triton_mm_2181 0.1182 ms 82.7%
  triton_mm_2182 0.1205 ms 81.1%
  triton_mm_2186 0.1206 ms 81.0%
  triton_mm_2189 0.1220 ms 80.1%
  triton_mm_2185 0.1268 ms 77.1%
  triton_mm_2187 0.1302 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.4114 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2234 ms 100.0%
  triton_mm_2209 0.2274 ms 98.2%
  triton_mm_2208 0.2323 ms 96.2%
  triton_mm_2210 0.2439 ms 91.6%
  triton_mm_2205 0.2578 ms 86.6%
  triton_mm_2203 0.2635 ms 84.8%
  triton_mm_2201 0.2654 ms 84.2%
  triton_mm_2204 0.2873 ms 77.7%
  triton_mm_2202 0.2912 ms 76.7%
  triton_mm_2206 0.2968 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5024 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  triton_mm_2280 0.2792 ms 100.0%
  mm 0.2797 ms 99.8%
  triton_mm_2281 0.2820 ms 99.0%
  triton_mm_2282 0.3185 ms 87.7%
  triton_mm_2273 0.3410 ms 81.9%
  triton_mm_2275 0.3428 ms 81.5%
  triton_mm_2277 0.3498 ms 79.8%
  triton_mm_2274 0.3637 ms 76.8%
  triton_mm_2278 0.3879 ms 72.0%
  triton_mm_2276 0.4219 ms 66.2%
SingleProcess AUTOTUNE benchmarking takes 2.5351 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2259 0.0174 ms 100.0%
  triton_mm_2256 0.0175 ms 99.5%
  triton_mm_2258 0.0175 ms 99.3%
  triton_mm_2252 0.0183 ms 95.1%
  triton_mm_2257 0.0185 ms 94.1%
  triton_mm_2253 0.0187 ms 93.1%
  triton_mm_2255 0.0187 ms 93.1%
  triton_mm_2260 0.0193 ms 90.0%
  triton_mm_2254 0.0197 ms 88.1%
  triton_mm_2262 0.0198 ms 87.6%
SingleProcess AUTOTUNE benchmarking takes 2.1543 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  mm 0.2904 ms 100.0%
  triton_mm_2337 0.2932 ms 99.1%
  triton_mm_2338 0.2973 ms 97.7%
  triton_mm_2339 0.3027 ms 96.0%
  triton_mm_2334 0.3491 ms 83.2%
  triton_mm_2330 0.3559 ms 81.6%
  triton_mm_2332 0.3600 ms 80.7%
  triton_mm_2333 0.3867 ms 75.1%
  triton_mm_2335 0.3930 ms 73.9%
  triton_mm_2331 0.4012 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5467 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2234 0.0268 ms 100.0%
  mm 0.0270 ms 99.4%
  triton_mm_2238 0.0308 ms 87.3%
  triton_mm_2242 0.0412 ms 65.1%
  triton_mm_2246 0.0508 ms 52.8%
  triton_mm_2233 0.0515 ms 52.1%
  triton_mm_2232 0.0555 ms 48.4%
  triton_mm_2237 0.0597 ms 45.0%
  triton_mm_2241 0.0619 ms 43.4%
  triton_mm_2231 0.0660 ms 40.7%
SingleProcess AUTOTUNE benchmarking takes 2.0997 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2377 0.0986 ms 100.0%
  mm 0.1009 ms 97.7%
  triton_mm_2370 0.1054 ms 93.5%
  triton_mm_2376 0.1078 ms 91.4%
  triton_mm_2367 0.1181 ms 83.4%
  triton_mm_2368 0.1202 ms 82.0%
  triton_mm_2372 0.1204 ms 81.8%
  triton_mm_2375 0.1212 ms 81.3%
  triton_mm_2371 0.1266 ms 77.9%
  triton_mm_2373 0.1301 ms 75.7%
SingleProcess AUTOTUNE benchmarking takes 2.4275 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2239 ms 100.0%
  triton_mm_2395 0.2258 ms 99.1%
  triton_mm_2394 0.2315 ms 96.7%
  triton_mm_2396 0.2448 ms 91.4%
  triton_mm_2391 0.2583 ms 86.7%
  triton_mm_2389 0.2631 ms 85.1%
  triton_mm_2387 0.2662 ms 84.1%
  triton_mm_2390 0.2888 ms 77.5%
  triton_mm_2388 0.2907 ms 77.0%
  triton_mm_2392 0.2970 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.5099 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0268 ms 100.0%
  triton_mm_2420 0.0278 ms 96.7%
  triton_mm_2424 0.0308 ms 87.3%
  triton_mm_2428 0.0400 ms 67.2%
  triton_mm_2432 0.0508 ms 52.8%
  triton_mm_2419 0.0523 ms 51.3%
  triton_mm_2418 0.0562 ms 47.8%
  triton_mm_2423 0.0597 ms 45.0%
  triton_mm_2427 0.0627 ms 42.8%
  triton_mm_2417 0.0651 ms 41.2%
SingleProcess AUTOTUNE benchmarking takes 2.1026 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2563 0.0987 ms 100.0%
  mm 0.1004 ms 98.2%
  triton_mm_2556 0.1062 ms 92.9%
  triton_mm_2562 0.1078 ms 91.5%
  triton_mm_2553 0.1190 ms 82.9%
  triton_mm_2554 0.1204 ms 81.9%
  triton_mm_2558 0.1206 ms 81.8%
  triton_mm_2561 0.1213 ms 81.3%
  triton_mm_2557 0.1276 ms 77.3%
  triton_mm_2559 0.1301 ms 75.8%
SingleProcess AUTOTUNE benchmarking takes 2.4337 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2224 ms 100.0%
  triton_mm_2581 0.2266 ms 98.1%
  triton_mm_2580 0.2322 ms 95.8%
  triton_mm_2582 0.2436 ms 91.3%
  triton_mm_2577 0.2608 ms 85.3%
  triton_mm_2573 0.2640 ms 84.2%
  triton_mm_2575 0.2652 ms 83.8%
  triton_mm_2576 0.2874 ms 77.4%
  triton_mm_2574 0.2917 ms 76.2%
  triton_mm_2578 0.2979 ms 74.6%
SingleProcess AUTOTUNE benchmarking takes 2.5099 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0269 ms 100.0%
  triton_mm_2606 0.0277 ms 96.9%
  triton_mm_2610 0.0319 ms 84.3%
  triton_mm_2614 0.0405 ms 66.4%
  triton_mm_2618 0.0508 ms 52.9%
  triton_mm_2605 0.0524 ms 51.3%
  triton_mm_2604 0.0562 ms 47.8%
  triton_mm_2609 0.0605 ms 44.4%
  triton_mm_2613 0.0619 ms 43.4%
  triton_mm_2603 0.0659 ms 40.8%
SingleProcess AUTOTUNE benchmarking takes 2.0995 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2749 0.0995 ms 100.0%
  mm 0.1007 ms 98.8%
  triton_mm_2742 0.1062 ms 93.7%
  triton_mm_2748 0.1085 ms 91.6%
  triton_mm_2739 0.1189 ms 83.7%
  triton_mm_2740 0.1196 ms 83.2%
  triton_mm_2744 0.1198 ms 83.0%
  triton_mm_2747 0.1220 ms 81.5%
  triton_mm_2743 0.1274 ms 78.1%
  triton_mm_2745 0.1309 ms 76.0%
SingleProcess AUTOTUNE benchmarking takes 2.4271 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2227 ms 100.0%
  triton_mm_2767 0.2254 ms 98.8%
  triton_mm_2766 0.2319 ms 96.0%
  triton_mm_2768 0.2443 ms 91.2%
  triton_mm_2763 0.2590 ms 86.0%
  triton_mm_2761 0.2634 ms 84.6%
  triton_mm_2759 0.2636 ms 84.5%
  triton_mm_2762 0.2873 ms 77.5%
  triton_mm_2760 0.2907 ms 76.6%
  triton_mm_2764 0.2970 ms 75.0%
SingleProcess AUTOTUNE benchmarking takes 2.5090 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0267 ms 100.0%
  triton_mm_2792 0.0278 ms 96.1%
  triton_mm_2796 0.0308 ms 86.8%
  triton_mm_2800 0.0412 ms 64.8%
  triton_mm_2804 0.0508 ms 52.5%
  triton_mm_2791 0.0522 ms 51.1%
  triton_mm_2790 0.0562 ms 47.5%
  triton_mm_2795 0.0597 ms 44.7%
  triton_mm_2799 0.0619 ms 43.1%
  triton_mm_2789 0.0651 ms 41.0%
SingleProcess AUTOTUNE benchmarking takes 2.1016 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_2935 0.0995 ms 100.0%
  mm 0.1008 ms 98.7%
  triton_mm_2928 0.1054 ms 94.4%
  triton_mm_2934 0.1084 ms 91.7%
  triton_mm_2925 0.1181 ms 84.2%
  triton_mm_2926 0.1204 ms 82.6%
  triton_mm_2930 0.1206 ms 82.5%
  triton_mm_2933 0.1212 ms 82.0%
  triton_mm_2929 0.1267 ms 78.5%
  triton_mm_2931 0.1301 ms 76.4%
SingleProcess AUTOTUNE benchmarking takes 2.4366 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2232 ms 100.0%
  triton_mm_2953 0.2264 ms 98.6%
  triton_mm_2952 0.2327 ms 95.9%
  triton_mm_2954 0.2427 ms 92.0%
  triton_mm_2949 0.2579 ms 86.5%
  triton_mm_2947 0.2624 ms 85.1%
  triton_mm_2945 0.2635 ms 84.7%
  triton_mm_2948 0.2872 ms 77.7%
  triton_mm_2946 0.2906 ms 76.8%
  triton_mm_2950 0.2967 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5094 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0278 ms 100.0%
  triton_mm_4872 0.0496 ms 56.0%
  triton_mm_4879 0.0503 ms 55.3%
  triton_mm_4870 0.0568 ms 48.9%
  triton_mm_4871 0.0641 ms 43.4%
  triton_mm_4878 0.0674 ms 41.3%
  triton_mm_4875 0.0696 ms 39.9%
  triton_mm_4884 0.0740 ms 37.6%
  triton_mm_4883 0.0746 ms 37.3%
  triton_mm_4877 0.0783 ms 35.5%
SingleProcess AUTOTUNE benchmarking takes 6.4417 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2198: UserWarning: Overwriting vit_tiny_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2207: UserWarning: Overwriting vit_tiny_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_tiny_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_tiny_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2216: UserWarning: Overwriting vit_small_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2225: UserWarning: Overwriting vit_small_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2234: UserWarning: Overwriting vit_small_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2243: UserWarning: Overwriting vit_small_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2252: UserWarning: Overwriting vit_small_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2261: UserWarning: Overwriting vit_base_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2271: UserWarning: Overwriting vit_base_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2281: UserWarning: Overwriting vit_base_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2291: UserWarning: Overwriting vit_base_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2301: UserWarning: Overwriting vit_base_patch8_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch8_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch8_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2311: UserWarning: Overwriting vit_large_patch32_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2320: UserWarning: Overwriting vit_large_patch32_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch32_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch32_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2330: UserWarning: Overwriting vit_large_patch16_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2340: UserWarning: Overwriting vit_large_patch16_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2350: UserWarning: Overwriting vit_large_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2359: UserWarning: Overwriting vit_huge_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2368: UserWarning: Overwriting vit_giant_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2377: UserWarning: Overwriting vit_gigantic_patch14_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2387: UserWarning: Overwriting vit_base_patch16_224_miil in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_224_miil. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_224_miil(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2398: UserWarning: Overwriting vit_medium_patch16_gap_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2410: UserWarning: Overwriting vit_medium_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2422: UserWarning: Overwriting vit_medium_patch16_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2434: UserWarning: Overwriting vit_betwixt_patch16_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2446: UserWarning: Overwriting vit_base_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2457: UserWarning: Overwriting vit_huge_patch14_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2468: UserWarning: Overwriting vit_huge_patch16_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch16_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch16_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2479: UserWarning: Overwriting vit_giant_patch16_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch16_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch16_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2491: UserWarning: Overwriting vit_xsmall_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_xsmall_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_xsmall_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2500: UserWarning: Overwriting vit_medium_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2510: UserWarning: Overwriting vit_medium_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2519: UserWarning: Overwriting vit_betwixt_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2529: UserWarning: Overwriting vit_base_patch32_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2540: UserWarning: Overwriting vit_base_patch32_clip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2551: UserWarning: Overwriting vit_base_patch32_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2562: UserWarning: Overwriting vit_base_patch32_clip_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2573: UserWarning: Overwriting vit_base_patch16_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2583: UserWarning: Overwriting vit_base_patch16_clip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2593: UserWarning: Overwriting vit_large_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2603: UserWarning: Overwriting vit_large_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2613: UserWarning: Overwriting vit_huge_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2623: UserWarning: Overwriting vit_huge_patch14_clip_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2633: UserWarning: Overwriting vit_huge_patch14_clip_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2643: UserWarning: Overwriting vit_giant_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2656: UserWarning: Overwriting vit_gigantic_patch14_clip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_gigantic_patch14_clip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_gigantic_patch14_clip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2669: UserWarning: Overwriting vit_base_patch32_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2681: UserWarning: Overwriting vit_base_patch16_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2693: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2705: UserWarning: Overwriting vit_large_patch14_clip_quickgelu_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_clip_quickgelu_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_clip_quickgelu_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2717: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2729: UserWarning: Overwriting vit_huge_patch14_clip_quickgelu_378 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_clip_quickgelu_378. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_clip_quickgelu_378(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2743: UserWarning: Overwriting vit_base_patch32_plus_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch32_plus_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch32_plus_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2753: UserWarning: Overwriting vit_base_patch16_plus_240 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_plus_240. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_plus_240(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2763: UserWarning: Overwriting vit_base_patch16_rpn_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_rpn_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_rpn_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2775: UserWarning: Overwriting vit_small_patch16_36x1_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_36x1_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_36x1_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2787: UserWarning: Overwriting vit_small_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2800: UserWarning: Overwriting vit_base_patch16_18x2_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_18x2_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_18x2_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2812: UserWarning: Overwriting eva_large_patch14_196 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_196. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_196(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2821: UserWarning: Overwriting eva_large_patch14_336 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.eva_large_patch14_336. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def eva_large_patch14_336(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2829: UserWarning: Overwriting flexivit_small in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_small. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_small(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2838: UserWarning: Overwriting flexivit_base in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_base. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_base(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2847: UserWarning: Overwriting flexivit_large in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.flexivit_large. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def flexivit_large(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2856: UserWarning: Overwriting vit_base_patch16_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2869: UserWarning: Overwriting vit_large_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2882: UserWarning: Overwriting vit_huge_patch14_xp_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_huge_patch14_xp_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_huge_patch14_xp_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2895: UserWarning: Overwriting vit_small_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2905: UserWarning: Overwriting vit_base_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2915: UserWarning: Overwriting vit_large_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2925: UserWarning: Overwriting vit_giant_patch14_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2942: UserWarning: Overwriting vit_small_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_small_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_small_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2955: UserWarning: Overwriting vit_base_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2968: UserWarning: Overwriting vit_large_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2981: UserWarning: Overwriting vit_giant_patch14_reg4_dinov2 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_giant_patch14_reg4_dinov2. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_giant_patch14_reg4_dinov2(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:2998: UserWarning: Overwriting vit_base_patch16_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3008: UserWarning: Overwriting vit_base_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3018: UserWarning: Overwriting vit_base_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3028: UserWarning: Overwriting vit_base_patch16_siglip_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3038: UserWarning: Overwriting vit_large_patch16_siglip_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3048: UserWarning: Overwriting vit_large_patch16_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3058: UserWarning: Overwriting vit_so400m_patch14_siglip_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3068: UserWarning: Overwriting vit_so400m_patch14_siglip_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3078: UserWarning: Overwriting vit_base_patch16_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3089: UserWarning: Overwriting vit_base_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3100: UserWarning: Overwriting vit_base_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3111: UserWarning: Overwriting vit_base_patch16_siglip_gap_512 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_siglip_gap_512. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_siglip_gap_512(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3122: UserWarning: Overwriting vit_large_patch16_siglip_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3133: UserWarning: Overwriting vit_large_patch16_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_large_patch16_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_large_patch16_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3144: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_224 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_224. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_224(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3156: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_384 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_384. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_384(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3168: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_448 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_448. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_448(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3180: UserWarning: Overwriting vit_so400m_patch14_siglip_gap_896 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so400m_patch14_siglip_gap_896. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so400m_patch14_siglip_gap_896(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3192: UserWarning: Overwriting vit_wee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_wee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_wee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3203: UserWarning: Overwriting vit_pwee_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_pwee_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_pwee_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3214: UserWarning: Overwriting vit_little_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3225: UserWarning: Overwriting vit_little_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_little_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_little_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3236: UserWarning: Overwriting vit_medium_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3247: UserWarning: Overwriting vit_medium_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_medium_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_medium_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3258: UserWarning: Overwriting vit_mediumd_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_mediumd_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_mediumd_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3269: UserWarning: Overwriting vit_betwixt_patch16_reg1_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg1_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg1_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3280: UserWarning: Overwriting vit_betwixt_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_betwixt_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_betwixt_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3291: UserWarning: Overwriting vit_base_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_base_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_base_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3302: UserWarning: Overwriting vit_so150m_patch16_reg4_map_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_map_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_map_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/vision_transformer.py:3313: UserWarning: Overwriting vit_so150m_patch16_reg4_gap_256 in registry with tokenizer.tokenizer_image.dino_enc.vision_transformer.vit_so150m_patch16_reg4_gap_256. This is because the name being registered conflicts with an existing name. Please check if this is not expected.
  def vit_so150m_patch16_reg4_gap_256(pretrained: bool = False, **kwargs) -> VisionTransformer:
/home/user/VAR/train.py:99: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  checkpoint = torch.load(vae_ckpt, map_location="cpu")
/home/user/VAR/utils/amp_sc.py:27: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.
  self.scaler = torch.cuda.amp.GradScaler(init_scale=2. ** 11, growth_interval=1000) if self.using_fp16_rather_bf16 else None # only fp16 needs a scaler
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
AUTOTUNE mm(6840x24, 24x1088)
  triton_mm_8 0.0266 ms 100.0%
  triton_mm_7 0.0269 ms 98.8%
  triton_mm_6 0.0276 ms 96.4%
  triton_mm_11 0.0277 ms 96.0%
  triton_mm_9 0.0278 ms 95.7%
  triton_mm_4 0.0279 ms 95.4%
  triton_mm_12 0.0279 ms 95.4%
  triton_mm_3 0.0282 ms 94.5%
  triton_mm_2 0.0283 ms 94.0%
  triton_mm_1 0.0299 ms 89.2%
SingleProcess AUTOTUNE benchmarking takes 2.2734 seconds and 0.0856 seconds precompiling
AUTOTUNE addmm(24x6528, 24x1088, 1088x6528)
  triton_mm_33 0.0222 ms 100.0%
  triton_mm_24 0.0224 ms 98.9%
  triton_mm_29 0.0228 ms 97.1%
  triton_mm_21 0.0230 ms 96.5%
  triton_mm_25 0.0230 ms 96.3%
  bias_addmm 0.0236 ms 93.8%
  triton_mm_28 0.0244 ms 91.1%
  triton_mm_18 0.0244 ms 90.7%
  triton_mm_19 0.0249 ms 89.0%
  triton_mm_20 0.0253 ms 87.6%
SingleProcess AUTOTUNE benchmarking takes 2.2102 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x3264, 6864x1088, 1088x3264)
  triton_mm_50 0.2214 ms 100.0%
  triton_mm_51 0.2257 ms 98.1%
  triton_mm_52 0.2538 ms 87.2%
  triton_mm_45 0.2611 ms 84.8%
  triton_mm_47 0.2708 ms 81.8%
  triton_mm_43 0.2742 ms 80.8%
  bias_addmm 0.2992 ms 74.0%
  triton_mm_44 0.3042 ms 72.8%
  triton_mm_48 0.3096 ms 71.5%
  addmm 0.3213 ms 68.9%
SingleProcess AUTOTUNE benchmarking takes 2.6286 seconds and 0.0119 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x1088, 1088x1088)
  triton_mm_70 0.0901 ms 100.0%
  triton_mm_69 0.0905 ms 99.5%
  bias_addmm 0.0953 ms 94.5%
  triton_mm_66 0.0985 ms 91.5%
  triton_mm_64 0.0988 ms 91.2%
  triton_mm_71 0.1005 ms 89.6%
  triton_mm_62 0.1022 ms 88.1%
  addmm 0.1099 ms 82.0%
  triton_mm_63 0.1119 ms 80.5%
  triton_mm_67 0.1133 ms 79.5%
SingleProcess AUTOTUNE benchmarking takes 2.5141 seconds and 0.0011 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_88 0.2942 ms 100.0%
  triton_mm_89 0.2952 ms 99.7%
  bias_addmm 0.3259 ms 90.3%
  triton_mm_90 0.3332 ms 88.3%
  triton_mm_83 0.3422 ms 86.0%
  triton_mm_81 0.3621 ms 81.3%
  triton_mm_85 0.3636 ms 80.9%
  addmm 0.3720 ms 79.1%
  triton_mm_82 0.3992 ms 73.7%
  triton_mm_86 0.4100 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6574 seconds and 0.0202 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2908 ms 100.0%
  triton_mm_108 0.3073 ms 94.6%
  triton_mm_107 0.3155 ms 92.2%
  triton_mm_109 0.3261 ms 89.2%
  addmm 0.3269 ms 89.0%
  triton_mm_104 0.3557 ms 81.8%
  triton_mm_102 0.3559 ms 81.7%
  triton_mm_100 0.3683 ms 79.0%
  triton_mm_103 0.3695 ms 78.7%
  triton_mm_105 0.4069 ms 71.5%
SingleProcess AUTOTUNE benchmarking takes 2.6562 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_181 0.2943 ms 100.0%
  triton_mm_182 0.3030 ms 97.1%
  bias_addmm 0.3253 ms 90.5%
  triton_mm_183 0.3351 ms 87.8%
  triton_mm_176 0.3413 ms 86.2%
  triton_mm_174 0.3623 ms 81.2%
  triton_mm_178 0.3627 ms 81.1%
  triton_mm_175 0.3995 ms 73.7%
  triton_mm_179 0.4110 ms 71.6%
  addmm 0.4164 ms 70.7%
SingleProcess AUTOTUNE benchmarking takes 2.6352 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2920 ms 100.0%
  triton_mm_201 0.3074 ms 95.0%
  triton_mm_200 0.3154 ms 92.6%
  triton_mm_202 0.3271 ms 89.2%
  addmm 0.3273 ms 89.2%
  triton_mm_195 0.3566 ms 81.9%
  triton_mm_197 0.3569 ms 81.8%
  triton_mm_193 0.3690 ms 79.1%
  triton_mm_196 0.3705 ms 78.8%
  triton_mm_198 0.4076 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6486 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_274 0.2950 ms 100.0%
  triton_mm_275 0.2960 ms 99.7%
  bias_addmm 0.3254 ms 90.7%
  triton_mm_276 0.3349 ms 88.1%
  triton_mm_269 0.3420 ms 86.2%
  triton_mm_267 0.3637 ms 81.1%
  triton_mm_271 0.3668 ms 80.4%
  triton_mm_268 0.4019 ms 73.4%
  triton_mm_272 0.4107 ms 71.8%
  addmm 0.4165 ms 70.8%
SingleProcess AUTOTUNE benchmarking takes 2.6390 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2929 ms 100.0%
  triton_mm_294 0.3073 ms 95.3%
  triton_mm_293 0.3168 ms 92.5%
  triton_mm_295 0.3274 ms 89.5%
  addmm 0.3282 ms 89.3%
  triton_mm_290 0.3567 ms 82.1%
  triton_mm_288 0.3568 ms 82.1%
  triton_mm_286 0.3703 ms 79.1%
  triton_mm_289 0.3718 ms 78.8%
  triton_mm_291 0.4077 ms 71.9%
SingleProcess AUTOTUNE benchmarking takes 2.6599 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_367 0.2952 ms 100.0%
  triton_mm_368 0.2959 ms 99.8%
  bias_addmm 0.3254 ms 90.7%
  triton_mm_369 0.3358 ms 87.9%
  triton_mm_362 0.3434 ms 86.0%
  triton_mm_360 0.3634 ms 81.2%
  triton_mm_364 0.3645 ms 81.0%
  triton_mm_361 0.4016 ms 73.5%
  triton_mm_365 0.4132 ms 71.4%
  addmm 0.4167 ms 70.8%
SingleProcess AUTOTUNE benchmarking takes 2.6509 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2924 ms 100.0%
  triton_mm_387 0.3079 ms 95.0%
  triton_mm_386 0.3163 ms 92.5%
  addmm 0.3278 ms 89.2%
  triton_mm_388 0.3278 ms 89.2%
  triton_mm_381 0.3564 ms 82.1%
  triton_mm_383 0.3580 ms 81.7%
  triton_mm_379 0.3708 ms 78.9%
  triton_mm_382 0.3712 ms 78.8%
  triton_mm_384 0.4082 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 2.6633 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x4352, 6864x1088, 1088x4352)
  triton_mm_460 0.2960 ms 100.0%
  triton_mm_461 0.2968 ms 99.7%
  bias_addmm 0.3254 ms 91.0%
  triton_mm_462 0.3350 ms 88.4%
  triton_mm_455 0.3444 ms 85.9%
  triton_mm_453 0.3645 ms 81.2%
  triton_mm_457 0.3652 ms 81.0%
  triton_mm_454 0.4025 ms 73.5%
  triton_mm_458 0.4138 ms 71.5%
  addmm 0.4164 ms 71.1%
SingleProcess AUTOTUNE benchmarking takes 2.6550 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  bias_addmm 0.2934 ms 100.0%
  triton_mm_480 0.3086 ms 95.1%
  triton_mm_479 0.3172 ms 92.5%
  triton_mm_481 0.3282 ms 89.4%
  addmm 0.3283 ms 89.4%
  triton_mm_474 0.3571 ms 82.2%
  triton_mm_476 0.3577 ms 82.0%
  triton_mm_472 0.3706 ms 79.2%
  triton_mm_475 0.3721 ms 78.8%
  triton_mm_477 0.4088 ms 71.8%
SingleProcess AUTOTUNE benchmarking takes 2.6567 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x1088, 6864x4352, 4352x1088)
  triton_mm_573 0.3075 ms 100.0%
  triton_mm_572 0.3173 ms 96.9%
  triton_mm_574 0.3273 ms 93.9%
  bias_addmm 0.3282 ms 93.7%
  triton_mm_567 0.3556 ms 86.5%
  triton_mm_569 0.3565 ms 86.2%
  addmm 0.3659 ms 84.0%
  triton_mm_565 0.3691 ms 83.3%
  triton_mm_568 0.3718 ms 82.7%
  triton_mm_570 0.4079 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.6578 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x1088, 1088x2176)
  triton_mm_1606 0.0138 ms 100.0%
  triton_mm_1602 0.0142 ms 97.1%
  triton_mm_1610 0.0147 ms 93.5%
  triton_mm_1614 0.0158 ms 86.9%
  mm 0.0166 ms 83.0%
  triton_mm_1601 0.0168 ms 81.8%
  triton_mm_1605 0.0172 ms 80.1%
  triton_mm_1600 0.0180 ms 76.6%
  triton_mm_1599 0.0185 ms 74.3%
  triton_mm_1609 0.0188 ms 73.4%
SingleProcess AUTOTUNE benchmarking takes 7.2707 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(6864x8192, 6864x1088, 1088x8192)
  triton_mm_1632 0.5541 ms 100.0%
  bias_addmm 0.5542 ms 100.0%
  triton_mm_1631 0.5580 ms 99.3%
  triton_mm_1626 0.6532 ms 84.8%
  triton_mm_1628 0.6882 ms 80.5%
  addmm 0.6958 ms 79.6%
  triton_mm_1624 0.7046 ms 78.6%
  triton_mm_1633 0.7297 ms 75.9%
  triton_mm_1629 0.7785 ms 71.2%
  triton_mm_1625 0.7795 ms 71.1%
SingleProcess AUTOTUNE benchmarking takes 11.7811 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(8192x6864, 6864x1088)
  mm 0.5267 ms 100.0%
  triton_mm_1669 0.5533 ms 95.2%
  triton_mm_1670 0.5712 ms 92.2%
  triton_mm_1671 0.5952 ms 88.5%
  triton_mm_1664 0.6636 ms 79.4%
  triton_mm_1666 0.6715 ms 78.4%
  triton_mm_1662 0.6763 ms 77.9%
  triton_mm_1665 0.7180 ms 73.4%
  triton_mm_1667 0.7250 ms 72.6%
  triton_mm_1663 0.7375 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 9.6738 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x4352)
  mm 0.2904 ms 100.0%
  triton_mm_1742 0.2934 ms 99.0%
  triton_mm_1741 0.2957 ms 98.2%
  triton_mm_1743 0.2988 ms 97.2%
  triton_mm_1736 0.3503 ms 82.9%
  triton_mm_1734 0.3536 ms 82.1%
  triton_mm_1738 0.3609 ms 80.5%
  triton_mm_1737 0.3782 ms 76.8%
  triton_mm_1739 0.3961 ms 73.3%
  triton_mm_1735 0.4018 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 9.9726 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(2176x24, 24x1088)
  triton_mm_1694 0.0114 ms 100.0%
  triton_mm_1695 0.0115 ms 98.9%
  triton_mm_1700 0.0115 ms 98.6%
  triton_mm_1701 0.0117 ms 97.0%
  triton_mm_1696 0.0119 ms 95.7%
  triton_mm_1693 0.0121 ms 93.7%
  triton_mm_1697 0.0123 ms 92.7%
  triton_mm_1698 0.0123 ms 92.1%
  triton_mm_1689 0.0124 ms 91.5%
  triton_mm_1699 0.0125 ms 91.1%
SingleProcess AUTOTUNE benchmarking takes 5.9954 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x2176, 2176x1088)
  triton_mm_1676 0.0164 ms 100.0%
  mm 0.0170 ms 96.8%
  triton_mm_1680 0.0172 ms 95.5%
  triton_mm_1684 0.0210 ms 78.3%
  triton_mm_1675 0.0219 ms 74.9%
  triton_mm_1688 0.0223 ms 73.7%
  triton_mm_1674 0.0242 ms 67.9%
  triton_mm_1679 0.0247 ms 66.5%
  triton_mm_1683 0.0253 ms 64.8%
  triton_mm_1673 0.0258 ms 63.6%
SingleProcess AUTOTUNE benchmarking takes 7.7763 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x8192, 8192x1088)
  mm 0.5373 ms 100.0%
  triton_mm_1650 0.5648 ms 95.1%
  triton_mm_1651 0.5750 ms 93.4%
  triton_mm_1652 0.5888 ms 91.2%
  triton_mm_1645 0.6607 ms 81.3%
  triton_mm_1647 0.6615 ms 81.2%
  triton_mm_1643 0.6717 ms 80.0%
  triton_mm_1646 0.6932 ms 77.5%
  triton_mm_1644 0.7183 ms 74.8%
  triton_mm_1648 0.7311 ms 73.5%
SingleProcess AUTOTUNE benchmarking takes 9.6868 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x4352)
  mm 0.2767 ms 100.0%
  triton_mm_1722 0.2774 ms 99.7%
  triton_mm_1723 0.2792 ms 99.1%
  triton_mm_1715 0.3369 ms 82.1%
  triton_mm_1717 0.3383 ms 81.8%
  triton_mm_1719 0.3483 ms 79.4%
  triton_mm_1716 0.3601 ms 76.8%
  triton_mm_1724 0.3703 ms 74.7%
  triton_mm_1720 0.3863 ms 71.6%
  triton_mm_1718 0.4185 ms 66.1%
SingleProcess AUTOTUNE benchmarking takes 10.2238 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_1837 0.2246 ms 100.0%
  triton_mm_1836 0.2309 ms 97.2%
  mm 0.2564 ms 87.6%
  triton_mm_1833 0.2579 ms 87.1%
  triton_mm_1831 0.2626 ms 85.5%
  triton_mm_1829 0.2638 ms 85.1%
  triton_mm_1838 0.2823 ms 79.5%
  triton_mm_1832 0.2872 ms 78.2%
  triton_mm_1830 0.2915 ms 77.1%
  triton_mm_1834 0.2975 ms 75.5%
SingleProcess AUTOTUNE benchmarking takes 9.9179 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1779 0.2873 ms 100.0%
  mm 0.2901 ms 99.0%
  triton_mm_1780 0.2917 ms 98.5%
  triton_mm_1781 0.3422 ms 84.0%
  triton_mm_1776 0.3441 ms 83.5%
  triton_mm_1772 0.3506 ms 81.9%
  triton_mm_1774 0.3547 ms 81.0%
  triton_mm_1775 0.3800 ms 75.6%
  triton_mm_1777 0.3899 ms 73.7%
  triton_mm_1773 0.3967 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 9.9113 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2244 ms 100.0%
  triton_mm_1855 0.2777 ms 80.8%
  triton_mm_1850 0.2830 ms 79.3%
  triton_mm_1856 0.2849 ms 78.8%
  triton_mm_1852 0.2852 ms 78.7%
  triton_mm_1848 0.2879 ms 77.9%
  triton_mm_1857 0.2897 ms 77.4%
  triton_mm_1851 0.3142 ms 71.4%
  triton_mm_1853 0.3255 ms 68.9%
  triton_mm_1849 0.3301 ms 68.0%
SingleProcess AUTOTUNE benchmarking takes 2.5119 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  triton_mm_1819 0.0983 ms 100.0%
  mm 0.1004 ms 97.9%
  triton_mm_1812 0.1041 ms 94.4%
  triton_mm_1818 0.1078 ms 91.2%
  triton_mm_1809 0.1178 ms 83.4%
  triton_mm_1810 0.1183 ms 83.1%
  triton_mm_1814 0.1196 ms 82.2%
  triton_mm_1817 0.1197 ms 82.1%
  triton_mm_1815 0.1301 ms 75.6%
  triton_mm_1808 0.1326 ms 74.1%
SingleProcess AUTOTUNE benchmarking takes 9.8079 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3027 ms 100.0%
  triton_mm_1760 0.3044 ms 99.4%
  triton_mm_1761 0.3115 ms 97.2%
  triton_mm_1762 0.3208 ms 94.4%
  triton_mm_1757 0.3444 ms 87.9%
  triton_mm_1755 0.3489 ms 86.8%
  triton_mm_1753 0.3515 ms 86.1%
  triton_mm_1756 0.3650 ms 82.9%
  triton_mm_1754 0.3869 ms 78.2%
  triton_mm_1758 0.3951 ms 76.6%
SingleProcess AUTOTUNE benchmarking takes 13.2516 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  triton_mm_1799 0.0842 ms 100.0%
  mm 0.0851 ms 98.9%
  triton_mm_1798 0.0861 ms 97.8%
  triton_mm_1795 0.0920 ms 91.5%
  triton_mm_1791 0.0946 ms 89.0%
  triton_mm_1800 0.0948 ms 88.8%
  triton_mm_1793 0.0960 ms 87.8%
  triton_mm_1792 0.1029 ms 81.8%
  triton_mm_1796 0.1059 ms 79.5%
  triton_mm_1794 0.1236 ms 68.1%
SingleProcess AUTOTUNE benchmarking takes 10.1596 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.3029 ms 100.0%
  triton_mm_1946 0.3039 ms 99.7%
  triton_mm_1947 0.3122 ms 97.0%
  triton_mm_1948 0.3219 ms 94.1%
  triton_mm_1943 0.3462 ms 87.5%
  triton_mm_1941 0.3504 ms 86.5%
  triton_mm_1939 0.3522 ms 86.0%
  triton_mm_1942 0.3658 ms 82.8%
  triton_mm_1940 0.3877 ms 78.1%
  triton_mm_1944 0.3952 ms 76.7%
SingleProcess AUTOTUNE benchmarking takes 2.5296 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_1887 0.0171 ms 100.0%
  triton_mm_1883 0.0172 ms 99.4%
  triton_mm_1886 0.0172 ms 98.9%
  triton_mm_1881 0.0181 ms 94.0%
  triton_mm_1885 0.0182 ms 93.7%
  triton_mm_1890 0.0184 ms 92.7%
  triton_mm_1884 0.0184 ms 92.5%
  triton_mm_1888 0.0188 ms 90.8%
  triton_mm_1880 0.0191 ms 89.1%
  triton_mm_1882 0.0192 ms 88.8%
SingleProcess AUTOTUNE benchmarking takes 5.7657 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_1965 0.2909 ms 100.0%
  mm 0.2936 ms 99.1%
  triton_mm_1966 0.2969 ms 98.0%
  triton_mm_1967 0.3029 ms 96.0%
  triton_mm_1962 0.3482 ms 83.5%
  triton_mm_1958 0.3550 ms 81.9%
  triton_mm_1960 0.3599 ms 80.8%
  triton_mm_1961 0.3852 ms 75.5%
  triton_mm_1963 0.3940 ms 73.8%
  triton_mm_1959 0.4021 ms 72.3%
SingleProcess AUTOTUNE benchmarking takes 2.5312 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0267 ms 100.0%
  triton_mm_1862 0.0276 ms 96.5%
  triton_mm_1866 0.0305 ms 87.4%
  triton_mm_1870 0.0398 ms 67.1%
  triton_mm_1874 0.0506 ms 52.7%
  triton_mm_1861 0.0523 ms 51.1%
  triton_mm_1860 0.0559 ms 47.7%
  triton_mm_1865 0.0594 ms 45.0%
  triton_mm_1869 0.0616 ms 43.3%
  triton_mm_1859 0.0660 ms 40.4%
SingleProcess AUTOTUNE benchmarking takes 2.0730 seconds and 0.0008 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2250 ms 100.0%
  triton_mm_2041 0.2772 ms 81.2%
  triton_mm_2036 0.2843 ms 79.2%
  triton_mm_2042 0.2846 ms 79.1%
  triton_mm_2038 0.2856 ms 78.8%
  triton_mm_2034 0.2893 ms 77.8%
  triton_mm_2043 0.2899 ms 77.6%
  triton_mm_2037 0.3132 ms 71.8%
  triton_mm_2039 0.3268 ms 68.9%
  triton_mm_2035 0.3316 ms 67.9%
SingleProcess AUTOTUNE benchmarking takes 2.5097 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0971 ms 100.0%
  triton_mm_2005 0.0993 ms 97.7%
  triton_mm_1998 0.1052 ms 92.3%
  triton_mm_2004 0.1081 ms 89.8%
  triton_mm_1995 0.1181 ms 82.2%
  triton_mm_1996 0.1195 ms 81.2%
  triton_mm_2000 0.1197 ms 81.1%
  triton_mm_2003 0.1218 ms 79.7%
  triton_mm_1999 0.1270 ms 76.4%
  triton_mm_2001 0.1305 ms 74.4%
SingleProcess AUTOTUNE benchmarking takes 2.4015 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x1088, 1088x1088)
  mm 0.0832 ms 100.0%
  triton_mm_1985 0.0833 ms 99.8%
  triton_mm_1984 0.0853 ms 97.5%
  triton_mm_1981 0.0922 ms 90.2%
  triton_mm_1986 0.0948 ms 87.7%
  triton_mm_1979 0.0950 ms 87.6%
  triton_mm_1977 0.0956 ms 87.0%
  triton_mm_1978 0.1026 ms 81.1%
  triton_mm_1982 0.1059 ms 78.5%
  triton_mm_1980 0.1236 ms 67.3%
SingleProcess AUTOTUNE benchmarking takes 2.4112 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2253 ms 100.0%
  triton_mm_2023 0.2254 ms 99.9%
  triton_mm_2022 0.2313 ms 97.4%
  triton_mm_2024 0.2441 ms 92.3%
  triton_mm_2019 0.2600 ms 86.6%
  triton_mm_2017 0.2642 ms 85.3%
  triton_mm_2015 0.2658 ms 84.8%
  triton_mm_2018 0.2884 ms 78.1%
  triton_mm_2016 0.2921 ms 77.1%
  triton_mm_2020 0.2990 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5070 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2999 ms 100.0%
  triton_mm_2132 0.3057 ms 98.1%
  triton_mm_2133 0.3132 ms 95.8%
  triton_mm_2134 0.3213 ms 93.3%
  triton_mm_2129 0.3466 ms 86.5%
  triton_mm_2127 0.3522 ms 85.2%
  triton_mm_2125 0.3536 ms 84.8%
  triton_mm_2128 0.3668 ms 81.8%
  triton_mm_2126 0.3890 ms 77.1%
  triton_mm_2130 0.3966 ms 75.6%
SingleProcess AUTOTUNE benchmarking takes 2.5332 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2069 0.0171 ms 100.0%
  triton_mm_2067 0.0172 ms 99.8%
  triton_mm_2071 0.0182 ms 93.9%
  triton_mm_2073 0.0183 ms 93.4%
  triton_mm_2070 0.0185 ms 92.7%
  triton_mm_2072 0.0185 ms 92.7%
  triton_mm_2066 0.0191 ms 89.6%
  triton_mm_2068 0.0192 ms 89.4%
  triton_mm_2074 0.0193 ms 88.5%
  triton_mm_2075 0.0195 ms 87.8%
SingleProcess AUTOTUNE benchmarking takes 2.1232 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2151 0.2920 ms 100.0%
  mm 0.2921 ms 100.0%
  triton_mm_2152 0.2977 ms 98.1%
  triton_mm_2153 0.3034 ms 96.3%
  triton_mm_2148 0.3492 ms 83.6%
  triton_mm_2144 0.3568 ms 81.8%
  triton_mm_2146 0.3611 ms 80.9%
  triton_mm_2147 0.3874 ms 75.4%
  triton_mm_2149 0.3944 ms 74.0%
  triton_mm_2145 0.4023 ms 72.6%
SingleProcess AUTOTUNE benchmarking takes 2.5332 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0268 ms 100.0%
  triton_mm_2048 0.0275 ms 97.5%
  triton_mm_2052 0.0305 ms 87.8%
  triton_mm_2056 0.0408 ms 65.7%
  triton_mm_2060 0.0506 ms 52.9%
  triton_mm_2047 0.0515 ms 52.0%
  triton_mm_2046 0.0561 ms 47.8%
  triton_mm_2051 0.0594 ms 45.1%
  triton_mm_2055 0.0623 ms 43.0%
  triton_mm_2045 0.0652 ms 41.1%
SingleProcess AUTOTUNE benchmarking takes 2.0790 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2252 ms 100.0%
  triton_mm_2227 0.2772 ms 81.3%
  triton_mm_2222 0.2856 ms 78.9%
  triton_mm_2228 0.2857 ms 78.8%
  triton_mm_2224 0.2862 ms 78.7%
  triton_mm_2220 0.2885 ms 78.1%
  triton_mm_2229 0.2900 ms 77.7%
  triton_mm_2223 0.3142 ms 71.7%
  triton_mm_2225 0.3268 ms 68.9%
  triton_mm_2221 0.3313 ms 68.0%
SingleProcess AUTOTUNE benchmarking takes 2.5157 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0980 ms 100.0%
  triton_mm_2191 0.0994 ms 98.6%
  triton_mm_2184 0.1052 ms 93.1%
  triton_mm_2190 0.1079 ms 90.8%
  triton_mm_2181 0.1181 ms 82.9%
  triton_mm_2182 0.1195 ms 82.0%
  triton_mm_2186 0.1198 ms 81.8%
  triton_mm_2189 0.1219 ms 80.4%
  triton_mm_2185 0.1271 ms 77.0%
  triton_mm_2187 0.1309 ms 74.8%
SingleProcess AUTOTUNE benchmarking takes 2.4078 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2249 ms 100.0%
  triton_mm_2209 0.2256 ms 99.7%
  triton_mm_2208 0.2316 ms 97.1%
  triton_mm_2210 0.2442 ms 92.1%
  triton_mm_2205 0.2600 ms 86.5%
  triton_mm_2203 0.2643 ms 85.1%
  triton_mm_2201 0.2653 ms 84.8%
  triton_mm_2204 0.2884 ms 78.0%
  triton_mm_2202 0.2929 ms 76.8%
  triton_mm_2206 0.2993 ms 75.1%
SingleProcess AUTOTUNE benchmarking takes 2.5029 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2993 ms 100.0%
  triton_mm_2318 0.3057 ms 97.9%
  triton_mm_2319 0.3120 ms 95.9%
  triton_mm_2320 0.3221 ms 92.9%
  triton_mm_2315 0.3462 ms 86.4%
  triton_mm_2313 0.3502 ms 85.5%
  triton_mm_2311 0.3519 ms 85.1%
  triton_mm_2314 0.3659 ms 81.8%
  triton_mm_2312 0.3873 ms 77.3%
  triton_mm_2316 0.3966 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.5409 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2259 0.0171 ms 100.0%
  triton_mm_2253 0.0172 ms 99.6%
  triton_mm_2256 0.0172 ms 99.3%
  triton_mm_2258 0.0179 ms 95.7%
  triton_mm_2260 0.0182 ms 94.0%
  triton_mm_2257 0.0182 ms 93.7%
  triton_mm_2255 0.0183 ms 93.4%
  triton_mm_2254 0.0189 ms 90.5%
  triton_mm_2252 0.0191 ms 89.3%
  triton_mm_2263 0.0196 ms 87.4%
SingleProcess AUTOTUNE benchmarking takes 2.1593 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2337 0.2913 ms 100.0%
  mm 0.2920 ms 99.8%
  triton_mm_2338 0.2957 ms 98.5%
  triton_mm_2339 0.3020 ms 96.5%
  triton_mm_2334 0.3496 ms 83.3%
  triton_mm_2330 0.3578 ms 81.4%
  triton_mm_2332 0.3605 ms 80.8%
  triton_mm_2333 0.3864 ms 75.4%
  triton_mm_2335 0.3959 ms 73.6%
  triton_mm_2331 0.4026 ms 72.4%
SingleProcess AUTOTUNE benchmarking takes 2.5464 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  triton_mm_2234 0.0265 ms 100.0%
  mm 0.0269 ms 98.7%
  triton_mm_2238 0.0318 ms 83.5%
  triton_mm_2242 0.0402 ms 66.1%
  triton_mm_2246 0.0507 ms 52.4%
  triton_mm_2233 0.0524 ms 50.7%
  triton_mm_2232 0.0551 ms 48.1%
  triton_mm_2237 0.0602 ms 44.0%
  triton_mm_2241 0.0624 ms 42.5%
  triton_mm_2231 0.0652 ms 40.7%
SingleProcess AUTOTUNE benchmarking takes 2.1147 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(3264x6864, 6864x1088)
  mm 0.2249 ms 100.0%
  triton_mm_2413 0.2772 ms 81.1%
  triton_mm_2408 0.2849 ms 78.9%
  triton_mm_2414 0.2858 ms 78.7%
  triton_mm_2410 0.2865 ms 78.5%
  triton_mm_2406 0.2877 ms 78.2%
  triton_mm_2415 0.2899 ms 77.6%
  triton_mm_2409 0.3136 ms 71.7%
  triton_mm_2411 0.3258 ms 69.0%
  triton_mm_2407 0.3315 ms 67.8%
SingleProcess AUTOTUNE benchmarking takes 2.5247 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6864, 6864x1088)
  mm 0.0970 ms 100.0%
  triton_mm_2377 0.0985 ms 98.5%
  triton_mm_2370 0.1044 ms 92.9%
  triton_mm_2376 0.1073 ms 90.4%
  triton_mm_2368 0.1188 ms 81.6%
  triton_mm_2367 0.1189 ms 81.6%
  triton_mm_2372 0.1206 ms 80.4%
  triton_mm_2375 0.1212 ms 80.0%
  triton_mm_2371 0.1262 ms 76.8%
  triton_mm_2373 0.1299 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.4360 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2242 ms 100.0%
  triton_mm_2395 0.2263 ms 99.1%
  triton_mm_2394 0.2305 ms 97.3%
  triton_mm_2396 0.2434 ms 92.1%
  triton_mm_2391 0.2590 ms 86.6%
  triton_mm_2389 0.2632 ms 85.2%
  triton_mm_2387 0.2660 ms 84.3%
  triton_mm_2390 0.2892 ms 77.5%
  triton_mm_2388 0.2916 ms 76.9%
  triton_mm_2392 0.2983 ms 75.2%
SingleProcess AUTOTUNE benchmarking takes 2.5160 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x4352, 4352x1088)
  mm 0.2988 ms 100.0%
  triton_mm_2504 0.3054 ms 97.9%
  triton_mm_2505 0.3119 ms 95.8%
  triton_mm_2506 0.3219 ms 92.8%
  triton_mm_2501 0.3458 ms 86.4%
  triton_mm_2499 0.3514 ms 85.0%
  triton_mm_2497 0.3527 ms 84.7%
  triton_mm_2500 0.3658 ms 81.7%
  triton_mm_2498 0.3880 ms 77.0%
  triton_mm_2502 0.3963 ms 75.4%
SingleProcess AUTOTUNE benchmarking takes 2.5446 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6528x24, 24x1088)
  triton_mm_2444 0.0172 ms 100.0%
  triton_mm_2446 0.0181 ms 94.9%
  triton_mm_2439 0.0182 ms 94.4%
  triton_mm_2440 0.0182 ms 94.4%
  triton_mm_2443 0.0182 ms 94.4%
  triton_mm_2445 0.0183 ms 94.2%
  triton_mm_2441 0.0184 ms 93.4%
  triton_mm_2442 0.0185 ms 93.2%
  triton_mm_2438 0.0191 ms 90.1%
  triton_mm_2449 0.0195 ms 88.3%
SingleProcess AUTOTUNE benchmarking takes 2.1584 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(4352x6864, 6864x1088)
  triton_mm_2523 0.2909 ms 100.0%
  mm 0.2917 ms 99.7%
  triton_mm_2524 0.2967 ms 98.1%
  triton_mm_2525 0.3034 ms 95.9%
  triton_mm_2520 0.3489 ms 83.4%
  triton_mm_2516 0.3572 ms 81.5%
  triton_mm_2518 0.3599 ms 80.8%
  triton_mm_2519 0.3863 ms 75.3%
  triton_mm_2521 0.3946 ms 73.7%
  triton_mm_2517 0.4014 ms 72.5%
SingleProcess AUTOTUNE benchmarking takes 2.5473 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0265 ms 100.0%
  triton_mm_2420 0.0266 ms 99.8%
  triton_mm_2424 0.0305 ms 86.8%
  triton_mm_2428 0.0398 ms 66.6%
  triton_mm_2432 0.0506 ms 52.3%
  triton_mm_2419 0.0523 ms 50.7%
  triton_mm_2418 0.0551 ms 48.1%
  triton_mm_2423 0.0602 ms 44.0%
  triton_mm_2427 0.0616 ms 43.0%
  triton_mm_2417 0.0653 ms 40.6%
SingleProcess AUTOTUNE benchmarking takes 2.1031 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2225 ms 100.0%
  triton_mm_2581 0.2265 ms 98.2%
  triton_mm_2580 0.2312 ms 96.2%
  triton_mm_2582 0.2434 ms 91.4%
  triton_mm_2577 0.2587 ms 86.0%
  triton_mm_2575 0.2631 ms 84.5%
  triton_mm_2573 0.2653 ms 83.8%
  triton_mm_2576 0.2887 ms 77.1%
  triton_mm_2574 0.2916 ms 76.3%
  triton_mm_2578 0.2979 ms 74.7%
SingleProcess AUTOTUNE benchmarking takes 2.5160 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0266 ms 100.0%
  triton_mm_2606 0.0274 ms 97.1%
  triton_mm_2610 0.0305 ms 87.3%
  triton_mm_2614 0.0408 ms 65.1%
  triton_mm_2618 0.0506 ms 52.6%
  triton_mm_2605 0.0515 ms 51.7%
  triton_mm_2604 0.0552 ms 48.2%
  triton_mm_2609 0.0593 ms 44.8%
  triton_mm_2613 0.0615 ms 43.2%
  triton_mm_2603 0.0658 ms 40.4%
SingleProcess AUTOTUNE benchmarking takes 2.0947 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  mm 0.2248 ms 100.0%
  triton_mm_2767 0.2251 ms 99.9%
  triton_mm_2766 0.2311 ms 97.3%
  triton_mm_2768 0.2438 ms 92.2%
  triton_mm_2763 0.2598 ms 86.5%
  triton_mm_2759 0.2636 ms 85.3%
  triton_mm_2761 0.2637 ms 85.2%
  triton_mm_2762 0.2881 ms 78.0%
  triton_mm_2760 0.2916 ms 77.1%
  triton_mm_2764 0.2984 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5105 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(24x6528, 6528x1088)
  mm 0.0264 ms 100.0%
  triton_mm_2792 0.0274 ms 96.4%
  triton_mm_2796 0.0316 ms 83.6%
  triton_mm_2800 0.0397 ms 66.4%
  triton_mm_2804 0.0506 ms 52.1%
  triton_mm_2791 0.0523 ms 50.5%
  triton_mm_2790 0.0557 ms 47.4%
  triton_mm_2795 0.0593 ms 44.5%
  triton_mm_2799 0.0615 ms 42.9%
  triton_mm_2789 0.0650 ms 40.6%
SingleProcess AUTOTUNE benchmarking takes 2.0896 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(6864x3264, 3264x1088)
  triton_mm_2953 0.2249 ms 100.0%
  mm 0.2251 ms 99.9%
  triton_mm_2952 0.2312 ms 97.3%
  triton_mm_2954 0.2437 ms 92.3%
  triton_mm_2949 0.2596 ms 86.6%
  triton_mm_2947 0.2635 ms 85.4%
  triton_mm_2945 0.2640 ms 85.2%
  triton_mm_2948 0.2878 ms 78.1%
  triton_mm_2946 0.2915 ms 77.1%
  triton_mm_2950 0.2987 ms 75.3%
SingleProcess AUTOTUNE benchmarking takes 2.5158 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(1088x6840, 6840x24)
  mm 0.0274 ms 100.0%
  triton_mm_4879 0.0492 ms 55.6%
  triton_mm_4872 0.0494 ms 55.3%
  triton_mm_4870 0.0559 ms 49.0%
  triton_mm_4871 0.0628 ms 43.6%
  triton_mm_4878 0.0666 ms 41.1%
  triton_mm_4875 0.0693 ms 39.5%
  triton_mm_4883 0.0734 ms 37.3%
  triton_mm_4884 0.0740 ms 36.9%
  triton_mm_4877 0.0780 ms 35.1%
SingleProcess AUTOTUNE benchmarking takes 6.8455 seconds and 0.0000 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8329 ms 100.0%
  mm 0.9425 ms 88.4%
  triton_mm_4987 0.9932 ms 83.9%
  triton_mm_4983 1.0106 ms 82.4%
  triton_mm_4991 1.0645 ms 78.2%
  triton_mm_4988 1.1129 ms 74.8%
  triton_mm_4984 1.1148 ms 74.7%
  triton_mm_4985 1.1464 ms 72.7%
  triton_mm_4980 1.3488 ms 61.8%
  triton_mm_4981 1.4167 ms 58.8%
SingleProcess AUTOTUNE benchmarking takes 2.1370 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8340 ms 100.0%
  mm 0.8369 ms 99.7%
  triton_mm_5080 1.0008 ms 83.3%
  triton_mm_5076 1.0095 ms 82.6%
  triton_mm_5084 1.0768 ms 77.5%
  triton_mm_5081 1.1135 ms 74.9%
  triton_mm_5077 1.1145 ms 74.8%
  triton_mm_5078 1.1467 ms 72.7%
  triton_mm_5073 1.3463 ms 62.0%
  triton_mm_5082 1.4277 ms 58.4%
SingleProcess AUTOTUNE benchmarking takes 2.1322 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0364 ms 100.0%
  triton_mm_4892 0.0377 ms 96.4%
  triton_mm_4899 0.0380 ms 95.8%
  triton_mm_4895 0.0380 ms 95.7%
  triton_mm_4896 0.0381 ms 95.5%
  triton_mm_4898 0.0390 ms 93.2%
  triton_mm_4887 0.0411 ms 88.5%
  triton_mm_4894 0.0420 ms 86.6%
  triton_mm_4888 0.0460 ms 79.1%
  triton_mm_4891 0.0508 ms 71.6%
SingleProcess AUTOTUNE benchmarking takes 1.6416 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4914 0.0346 ms 100.0%
  triton_mm_4909 0.0351 ms 98.4%
  triton_mm_4908 0.0352 ms 98.1%
  triton_mm_4913 0.0354 ms 97.7%
  triton_mm_4910 0.0361 ms 95.7%
  triton_mm_4911 0.0363 ms 95.2%
  triton_mm_4906 0.0373 ms 92.6%
  triton_mm_4907 0.0380 ms 91.0%
  triton_mm_4912 0.0380 ms 90.8%
  triton_mm_4915 0.0381 ms 90.8%
SingleProcess AUTOTUNE benchmarking takes 2.0948 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6432 ms 100.0%
  bias_addmm 0.6434 ms 100.0%
  triton_mm_4932 0.7538 ms 85.3%
  triton_mm_4928 0.7644 ms 84.1%
  addmm 0.7972 ms 80.7%
  triton_mm_4936 0.8391 ms 76.7%
  triton_mm_4933 0.8430 ms 76.3%
  triton_mm_4929 0.8505 ms 75.6%
  triton_mm_4930 0.8811 ms 73.0%
  triton_mm_4925 1.0154 ms 63.4%
SingleProcess AUTOTUNE benchmarking takes 2.2301 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2255 ms 100.0%
  mm 0.2363 ms 95.4%
  triton_mm_4951 0.2559 ms 88.1%
  triton_mm_4947 0.2683 ms 84.0%
  triton_mm_4952 0.2804 ms 80.4%
  triton_mm_4955 0.2896 ms 77.9%
  triton_mm_4948 0.2978 ms 75.7%
  triton_mm_4949 0.3076 ms 73.3%
  triton_mm_4944 0.3418 ms 66.0%
  triton_mm_4945 0.3552 ms 63.5%
SingleProcess AUTOTUNE benchmarking takes 2.0154 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8417 ms 100.0%
  mm 0.8797 ms 95.7%
  triton_mm_5010 1.0068 ms 83.6%
  triton_mm_5006 1.0183 ms 82.7%
  triton_mm_5002 1.0593 ms 79.5%
  triton_mm_5007 1.0754 ms 78.3%
  triton_mm_5003 1.1251 ms 74.8%
  triton_mm_5004 1.1448 ms 73.5%
  triton_mm_4999 1.3707 ms 61.4%
  triton_mm_5000 1.3797 ms 61.0%
SingleProcess AUTOTUNE benchmarking takes 2.1415 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_6256 0.2247 ms 100.0%
  mm 0.2354 ms 95.5%
  triton_mm_6253 0.2550 ms 88.1%
  triton_mm_6249 0.2682 ms 83.8%
  triton_mm_6254 0.2812 ms 79.9%
  triton_mm_6257 0.2900 ms 77.5%
  triton_mm_6250 0.2968 ms 75.7%
  triton_mm_6251 0.3068 ms 73.3%
  triton_mm_6246 0.3416 ms 65.8%
  triton_mm_6247 0.3544 ms 63.4%
SingleProcess AUTOTUNE benchmarking takes 2.0137 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_6311 0.8373 ms 100.0%
  mm 0.8797 ms 95.2%
  triton_mm_6312 1.0072 ms 83.1%
  triton_mm_6308 1.0180 ms 82.3%
  triton_mm_6304 1.0577 ms 79.2%
  triton_mm_6309 1.0837 ms 77.3%
  triton_mm_6305 1.1252 ms 74.4%
  triton_mm_6306 1.1432 ms 73.2%
  triton_mm_6301 1.3682 ms 61.2%
  triton_mm_6302 1.3793 ms 60.7%
SingleProcess AUTOTUNE benchmarking takes 2.1325 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_6330 0.6429 ms 100.0%
  bias_addmm 0.6468 ms 99.4%
  triton_mm_6327 0.7534 ms 85.3%
  triton_mm_6323 0.7582 ms 84.8%
  addmm 0.8020 ms 80.2%
  triton_mm_6331 0.8391 ms 76.6%
  triton_mm_6328 0.8427 ms 76.3%
  triton_mm_6324 0.8497 ms 75.7%
  triton_mm_6325 0.8811 ms 73.0%
  triton_mm_6320 1.0151 ms 63.3%
SingleProcess AUTOTUNE benchmarking takes 2.2395 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6447 0.0214 ms 100.0%
  triton_mm_6448 0.0219 ms 97.8%
  mm 0.0219 ms 97.5%
  triton_mm_6452 0.0242 ms 88.5%
  triton_mm_6459 0.0246 ms 86.8%
  triton_mm_6446 0.0253 ms 84.3%
  triton_mm_6456 0.0268 ms 79.6%
  triton_mm_6458 0.0273 ms 78.2%
  triton_mm_6455 0.0281 ms 76.0%
  triton_mm_6454 0.0314 ms 68.1%
SingleProcess AUTOTUNE benchmarking takes 1.6413 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5441 ms 100.0%
  bias_addmm 1.5699 ms 98.4%
  triton_mm_6513 1.8780 ms 82.2%
  addmm 1.9296 ms 80.0%
  triton_mm_6509 1.9338 ms 79.8%
  triton_mm_6517 2.0057 ms 77.0%
  triton_mm_6514 2.0939 ms 73.7%
  triton_mm_6510 2.1464 ms 71.9%
  triton_mm_6511 2.1837 ms 70.7%
  triton_mm_6506 2.5404 ms 60.8%
SingleProcess AUTOTUNE benchmarking takes 2.3946 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:22<1:42:14, 142.67s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8217 ms 100.0%
  mm 0.9400 ms 87.4%
  triton_mm_4987 0.9796 ms 83.9%
  triton_mm_4983 1.0008 ms 82.1%
  triton_mm_4991 1.0533 ms 78.0%
  triton_mm_4988 1.1011 ms 74.6%
  triton_mm_4984 1.1140 ms 73.8%
  triton_mm_4985 1.1284 ms 72.8%
  triton_mm_4980 1.3302 ms 61.8%
  triton_mm_4981 1.3957 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1373 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8228 ms 100.0%
  mm 0.8332 ms 98.7%
  triton_mm_5080 0.9803 ms 83.9%
  triton_mm_5076 1.0000 ms 82.3%
  triton_mm_5084 1.0646 ms 77.3%
  triton_mm_5081 1.1017 ms 74.7%
  triton_mm_5077 1.1144 ms 73.8%
  triton_mm_5078 1.1291 ms 72.9%
  triton_mm_5073 1.3303 ms 61.8%
  triton_mm_5074 1.3963 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1507 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.8316 ms 100.0%
  triton_mm_5269 0.8319 ms 100.0%
  triton_mm_5266 0.9845 ms 84.5%
  triton_mm_5262 1.0008 ms 83.1%
  triton_mm_5270 1.0661 ms 78.0%
  triton_mm_5267 1.1012 ms 75.5%
  triton_mm_5263 1.1124 ms 74.8%
  triton_mm_5264 1.1300 ms 73.6%
  triton_mm_5259 1.3436 ms 61.9%
  triton_mm_5260 1.3964 ms 59.6%
SingleProcess AUTOTUNE benchmarking takes 2.1521 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5455 0.8263 ms 100.0%
  mm 0.8328 ms 99.2%
  triton_mm_5452 0.9911 ms 83.4%
  triton_mm_5448 0.9997 ms 82.7%
  triton_mm_5456 1.0697 ms 77.2%
  triton_mm_5453 1.1032 ms 74.9%
  triton_mm_5449 1.1133 ms 74.2%
  triton_mm_5450 1.1358 ms 72.7%
  triton_mm_5445 1.3424 ms 61.6%
  triton_mm_5446 1.4092 ms 58.6%
SingleProcess AUTOTUNE benchmarking takes 2.1442 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5548 0.8237 ms 100.0%
  mm 0.8329 ms 98.9%
  triton_mm_5545 0.9904 ms 83.2%
  triton_mm_5541 0.9998 ms 82.4%
  triton_mm_5549 1.0641 ms 77.4%
  triton_mm_5546 1.1129 ms 74.0%
  triton_mm_5542 1.1138 ms 74.0%
  triton_mm_5543 1.1314 ms 72.8%
  triton_mm_5538 1.3308 ms 61.9%
  triton_mm_5539 1.4095 ms 58.4%
SingleProcess AUTOTUNE benchmarking takes 2.1377 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5734 0.8321 ms 100.0%
  mm 0.8323 ms 100.0%
  triton_mm_5731 0.9913 ms 83.9%
  triton_mm_5727 1.0004 ms 83.2%
  triton_mm_5735 1.0662 ms 78.0%
  triton_mm_5732 1.1025 ms 75.5%
  triton_mm_5728 1.1140 ms 74.7%
  triton_mm_5729 1.1312 ms 73.6%
  triton_mm_5724 1.3299 ms 62.6%
  triton_mm_5725 1.4109 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1382 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  triton_mm_4899 0.0363 ms 100.0%
  mm 0.0366 ms 99.0%
  triton_mm_4896 0.0374 ms 96.9%
  triton_mm_4892 0.0377 ms 96.3%
  triton_mm_4895 0.0384 ms 94.4%
  triton_mm_4898 0.0393 ms 92.4%
  triton_mm_4894 0.0411 ms 88.4%
  triton_mm_4887 0.0415 ms 87.5%
  triton_mm_4888 0.0470 ms 77.1%
  triton_mm_4891 0.0503 ms 72.1%
SingleProcess AUTOTUNE benchmarking takes 1.6512 seconds and 0.0010 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4910 0.0348 ms 100.0%
  triton_mm_4914 0.0348 ms 99.9%
  triton_mm_4908 0.0349 ms 99.8%
  triton_mm_4909 0.0350 ms 99.4%
  triton_mm_4911 0.0351 ms 99.0%
  triton_mm_4913 0.0353 ms 98.6%
  triton_mm_4906 0.0360 ms 96.8%
  triton_mm_4907 0.0376 ms 92.6%
  triton_mm_4915 0.0377 ms 92.3%
  triton_mm_4905 0.0380 ms 91.7%
SingleProcess AUTOTUNE benchmarking takes 2.0990 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6343 ms 100.0%
  bias_addmm 0.6387 ms 99.3%
  triton_mm_4932 0.7451 ms 85.1%
  triton_mm_4928 0.7596 ms 83.5%
  addmm 0.7918 ms 80.1%
  triton_mm_4936 0.8368 ms 75.8%
  triton_mm_4933 0.8412 ms 75.4%
  triton_mm_4929 0.8488 ms 74.7%
  triton_mm_4930 0.8716 ms 72.8%
  triton_mm_4925 1.0139 ms 62.6%
SingleProcess AUTOTUNE benchmarking takes 2.2308 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2220 ms 100.0%
  mm 0.2335 ms 95.1%
  triton_mm_4951 0.2540 ms 87.4%
  triton_mm_4947 0.2666 ms 83.3%
  triton_mm_4952 0.2788 ms 79.6%
  triton_mm_4955 0.2879 ms 77.1%
  triton_mm_4948 0.2945 ms 75.4%
  triton_mm_4949 0.3045 ms 72.9%
  triton_mm_4944 0.3397 ms 65.3%
  triton_mm_4945 0.3549 ms 62.5%
SingleProcess AUTOTUNE benchmarking takes 2.0155 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8381 ms 100.0%
  mm 0.8689 ms 96.5%
  triton_mm_5010 0.9963 ms 84.1%
  triton_mm_5006 1.0193 ms 82.2%
  triton_mm_5002 1.0519 ms 79.7%
  triton_mm_5007 1.0686 ms 78.4%
  triton_mm_5003 1.1160 ms 75.1%
  triton_mm_5004 1.1382 ms 73.6%
  triton_mm_4999 1.3475 ms 62.2%
  triton_mm_5000 1.3763 ms 60.9%
SingleProcess AUTOTUNE benchmarking takes 2.1398 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6447 0.0206 ms 100.0%
  triton_mm_6448 0.0223 ms 92.7%
  mm 0.0224 ms 92.1%
  triton_mm_6452 0.0233 ms 88.5%
  triton_mm_6459 0.0249 ms 82.9%
  triton_mm_6446 0.0263 ms 78.6%
  triton_mm_6456 0.0266 ms 77.7%
  triton_mm_6458 0.0283 ms 72.8%
  triton_mm_6455 0.0294 ms 70.2%
  triton_mm_6454 0.0321 ms 64.4%
SingleProcess AUTOTUNE benchmarking takes 1.6387 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5435 ms 100.0%
  bias_addmm 1.5679 ms 98.4%
  triton_mm_6513 1.8604 ms 83.0%
  triton_mm_6509 1.9129 ms 80.7%
  addmm 1.9264 ms 80.1%
  triton_mm_6517 2.0081 ms 76.9%
  triton_mm_6514 2.0920 ms 73.8%
  triton_mm_6510 2.1201 ms 72.8%
  triton_mm_6511 2.1565 ms 71.6%
  triton_mm_6506 2.5403 ms 60.8%
SingleProcess AUTOTUNE benchmarking takes 2.3924 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:22<1:42:15, 142.69s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8172 ms 100.0%
  mm 0.9423 ms 86.7%
  triton_mm_4987 0.9824 ms 83.2%
  triton_mm_4983 0.9932 ms 82.3%
  triton_mm_4991 1.0537 ms 77.6%
  triton_mm_4988 1.0899 ms 75.0%
  triton_mm_4984 1.0917 ms 74.9%
  triton_mm_4985 1.1271 ms 72.5%
  triton_mm_4980 1.3277 ms 61.6%
  triton_mm_4981 1.3829 ms 59.1%
SingleProcess AUTOTUNE benchmarking takes 2.1438 seconds and 0.0013 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8178 ms 100.0%
  mm 0.8348 ms 98.0%
  triton_mm_5080 0.9838 ms 83.1%
  triton_mm_5076 0.9946 ms 82.2%
  triton_mm_5084 1.0576 ms 77.3%
  triton_mm_5081 1.0937 ms 74.8%
  triton_mm_5077 1.1037 ms 74.1%
  triton_mm_5078 1.1311 ms 72.3%
  triton_mm_5073 1.3318 ms 61.4%
  triton_mm_5074 1.4022 ms 58.3%
SingleProcess AUTOTUNE benchmarking takes 2.1414 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5176 0.8186 ms 100.0%
  mm 0.8284 ms 98.8%
  triton_mm_5173 0.9834 ms 83.2%
  triton_mm_5169 0.9950 ms 82.3%
  triton_mm_5177 1.0543 ms 77.6%
  triton_mm_5170 1.1003 ms 74.4%
  triton_mm_5174 1.1007 ms 74.4%
  triton_mm_5171 1.1269 ms 72.6%
  triton_mm_5166 1.3278 ms 61.7%
  triton_mm_5167 1.3854 ms 59.1%
SingleProcess AUTOTUNE benchmarking takes 2.1436 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5269 0.8189 ms 100.0%
  mm 0.8332 ms 98.3%
  triton_mm_5266 0.9844 ms 83.2%
  triton_mm_5262 1.0017 ms 81.7%
  triton_mm_5270 1.0549 ms 77.6%
  triton_mm_5267 1.0919 ms 75.0%
  triton_mm_5263 1.1010 ms 74.4%
  triton_mm_5264 1.1287 ms 72.5%
  triton_mm_5259 1.3318 ms 61.5%
  triton_mm_5260 1.3970 ms 58.6%
SingleProcess AUTOTUNE benchmarking takes 2.1375 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5362 0.8193 ms 100.0%
  mm 0.8297 ms 98.7%
  triton_mm_5359 0.9847 ms 83.2%
  triton_mm_5355 1.0013 ms 81.8%
  triton_mm_5363 1.0540 ms 77.7%
  triton_mm_5360 1.0927 ms 75.0%
  triton_mm_5356 1.1016 ms 74.4%
  triton_mm_5357 1.1287 ms 72.6%
  triton_mm_5352 1.3282 ms 61.7%
  triton_mm_5353 1.3971 ms 58.6%
SingleProcess AUTOTUNE benchmarking takes 2.1359 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_6199 0.8235 ms 100.0%
  mm 0.8288 ms 99.4%
  triton_mm_6196 0.9847 ms 83.6%
  triton_mm_6192 1.0031 ms 82.1%
  triton_mm_6200 1.0541 ms 78.1%
  triton_mm_6193 1.1002 ms 74.9%
  triton_mm_6197 1.1014 ms 74.8%
  triton_mm_6194 1.1316 ms 72.8%
  triton_mm_6189 1.3407 ms 61.4%
  triton_mm_6190 1.3971 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1430 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  triton_mm_4899 0.0368 ms 100.0%
  mm 0.0369 ms 99.7%
  triton_mm_4895 0.0375 ms 98.2%
  triton_mm_4892 0.0379 ms 97.1%
  triton_mm_4896 0.0381 ms 96.4%
  triton_mm_4898 0.0400 ms 91.9%
  triton_mm_4887 0.0410 ms 89.8%
  triton_mm_4894 0.0418 ms 87.9%
  triton_mm_4888 0.0454 ms 81.0%
  triton_mm_4886 0.0515 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 1.6455 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4909 0.0341 ms 100.0%
  triton_mm_4914 0.0349 ms 97.7%
  triton_mm_4910 0.0351 ms 97.1%
  triton_mm_4911 0.0353 ms 96.6%
  triton_mm_4913 0.0353 ms 96.6%
  triton_mm_4906 0.0359 ms 94.9%
  triton_mm_4908 0.0363 ms 94.0%
  triton_mm_4917 0.0378 ms 90.3%
  triton_mm_4915 0.0380 ms 89.9%
  triton_mm_4904 0.0383 ms 89.1%
SingleProcess AUTOTUNE benchmarking takes 2.1025 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_4935 0.6349 ms 100.0%
  bias_addmm 0.6378 ms 99.5%
  triton_mm_4932 0.7455 ms 85.2%
  triton_mm_4928 0.7558 ms 84.0%
  addmm 0.7945 ms 79.9%
  triton_mm_4936 0.8327 ms 76.2%
  triton_mm_4933 0.8332 ms 76.2%
  triton_mm_4929 0.8416 ms 75.4%
  triton_mm_4930 0.8697 ms 73.0%
  triton_mm_4925 1.0020 ms 63.4%
SingleProcess AUTOTUNE benchmarking takes 2.2316 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2232 ms 100.0%
  mm 0.2348 ms 95.1%
  triton_mm_4951 0.2547 ms 87.7%
  triton_mm_4947 0.2665 ms 83.8%
  triton_mm_4952 0.2779 ms 80.3%
  triton_mm_4955 0.2880 ms 77.5%
  triton_mm_4948 0.2934 ms 76.1%
  triton_mm_4949 0.3044 ms 73.3%
  triton_mm_4944 0.3388 ms 65.9%
  triton_mm_4945 0.3531 ms 63.2%
SingleProcess AUTOTUNE benchmarking takes 2.0158 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8337 ms 100.0%
  mm 0.8727 ms 95.5%
  triton_mm_5010 0.9970 ms 83.6%
  triton_mm_5006 1.0074 ms 82.8%
  triton_mm_5002 1.0419 ms 80.0%
  triton_mm_5007 1.0691 ms 78.0%
  triton_mm_5003 1.1147 ms 74.8%
  triton_mm_5004 1.1222 ms 74.3%
  triton_mm_4999 1.3421 ms 62.1%
  triton_mm_5000 1.3585 ms 61.4%
SingleProcess AUTOTUNE benchmarking takes 2.1507 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5939 0.8350 ms 100.0%
  mm 0.8693 ms 96.1%
  triton_mm_5940 0.9964 ms 83.8%
  triton_mm_5936 1.0130 ms 82.4%
  triton_mm_5932 1.0420 ms 80.1%
  triton_mm_5937 1.0691 ms 78.1%
  triton_mm_5933 1.1147 ms 74.9%
  triton_mm_5934 1.1264 ms 74.1%
  triton_mm_5929 1.3428 ms 62.2%
  triton_mm_5930 1.3582 ms 61.5%
SingleProcess AUTOTUNE benchmarking takes 2.1402 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_5958 0.6365 ms 100.0%
  bias_addmm 0.6433 ms 98.9%
  triton_mm_5955 0.7470 ms 85.2%
  triton_mm_5951 0.7575 ms 84.0%
  addmm 0.7977 ms 79.8%
  triton_mm_5959 0.8292 ms 76.8%
  triton_mm_5956 0.8340 ms 76.3%
  triton_mm_5952 0.8432 ms 75.5%
  triton_mm_5953 0.8693 ms 73.2%
  triton_mm_5948 1.0045 ms 63.4%
SingleProcess AUTOTUNE benchmarking takes 2.2331 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_5977 0.2237 ms 100.0%
  mm 0.2349 ms 95.3%
  triton_mm_5974 0.2555 ms 87.6%
  triton_mm_5970 0.2671 ms 83.8%
  triton_mm_5975 0.2787 ms 80.3%
  triton_mm_5978 0.2880 ms 77.7%
  triton_mm_5971 0.2947 ms 75.9%
  triton_mm_5972 0.3044 ms 73.5%
  triton_mm_5967 0.3389 ms 66.0%
  triton_mm_5968 0.3532 ms 63.3%
SingleProcess AUTOTUNE benchmarking takes 2.0159 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0368 ms 100.0%
  triton_mm_5987 0.0373 ms 98.7%
  triton_mm_5990 0.0374 ms 98.5%
  triton_mm_5994 0.0380 ms 97.0%
  triton_mm_5991 0.0382 ms 96.3%
  triton_mm_5993 0.0398 ms 92.5%
  triton_mm_5982 0.0410 ms 89.9%
  triton_mm_5989 0.0417 ms 88.3%
  triton_mm_5983 0.0453 ms 81.2%
  triton_mm_5981 0.0516 ms 71.4%
SingleProcess AUTOTUNE benchmarking takes 1.6582 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6447 0.0212 ms 100.0%
  mm 0.0226 ms 93.9%
  triton_mm_6448 0.0232 ms 91.6%
  triton_mm_6452 0.0245 ms 86.7%
  triton_mm_6446 0.0252 ms 84.0%
  triton_mm_6459 0.0261 ms 81.3%
  triton_mm_6456 0.0274 ms 77.5%
  triton_mm_6458 0.0278 ms 76.4%
  triton_mm_6455 0.0289 ms 73.3%
  triton_mm_6454 0.0323 ms 65.8%
SingleProcess AUTOTUNE benchmarking takes 1.6483 seconds and 0.0011 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5290 ms 100.0%
  bias_addmm 1.5550 ms 98.3%
  triton_mm_6513 1.8578 ms 82.3%
  triton_mm_6509 1.8923 ms 80.8%
  addmm 1.9133 ms 79.9%
  triton_mm_6517 2.0076 ms 76.2%
  triton_mm_6514 2.0949 ms 73.0%
  triton_mm_6510 2.0989 ms 72.8%
  triton_mm_6511 2.1612 ms 70.7%
  triton_mm_6506 2.5381 ms 60.2%
SingleProcess AUTOTUNE benchmarking takes 2.3894 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:22<1:42:16, 142.70s/it]AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_4990 0.8417 ms 100.0%
  mm 0.9393 ms 89.6%
  triton_mm_4987 1.0172 ms 82.7%
  triton_mm_4983 1.0243 ms 82.2%
  triton_mm_4991 1.0776 ms 78.1%
  triton_mm_4988 1.1299 ms 74.5%
  triton_mm_4984 1.1513 ms 73.1%
  triton_mm_4985 1.1578 ms 72.7%
  triton_mm_4980 1.3564 ms 62.1%
  triton_mm_4981 1.4119 ms 59.6%
SingleProcess AUTOTUNE benchmarking takes 2.1495 seconds and 0.0012 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5083 0.8418 ms 100.0%
  mm 0.8503 ms 99.0%
  triton_mm_5080 1.0135 ms 83.1%
  triton_mm_5076 1.0384 ms 81.1%
  triton_mm_5084 1.0806 ms 77.9%
  triton_mm_5081 1.1265 ms 74.7%
  triton_mm_5077 1.1392 ms 73.9%
  triton_mm_5078 1.1556 ms 72.8%
  triton_mm_5073 1.3570 ms 62.0%
  triton_mm_5074 1.4288 ms 58.9%
SingleProcess AUTOTUNE benchmarking takes 2.1444 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.8372 ms 100.0%
  triton_mm_5362 0.8455 ms 99.0%
  triton_mm_5359 1.0145 ms 82.5%
  triton_mm_5355 1.0239 ms 81.8%
  triton_mm_5363 1.0769 ms 77.7%
  triton_mm_5356 1.1260 ms 74.4%
  triton_mm_5360 1.1260 ms 74.4%
  triton_mm_5357 1.1539 ms 72.6%
  triton_mm_5352 1.3567 ms 61.7%
  triton_mm_5353 1.4272 ms 58.7%
SingleProcess AUTOTUNE benchmarking takes 2.1497 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  triton_mm_5455 0.8423 ms 100.0%
  mm 0.8501 ms 99.1%
  triton_mm_5452 1.0145 ms 83.0%
  triton_mm_5448 1.0246 ms 82.2%
  triton_mm_5456 1.0775 ms 78.2%
  triton_mm_5453 1.1172 ms 75.4%
  triton_mm_5449 1.1263 ms 74.8%
  triton_mm_5450 1.1534 ms 73.0%
  triton_mm_5445 1.3567 ms 62.1%
  triton_mm_5446 1.4278 ms 59.0%
SingleProcess AUTOTUNE benchmarking takes 2.1367 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x4352)
  mm 0.8227 ms 100.0%
  triton_mm_5920 0.8426 ms 97.6%
  triton_mm_5917 1.0029 ms 82.0%
  triton_mm_5913 1.0243 ms 80.3%
  triton_mm_5921 1.0847 ms 75.8%
  triton_mm_5918 1.1257 ms 73.1%
  triton_mm_5914 1.1296 ms 72.8%
  triton_mm_5915 1.1523 ms 71.4%
  triton_mm_5910 1.3565 ms 60.6%
  triton_mm_5911 1.4277 ms 57.6%
SingleProcess AUTOTUNE benchmarking takes 2.1434 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0363 ms 100.0%
  triton_mm_4899 0.0369 ms 98.4%
  triton_mm_4895 0.0374 ms 96.9%
  triton_mm_4896 0.0375 ms 96.7%
  triton_mm_4892 0.0380 ms 95.5%
  triton_mm_4898 0.0397 ms 91.2%
  triton_mm_4887 0.0405 ms 89.4%
  triton_mm_4894 0.0406 ms 89.2%
  triton_mm_4888 0.0463 ms 78.3%
  triton_mm_4891 0.0519 ms 69.9%
SingleProcess AUTOTUNE benchmarking takes 1.6438 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10260x24, 24x1088)
  triton_mm_4909 0.0338 ms 100.0%
  triton_mm_4914 0.0347 ms 97.5%
  triton_mm_4908 0.0349 ms 97.0%
  triton_mm_4911 0.0353 ms 95.7%
  triton_mm_4910 0.0359 ms 94.1%
  triton_mm_4913 0.0363 ms 93.2%
  triton_mm_4906 0.0371 ms 91.2%
  triton_mm_4917 0.0376 ms 89.9%
  triton_mm_4915 0.0378 ms 89.5%
  triton_mm_4912 0.0380 ms 89.1%
SingleProcess AUTOTUNE benchmarking takes 2.0978 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  bias_addmm 0.6453 ms 100.0%
  triton_mm_4935 0.6484 ms 99.5%
  triton_mm_4932 0.7512 ms 85.9%
  triton_mm_4928 0.7692 ms 83.9%
  addmm 0.8004 ms 80.6%
  triton_mm_4936 0.8401 ms 76.8%
  triton_mm_4933 0.8520 ms 75.7%
  triton_mm_4929 0.8585 ms 75.2%
  triton_mm_4930 0.8864 ms 72.8%
  triton_mm_4925 1.0230 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.2307 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_4954 0.2243 ms 100.0%
  mm 0.2378 ms 94.3%
  triton_mm_4951 0.2570 ms 87.3%
  triton_mm_4947 0.2673 ms 83.9%
  triton_mm_4952 0.2805 ms 80.0%
  triton_mm_4955 0.2906 ms 77.2%
  triton_mm_4948 0.2965 ms 75.6%
  triton_mm_4949 0.3073 ms 73.0%
  triton_mm_4944 0.3415 ms 65.7%
  triton_mm_4945 0.3554 ms 63.1%
SingleProcess AUTOTUNE benchmarking takes 2.0211 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5009 0.8484 ms 100.0%
  mm 0.8770 ms 96.7%
  triton_mm_5010 1.0075 ms 84.2%
  triton_mm_5006 1.0332 ms 82.1%
  triton_mm_5002 1.0601 ms 80.0%
  triton_mm_5007 1.0809 ms 78.5%
  triton_mm_5003 1.1402 ms 74.4%
  triton_mm_5004 1.1454 ms 74.1%
  triton_mm_4999 1.3572 ms 62.5%
  triton_mm_5000 1.3891 ms 61.1%
SingleProcess AUTOTUNE benchmarking takes 2.1470 seconds and 0.0011 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_5233 0.2244 ms 100.0%
  mm 0.2366 ms 94.8%
  triton_mm_5230 0.2558 ms 87.7%
  triton_mm_5226 0.2683 ms 83.6%
  triton_mm_5231 0.2804 ms 80.0%
  triton_mm_5234 0.2889 ms 77.6%
  triton_mm_5227 0.2979 ms 75.3%
  triton_mm_5228 0.3086 ms 72.7%
  triton_mm_5223 0.3428 ms 65.5%
  triton_mm_5224 0.3558 ms 63.0%
SingleProcess AUTOTUNE benchmarking takes 2.0196 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  mm 0.0368 ms 100.0%
  triton_mm_5246 0.0373 ms 98.5%
  triton_mm_5247 0.0377 ms 97.5%
  triton_mm_5243 0.0378 ms 97.3%
  triton_mm_5250 0.0379 ms 97.0%
  triton_mm_5249 0.0398 ms 92.4%
  triton_mm_5245 0.0406 ms 90.6%
  triton_mm_5238 0.0406 ms 90.5%
  triton_mm_5239 0.0452 ms 81.3%
  triton_mm_5242 0.0509 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 1.6440 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_5288 0.8516 ms 100.0%
  mm 0.8752 ms 97.3%
  triton_mm_5289 1.0120 ms 84.2%
  triton_mm_5285 1.0314 ms 82.6%
  triton_mm_5281 1.0591 ms 80.4%
  triton_mm_5286 1.0942 ms 77.8%
  triton_mm_5283 1.1353 ms 75.0%
  triton_mm_5282 1.1399 ms 74.7%
  triton_mm_5278 1.3570 ms 62.8%
  triton_mm_5279 1.3724 ms 62.1%
SingleProcess AUTOTUNE benchmarking takes 2.1516 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_5307 0.6402 ms 100.0%
  bias_addmm 0.6542 ms 97.9%
  triton_mm_5304 0.7517 ms 85.2%
  triton_mm_5300 0.7597 ms 84.3%
  addmm 0.8083 ms 79.2%
  triton_mm_5308 0.8380 ms 76.4%
  triton_mm_5305 0.8513 ms 75.2%
  triton_mm_5301 0.8594 ms 74.5%
  triton_mm_5302 0.8782 ms 72.9%
  triton_mm_5297 1.0247 ms 62.5%
SingleProcess AUTOTUNE benchmarking takes 2.2497 seconds and 0.0000 seconds precompiling
AUTOTUNE addmm(10296x3264, 10296x1088, 1088x3264)
  triton_mm_6051 0.6405 ms 100.0%
  bias_addmm 0.6450 ms 99.3%
  triton_mm_6048 0.7606 ms 84.2%
  triton_mm_6044 0.7728 ms 82.9%
  addmm 0.8066 ms 79.4%
  triton_mm_6052 0.8391 ms 76.3%
  triton_mm_6049 0.8515 ms 75.2%
  triton_mm_6045 0.8621 ms 74.3%
  triton_mm_6046 0.8797 ms 72.8%
  triton_mm_6041 1.0224 ms 62.6%
SingleProcess AUTOTUNE benchmarking takes 2.2381 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x1088, 1088x1088)
  triton_mm_6070 0.2239 ms 100.0%
  mm 0.2373 ms 94.4%
  triton_mm_6067 0.2556 ms 87.6%
  triton_mm_6063 0.2675 ms 83.7%
  triton_mm_6068 0.2804 ms 79.9%
  triton_mm_6071 0.2900 ms 77.2%
  triton_mm_6064 0.2950 ms 75.9%
  triton_mm_6065 0.3068 ms 73.0%
  triton_mm_6060 0.3426 ms 65.4%
  triton_mm_6061 0.3559 ms 62.9%
SingleProcess AUTOTUNE benchmarking takes 2.0243 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x6528)
  triton_mm_6087 0.0368 ms 100.0%
  mm 0.0370 ms 99.5%
  triton_mm_6083 0.0373 ms 98.5%
  triton_mm_6084 0.0375 ms 98.0%
  triton_mm_6080 0.0377 ms 97.5%
  triton_mm_6086 0.0398 ms 92.4%
  triton_mm_6075 0.0408 ms 90.2%
  triton_mm_6082 0.0415 ms 88.5%
  triton_mm_6076 0.0461 ms 79.7%
  triton_mm_6079 0.0509 ms 72.2%
SingleProcess AUTOTUNE benchmarking takes 1.6496 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(10296x4352, 4352x1088)
  triton_mm_6125 0.8420 ms 100.0%
  mm 0.8757 ms 96.2%
  triton_mm_6126 1.0118 ms 83.2%
  triton_mm_6122 1.0119 ms 83.2%
  triton_mm_6118 1.0491 ms 80.3%
  triton_mm_6123 1.0798 ms 78.0%
  triton_mm_6119 1.1286 ms 74.6%
  triton_mm_6120 1.1468 ms 73.4%
  triton_mm_6115 1.3570 ms 62.1%
  triton_mm_6116 1.3740 ms 61.3%
SingleProcess AUTOTUNE benchmarking takes 2.1569 seconds and 0.0000 seconds precompiling
AUTOTUNE mm(36x1088, 1088x2176)
  triton_mm_6447 0.0211 ms 100.0%
  mm 0.0219 ms 96.2%
  triton_mm_6448 0.0230 ms 91.6%
  triton_mm_6452 0.0235 ms 89.5%
  triton_mm_6446 0.0251 ms 84.0%
  triton_mm_6459 0.0257 ms 82.0%
  triton_mm_6456 0.0260 ms 80.9%
  triton_mm_6458 0.0285 ms 73.8%
  triton_mm_6455 0.0294 ms 71.6%
  triton_mm_6454 0.0319 ms 66.1%
SingleProcess AUTOTUNE benchmarking takes 1.6528 seconds and 0.0010 seconds precompiling
AUTOTUNE addmm(10296x8192, 10296x1088, 1088x8192)
  triton_mm_6516 1.5632 ms 100.0%
  bias_addmm 1.5690 ms 99.6%
  triton_mm_6513 1.8816 ms 83.1%
  triton_mm_6509 1.9193 ms 81.4%
  addmm 1.9252 ms 81.2%
  triton_mm_6517 2.0296 ms 77.0%
  triton_mm_6514 2.1190 ms 73.8%
  triton_mm_6510 2.1213 ms 73.7%
  triton_mm_6511 2.1860 ms 71.5%
  triton_mm_6506 2.5663 ms 60.9%
SingleProcess AUTOTUNE benchmarking takes 2.4017 seconds and 0.0011 seconds precompiling
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   2%|2         | 1/44 [02:22<1:42:20, 142.80s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:25<42:14, 60.34s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:25<42:14, 60.35s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:25<42:14, 60.35s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):
/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   5%|4         | 2/44 [02:25<42:16, 60.39s/it]   /home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:26<22:42, 33.23s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:26<22:42, 33.23s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress:   7%|6         | 3/44 [02:26<22:42, 33.24s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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 12%|#2        | 19/157 [00:02<00:09, 15.24it/s]
 13%|#3        | 21/157 [00:02<00:08, 15.48it/s]
 15%|#4        | 23/157 [00:02<00:08, 16.03it/s]
 16%|#5        | 25/157 [00:02<00:08, 16.44it/s]
 17%|#7        | 27/157 [00:02<00:07, 16.70it/s]
 18%|#8        | 29/157 [00:02<00:07, 16.79it/s]
 20%|#9        | 31/157 [00:02<00:07, 16.86it/s]
 21%|##1       | 33/157 [00:03<00:07, 16.95it/s]
 22%|##2       | 35/157 [00:03<00:07, 17.08it/s]
 24%|##3       | 37/157 [00:03<00:07, 16.40it/s]
 25%|##4       | 39/157 [00:03<00:07, 16.67it/s]
 26%|##6       | 41/157 [00:03<00:06, 16.92it/s]
 27%|##7       | 43/157 [00:03<00:06, 17.10it/s]
 29%|##8       | 45/157 [00:03<00:06, 17.23it/s]
 30%|##9       | 47/157 [00:03<00:06, 17.35it/s]
 31%|###1      | 49/157 [00:04<00:06, 17.30it/s]
 32%|###2      | 51/157 [00:04<00:06, 17.29it/s]
 34%|###3      | 53/157 [00:04<00:06, 17.25it/s]
 35%|###5      | 55/157 [00:04<00:05, 17.30it/s]
 36%|###6      | 57/157 [00:04<00:05, 17.32it/s]
 38%|###7      | 59/157 [00:04<00:05, 17.35it/s]
 39%|###8      | 61/157 [00:04<00:05, 17.40it/s]
 40%|####      | 63/157 [00:04<00:05, 17.40it/s]
 41%|####1     | 65/157 [00:04<00:05, 17.44it/s]
 43%|####2     | 67/157 [00:05<00:05, 17.46it/s]
 44%|####3     | 69/157 [00:05<00:05, 15.87it/s]
 45%|####5     | 71/157 [00:05<00:05, 16.26it/s]
 46%|####6     | 73/157 [00:05<00:05, 16.59it/s]
 48%|####7     | 75/157 [00:05<00:04, 16.88it/s]
 49%|####9     | 77/157 [00:05<00:04, 17.07it/s]
 50%|#####     | 79/157 [00:05<00:04, 17.21it/s]
 52%|#####1    | 81/157 [00:05<00:04, 17.30it/s]
 53%|#####2    | 83/157 [00:05<00:04, 17.35it/s]
 54%|#####4    | 85/157 [00:06<00:04, 17.22it/s]
 55%|#####5    | 87/157 [00:06<00:04, 17.25it/s]
 57%|#####6    | 89/157 [00:06<00:03, 17.26it/s]
 58%|#####7    | 91/157 [00:06<00:03, 17.23it/s]
 59%|#####9    | 93/157 [00:06<00:03, 17.26it/s]
 61%|######    | 95/157 [00:06<00:03, 17.33it/s]
 62%|######1   | 97/157 [00:06<00:03, 17.32it/s]
 63%|######3   | 99/157 [00:06<00:03, 17.34it/s]
 64%|######4   | 101/157 [00:07<00:03, 17.39it/s]
 66%|######5   | 103/157 [00:07<00:03, 17.39it/s]
 67%|######6   | 105/157 [00:07<00:02, 17.36it/s]
 68%|######8   | 107/157 [00:07<00:02, 17.41it/s]
 69%|######9   | 109/157 [00:07<00:02, 17.44it/s]
 71%|#######   | 111/157 [00:07<00:02, 17.26it/s]
 72%|#######1  | 113/157 [00:07<00:02, 17.25it/s]
 73%|#######3  | 115/157 [00:07<00:02, 17.15it/s]
 75%|#######4  | 117/157 [00:07<00:02, 17.03it/s]
 76%|#######5  | 119/157 [00:08<00:02, 16.99it/s]
 77%|#######7  | 121/157 [00:08<00:02, 16.87it/s]
 78%|#######8  | 123/157 [00:08<00:02, 16.94it/s]
 80%|#######9  | 125/157 [00:08<00:01, 16.94it/s]
 81%|########  | 127/157 [00:08<00:01, 17.13it/s]
 82%|########2 | 129/157 [00:08<00:01, 17.17it/s]
 83%|########3 | 131/157 [00:08<00:01, 17.16it/s]
 85%|########4 | 133/157 [00:08<00:01, 14.56it/s]
 86%|########5 | 135/157 [00:09<00:01, 15.27it/s]
 87%|########7 | 137/157 [00:09<00:01, 15.79it/s]
 89%|########8 | 139/157 [00:09<00:01, 16.22it/s]
 90%|########9 | 141/157 [00:09<00:00, 16.55it/s]
 91%|#########1| 143/157 [00:09<00:00, 16.81it/s]
 92%|#########2| 145/157 [00:09<00:00, 16.99it/s]
 94%|#########3| 147/157 [00:09<00:00, 16.94it/s]
 95%|#########4| 149/157 [00:09<00:00, 17.18it/s]
 96%|#########6| 151/157 [00:10<00:00, 17.30it/s]
 97%|#########7| 153/157 [00:10<00:00, 17.34it/s]
 99%|#########8| 155/157 [00:10<00:00, 17.34it/s]
100%|##########| 157/157 [00:11<00:00,  6.07it/s]
100%|##########| 157/157 [00:11<00:00, 14.18it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:45, 17.12it/s]
  1%|          | 4/781 [00:00<00:44, 17.34it/s]
  1%|          | 6/781 [00:00<00:45, 17.19it/s]
  1%|1         | 8/781 [00:00<00:45, 17.14it/s]
  1%|1         | 10/781 [00:00<00:45, 16.79it/s]
  2%|1         | 12/781 [00:00<00:45, 16.73it/s]
  2%|1         | 14/781 [00:00<00:45, 16.72it/s]
  2%|2         | 16/781 [00:00<00:45, 16.66it/s]
  2%|2         | 18/781 [00:01<00:46, 16.53it/s]
  3%|2         | 20/781 [00:01<00:46, 16.31it/s]
  3%|2         | 22/781 [00:01<00:46, 16.37it/s]
  3%|3         | 24/781 [00:01<00:46, 16.45it/s]
  3%|3         | 26/781 [00:01<00:45, 16.51it/s]
  4%|3         | 28/781 [00:01<00:45, 16.39it/s]
  4%|3         | 30/781 [00:01<00:45, 16.47it/s]
  4%|4         | 32/781 [00:01<00:44, 16.67it/s]
  4%|4         | 34/781 [00:02<00:44, 16.67it/s]
  5%|4         | 36/781 [00:02<00:44, 16.60it/s]
  5%|4         | 38/781 [00:02<00:44, 16.61it/s]
  5%|5         | 40/781 [00:02<00:44, 16.74it/s]
  5%|5         | 42/781 [00:02<00:43, 16.82it/s]
  6%|5         | 44/781 [00:02<00:43, 16.77it/s]
  6%|5         | 46/781 [00:02<00:43, 16.74it/s]
  6%|6         | 48/781 [00:02<00:44, 16.55it/s]
  6%|6         | 50/781 [00:03<00:44, 16.42it/s]
  7%|6         | 52/781 [00:03<00:44, 16.45it/s]
  7%|6         | 54/781 [00:03<00:44, 16.47it/s]
  7%|7         | 56/781 [00:03<00:43, 16.59it/s]
  7%|7         | 58/781 [00:03<00:43, 16.45it/s]
  8%|7         | 60/781 [00:03<00:43, 16.61it/s]
  8%|7         | 62/781 [00:03<00:43, 16.47it/s]
  8%|8         | 64/781 [00:03<00:43, 16.50it/s]
  8%|8         | 66/781 [00:03<00:43, 16.51it/s]
  9%|8         | 68/781 [00:04<00:43, 16.56it/s]
  9%|8         | 70/781 [00:04<00:42, 16.71it/s]
  9%|9         | 72/781 [00:04<00:42, 16.78it/s]
  9%|9         | 74/781 [00:04<00:42, 16.82it/s]
 10%|9         | 76/781 [00:04<00:41, 16.89it/s]
 10%|9         | 78/781 [00:04<00:42, 16.70it/s]
 10%|#         | 80/781 [00:04<00:42, 16.55it/s]
 10%|#         | 82/781 [00:04<00:42, 16.59it/s]
 11%|#         | 84/781 [00:05<00:42, 16.49it/s]
 11%|#1        | 86/781 [00:05<00:42, 16.53it/s]
 11%|#1        | 88/781 [00:05<00:41, 16.57it/s]
 12%|#1        | 90/781 [00:05<00:41, 16.71it/s]
 12%|#1        | 92/781 [00:05<00:40, 16.83it/s]
 12%|#2        | 94/781 [00:05<00:40, 16.89it/s]
 12%|#2        | 96/781 [00:05<00:40, 16.81it/s]
 13%|#2        | 98/781 [00:05<00:40, 16.78it/s]
 13%|#2        | 100/781 [00:06<00:40, 16.75it/s]
 13%|#3        | 102/781 [00:06<00:40, 16.61it/s]
 13%|#3        | 104/781 [00:06<00:40, 16.75it/s]
 14%|#3        | 106/781 [00:06<00:40, 16.67it/s]
 14%|#3        | 108/781 [00:06<00:40, 16.53it/s]
 14%|#4        | 110/781 [00:06<00:40, 16.54it/s]
 14%|#4        | 112/781 [00:06<00:40, 16.41it/s]
 15%|#4        | 114/781 [00:06<00:40, 16.32it/s]
 15%|#4        | 116/781 [00:06<00:40, 16.43it/s]
 15%|#5        | 118/781 [00:07<00:40, 16.23it/s]
 15%|#5        | 120/781 [00:07<00:40, 16.44it/s]
 16%|#5        | 122/781 [00:07<00:40, 16.30it/s]
 16%|#5        | 124/781 [00:07<00:40, 16.36it/s]
 16%|#6        | 126/781 [00:07<00:40, 16.33it/s]
 16%|#6        | 128/781 [00:07<00:40, 16.27it/s]
 17%|#6        | 130/781 [00:07<00:40, 16.14it/s]
 17%|#6        | 132/781 [00:07<00:40, 16.15it/s]
 17%|#7        | 134/781 [00:08<00:40, 16.15it/s]
 17%|#7        | 136/781 [00:08<00:39, 16.29it/s]
 18%|#7        | 138/781 [00:08<00:39, 16.12it/s]
 18%|#7        | 140/781 [00:08<00:39, 16.27it/s]
 18%|#8        | 142/781 [00:08<00:39, 16.25it/s]
 18%|#8        | 144/781 [00:08<00:38, 16.38it/s]
 19%|#8        | 146/781 [00:08<00:38, 16.46it/s]
 19%|#8        | 148/781 [00:08<00:38, 16.29it/s]
 19%|#9        | 150/781 [00:09<00:39, 16.18it/s]
 19%|#9        | 152/781 [00:09<00:38, 16.19it/s]
 20%|#9        | 154/781 [00:09<00:38, 16.28it/s]
 20%|#9        | 156/781 [00:09<00:38, 16.30it/s]
 20%|##        | 158/781 [00:09<00:38, 16.30it/s]
 20%|##        | 160/781 [00:09<00:38, 16.29it/s]
 21%|##        | 162/781 [00:09<00:37, 16.30it/s]
 21%|##        | 164/781 [00:09<00:38, 16.16it/s]
 21%|##1       | 166/781 [00:10<00:37, 16.28it/s]
 22%|##1       | 168/781 [00:10<00:37, 16.41it/s]
 22%|##1       | 170/781 [00:10<00:37, 16.34it/s]
 22%|##2       | 172/781 [00:10<00:37, 16.31it/s]
 22%|##2       | 174/781 [00:10<00:36, 16.42it/s]
 23%|##2       | 176/781 [00:10<00:36, 16.49it/s]
 23%|##2       | 178/781 [00:10<00:36, 16.42it/s]
 23%|##3       | 180/781 [00:10<00:36, 16.49it/s]
 23%|##3       | 182/781 [00:11<00:36, 16.43it/s]
 24%|##3       | 184/781 [00:11<00:35, 16.62it/s]
 24%|##3       | 186/781 [00:11<00:35, 16.61it/s]
 24%|##4       | 188/781 [00:11<00:35, 16.49it/s]
 24%|##4       | 190/781 [00:11<00:36, 16.39it/s]
 25%|##4       | 192/781 [00:11<00:35, 16.44it/s]
 25%|##4       | 194/781 [00:11<00:35, 16.50it/s]
 25%|##5       | 196/781 [00:11<00:35, 16.41it/s]
 25%|##5       | 198/781 [00:11<00:35, 16.47it/s]
 26%|##5       | 200/781 [00:12<00:34, 16.65it/s]
 26%|##5       | 202/781 [00:12<00:34, 16.54it/s]
 26%|##6       | 204/781 [00:12<00:35, 16.46it/s]
 26%|##6       | 206/781 [00:12<00:35, 16.43it/s]
 27%|##6       | 208/781 [00:12<00:35, 16.37it/s]
 27%|##6       | 210/781 [00:12<00:34, 16.35it/s]
 27%|##7       | 212/781 [00:12<00:34, 16.33it/s]
 27%|##7       | 214/781 [00:12<00:34, 16.44it/s]
 28%|##7       | 216/781 [00:13<00:34, 16.51it/s]
 28%|##7       | 218/781 [00:13<00:34, 16.43it/s]
 28%|##8       | 220/781 [00:13<00:34, 16.28it/s]
 28%|##8       | 222/781 [00:13<00:34, 16.34it/s]
 29%|##8       | 224/781 [00:13<00:33, 16.41it/s]
 29%|##8       | 226/781 [00:13<00:33, 16.47it/s]
 29%|##9       | 228/781 [00:13<00:33, 16.48it/s]
 29%|##9       | 230/781 [00:13<00:33, 16.53it/s]
 30%|##9       | 232/781 [00:14<00:33, 16.32it/s]
 30%|##9       | 234/781 [00:14<00:33, 16.27it/s]
 30%|###       | 236/781 [00:14<00:33, 16.21it/s]
 30%|###       | 238/781 [00:14<00:33, 16.32it/s]
 31%|###       | 240/781 [00:14<00:32, 16.51it/s]
 31%|###       | 242/781 [00:14<00:32, 16.35it/s]
 31%|###1      | 244/781 [00:14<00:32, 16.56it/s]
 31%|###1      | 246/781 [00:14<00:32, 16.55it/s]
 32%|###1      | 248/781 [00:15<00:32, 16.43it/s]
 32%|###2      | 250/781 [00:15<00:32, 16.38it/s]
 32%|###2      | 252/781 [00:15<00:32, 16.35it/s]
 33%|###2      | 254/781 [00:15<00:32, 16.43it/s]
 33%|###2      | 256/781 [00:15<00:31, 16.52it/s]
 33%|###3      | 258/781 [00:15<00:31, 16.44it/s]
 33%|###3      | 260/781 [00:15<00:31, 16.50it/s]
 34%|###3      | 262/781 [00:16<00:41, 12.43it/s]
 34%|###3      | 264/781 [00:16<00:38, 13.53it/s]
 34%|###4      | 266/781 [00:16<00:35, 14.32it/s]
 34%|###4      | 268/781 [00:16<00:34, 14.95it/s]
 35%|###4      | 270/781 [00:16<00:33, 15.26it/s]
 35%|###4      | 272/781 [00:16<00:32, 15.71it/s]
 35%|###5      | 274/781 [00:16<00:31, 15.87it/s]
 35%|###5      | 276/781 [00:16<00:31, 16.05it/s]
 36%|###5      | 278/781 [00:16<00:30, 16.28it/s]
 36%|###5      | 280/781 [00:17<00:30, 16.39it/s]
 36%|###6      | 282/781 [00:17<00:30, 16.54it/s]
 36%|###6      | 284/781 [00:17<00:30, 16.48it/s]
 37%|###6      | 286/781 [00:17<00:30, 16.36it/s]
 37%|###6      | 288/781 [00:17<00:30, 16.38it/s]
 37%|###7      | 290/781 [00:17<00:29, 16.41it/s]
 37%|###7      | 292/781 [00:17<00:29, 16.41it/s]
 38%|###7      | 294/781 [00:17<00:30, 16.20it/s]
 38%|###7      | 296/781 [00:18<00:29, 16.32it/s]
 38%|###8      | 298/781 [00:18<00:29, 16.53it/s]
 38%|###8      | 300/781 [00:18<00:29, 16.57it/s]
 39%|###8      | 302/781 [00:18<00:28, 16.59it/s]
 39%|###8      | 304/781 [00:18<00:28, 16.62it/s]
 39%|###9      | 306/781 [00:18<00:28, 16.74it/s]
 39%|###9      | 308/781 [00:18<00:28, 16.62it/s]
 40%|###9      | 310/781 [00:18<00:28, 16.62it/s]
 40%|###9      | 312/781 [00:19<00:27, 16.75it/s]
 40%|####      | 314/781 [00:19<00:28, 16.60it/s]
 40%|####      | 316/781 [00:19<00:27, 16.74it/s]
 41%|####      | 318/781 [00:19<00:27, 16.74it/s]
 41%|####      | 320/781 [00:19<00:27, 16.82it/s]
 41%|####1     | 322/781 [00:19<00:27, 16.77it/s]
 41%|####1     | 324/781 [00:19<00:27, 16.77it/s]
 42%|####1     | 326/781 [00:19<00:27, 16.75it/s]
 42%|####1     | 328/781 [00:20<00:27, 16.62it/s]
 42%|####2     | 330/781 [00:20<00:27, 16.55it/s]
 43%|####2     | 332/781 [00:20<00:26, 16.69it/s]
 43%|####2     | 334/781 [00:20<00:26, 16.80it/s]
 43%|####3     | 336/781 [00:20<00:26, 16.90it/s]
 43%|####3     | 338/781 [00:20<00:26, 16.71it/s]
 44%|####3     | 340/781 [00:20<00:26, 16.71it/s]
 44%|####3     | 342/781 [00:20<00:26, 16.58it/s]
 44%|####4     | 344/781 [00:20<00:26, 16.51it/s]
 44%|####4     | 346/781 [00:21<00:26, 16.59it/s]
 45%|####4     | 348/781 [00:21<00:26, 16.61it/s]
 45%|####4     | 350/781 [00:21<00:25, 16.77it/s]
 45%|####5     | 352/781 [00:21<00:25, 16.63it/s]
 45%|####5     | 354/781 [00:21<00:25, 16.75it/s]
 46%|####5     | 356/781 [00:21<00:25, 16.61it/s]
 46%|####5     | 358/781 [00:21<00:25, 16.61it/s]
 46%|####6     | 360/781 [00:21<00:25, 16.41it/s]
 46%|####6     | 362/781 [00:22<00:25, 16.48it/s]
 47%|####6     | 364/781 [00:22<00:25, 16.60it/s]
 47%|####6     | 366/781 [00:22<00:24, 16.62it/s]
 47%|####7     | 368/781 [00:22<00:24, 16.64it/s]
 47%|####7     | 370/781 [00:22<00:24, 16.55it/s]
 48%|####7     | 372/781 [00:22<00:24, 16.50it/s]
 48%|####7     | 374/781 [00:22<00:24, 16.58it/s]
 48%|####8     | 376/781 [00:22<00:24, 16.61it/s]
 48%|####8     | 378/781 [00:23<00:24, 16.42it/s]
 49%|####8     | 380/781 [00:23<00:24, 16.51it/s]
 49%|####8     | 382/781 [00:23<00:24, 16.44it/s]
 49%|####9     | 384/781 [00:23<00:24, 16.47it/s]
 49%|####9     | 386/781 [00:23<00:24, 16.39it/s]
 50%|####9     | 388/781 [00:23<00:23, 16.43it/s]
 50%|####9     | 390/781 [00:23<00:23, 16.46it/s]
 50%|#####     | 392/781 [00:23<00:23, 16.51it/s]
 50%|#####     | 394/781 [00:23<00:23, 16.56it/s]
 51%|#####     | 396/781 [00:24<00:23, 16.68it/s]
 51%|#####     | 398/781 [00:24<00:22, 16.74it/s]
 51%|#####1    | 400/781 [00:24<00:22, 16.70it/s]
 51%|#####1    | 402/781 [00:24<00:22, 16.78it/s]
 52%|#####1    | 404/781 [00:24<00:22, 16.56it/s]
 52%|#####1    | 406/781 [00:24<00:22, 16.66it/s]
 52%|#####2    | 408/781 [00:24<00:22, 16.80it/s]
 52%|#####2    | 410/781 [00:24<00:22, 16.83it/s]
 53%|#####2    | 412/781 [00:25<00:21, 16.87it/s]
 53%|#####3    | 414/781 [00:25<00:21, 16.93it/s]
 53%|#####3    | 416/781 [00:25<00:21, 16.98it/s]
 54%|#####3    | 418/781 [00:25<00:21, 17.02it/s]
 54%|#####3    | 420/781 [00:25<00:21, 16.91it/s]
 54%|#####4    | 422/781 [00:25<00:21, 16.95it/s]
 54%|#####4    | 424/781 [00:25<00:21, 16.86it/s]
 55%|#####4    | 426/781 [00:25<00:21, 16.79it/s]
 55%|#####4    | 428/781 [00:26<00:21, 16.80it/s]
 55%|#####5    | 430/781 [00:26<00:21, 16.63it/s]
 55%|#####5    | 432/781 [00:26<00:20, 16.78it/s]
 56%|#####5    | 434/781 [00:26<00:20, 16.74it/s]
 56%|#####5    | 436/781 [00:26<00:20, 16.62it/s]
 56%|#####6    | 438/781 [00:26<00:20, 16.73it/s]
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100%|#########9| 780/781 [00:47<00:00, 16.54it/s]
100%|##########| 781/781 [00:47<00:00, 16.34it/s]




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Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress: 100%|##########| 44/44 [00:50<00:00,  1.48s/it]
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  with torch.cuda.amp.autocast(enabled=False):

Validation Progress: 100%|##########| 44/44 [00:50<00:00,  1.48s/it]
Validation Progress: 100%|##########| 44/44 [00:50<00:00,  1.14s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

Validation Progress: 100%|##########| 44/44 [00:50<00:00,  1.48s/it]
Validation Progress: 100%|##########| 44/44 [00:50<00:00,  1.14s/it]/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:273: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

/home/user/VAR/tokenizer/tokenizer_image/dino_enc/dinov2.py:122: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
  with torch.cuda.amp.autocast(enabled=False):

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 11%|#1        | 88/781 [00:04<00:36, 18.95it/s]
 12%|#1        | 90/781 [00:04<00:36, 18.73it/s]
 12%|#1        | 92/781 [00:04<00:36, 18.75it/s]
 12%|#2        | 94/781 [00:04<00:36, 18.89it/s]
 12%|#2        | 96/781 [00:05<00:36, 18.73it/s]
 13%|#2        | 98/781 [00:05<00:36, 18.72it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.05it/s]
 13%|#3        | 102/781 [00:05<00:35, 19.01it/s]
 13%|#3        | 104/781 [00:05<00:35, 19.04it/s]
 14%|#3        | 106/781 [00:05<00:35, 19.05it/s]
 14%|#3        | 108/781 [00:05<00:34, 19.27it/s]
 14%|#4        | 110/781 [00:05<00:34, 19.31it/s]
 14%|#4        | 112/781 [00:05<00:34, 19.15it/s]
 15%|#4        | 114/781 [00:05<00:34, 19.16it/s]
 15%|#4        | 116/781 [00:06<00:34, 19.38it/s]
 15%|#5        | 118/781 [00:06<00:34, 19.38it/s]
 15%|#5        | 120/781 [00:06<00:34, 19.37it/s]
 16%|#5        | 122/781 [00:06<00:34, 19.19it/s]
 16%|#5        | 124/781 [00:06<00:34, 19.28it/s]
 16%|#6        | 126/781 [00:06<00:34, 18.96it/s]
 16%|#6        | 128/781 [00:06<00:34, 18.85it/s]
 17%|#6        | 130/781 [00:06<00:34, 18.86it/s]
 17%|#6        | 132/781 [00:06<00:34, 19.07it/s]
 17%|#7        | 134/781 [00:07<00:34, 19.02it/s]
 17%|#7        | 136/781 [00:07<00:33, 19.22it/s]
 18%|#7        | 138/781 [00:07<00:33, 19.11it/s]
 18%|#7        | 140/781 [00:07<00:34, 18.78it/s]
 18%|#8        | 142/781 [00:07<00:33, 18.92it/s]
 18%|#8        | 144/781 [00:07<00:33, 19.01it/s]
 19%|#8        | 146/781 [00:07<00:33, 19.15it/s]
 19%|#8        | 148/781 [00:07<00:32, 19.22it/s]
 19%|#9        | 150/781 [00:07<00:32, 19.20it/s]
 19%|#9        | 152/781 [00:07<00:32, 19.09it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.96it/s]
 20%|#9        | 156/781 [00:08<00:32, 19.05it/s]
 20%|##        | 158/781 [00:08<00:32, 18.90it/s]
 20%|##        | 160/781 [00:08<00:32, 18.84it/s]
 21%|##        | 162/781 [00:08<00:32, 19.13it/s]
 21%|##        | 164/781 [00:08<00:32, 19.16it/s]
 21%|##1       | 166/781 [00:08<00:32, 19.19it/s]
 22%|##1       | 168/781 [00:08<00:32, 19.06it/s]
 22%|##1       | 170/781 [00:08<00:31, 19.19it/s]
 22%|##2       | 172/781 [00:09<00:31, 19.22it/s]
 22%|##2       | 174/781 [00:09<00:31, 19.27it/s]
 23%|##2       | 176/781 [00:09<00:31, 19.10it/s]
 23%|##2       | 178/781 [00:09<00:31, 19.31it/s]
 23%|##3       | 180/781 [00:09<00:31, 19.28it/s]
 23%|##3       | 182/781 [00:09<00:31, 19.13it/s]
 24%|##3       | 184/781 [00:09<00:31, 19.18it/s]
 24%|##3       | 186/781 [00:09<00:30, 19.37it/s]
 24%|##4       | 188/781 [00:09<00:30, 19.39it/s]
 24%|##4       | 190/781 [00:09<00:30, 19.21it/s]
 25%|##4       | 192/781 [00:10<00:30, 19.38it/s]
 25%|##4       | 194/781 [00:10<00:30, 19.15it/s]
 25%|##5       | 196/781 [00:10<00:30, 19.37it/s]
 25%|##5       | 198/781 [00:10<00:30, 19.13it/s]
 26%|##5       | 200/781 [00:10<00:30, 19.15it/s]
 26%|##5       | 202/781 [00:10<00:29, 19.31it/s]
 26%|##6       | 204/781 [00:10<00:29, 19.31it/s]
 26%|##6       | 206/781 [00:10<00:29, 19.24it/s]
 27%|##6       | 208/781 [00:10<00:29, 19.25it/s]
 27%|##6       | 210/781 [00:10<00:29, 19.09it/s]
 27%|##7       | 212/781 [00:11<00:29, 19.33it/s]
 27%|##7       | 214/781 [00:11<00:29, 19.31it/s]
 28%|##7       | 216/781 [00:11<00:29, 19.11it/s]
 28%|##7       | 218/781 [00:11<00:29, 19.11it/s]
 28%|##8       | 220/781 [00:11<00:29, 18.84it/s]
 28%|##8       | 222/781 [00:11<00:29, 18.96it/s]
 29%|##8       | 224/781 [00:11<00:29, 18.75it/s]
 29%|##8       | 226/781 [00:11<00:29, 18.94it/s]
 29%|##9       | 228/781 [00:11<00:29, 18.91it/s]
 29%|##9       | 230/781 [00:12<00:29, 18.86it/s]
 30%|##9       | 232/781 [00:12<00:28, 19.15it/s]
 30%|##9       | 234/781 [00:12<00:28, 19.20it/s]
 30%|###       | 236/781 [00:12<00:28, 19.05it/s]
 30%|###       | 238/781 [00:12<00:28, 19.11it/s]
 31%|###       | 240/781 [00:12<00:27, 19.36it/s]
 31%|###       | 242/781 [00:12<00:27, 19.35it/s]
 31%|###1      | 244/781 [00:12<00:27, 19.35it/s]
 31%|###1      | 246/781 [00:12<00:27, 19.35it/s]
 32%|###1      | 248/781 [00:12<00:27, 19.37it/s]
 32%|###2      | 250/781 [00:13<00:27, 19.38it/s]
 32%|###2      | 252/781 [00:13<00:27, 19.23it/s]
 33%|###2      | 254/781 [00:13<00:27, 19.13it/s]
 33%|###2      | 256/781 [00:13<00:27, 19.12it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.01it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.21it/s]
 34%|###3      | 262/781 [00:13<00:27, 19.21it/s]
 34%|###3      | 264/781 [00:13<00:26, 19.24it/s]
 34%|###4      | 266/781 [00:13<00:26, 19.27it/s]
 34%|###4      | 268/781 [00:14<00:26, 19.13it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.18it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.36it/s]
 35%|###5      | 274/781 [00:14<00:26, 19.13it/s]
 35%|###5      | 276/781 [00:14<00:26, 19.17it/s]
 36%|###5      | 278/781 [00:14<00:26, 18.86it/s]
 36%|###5      | 280/781 [00:14<00:26, 18.96it/s]
 36%|###6      | 282/781 [00:14<00:26, 18.86it/s]
 36%|###6      | 284/781 [00:14<00:26, 18.72it/s]
 37%|###6      | 286/781 [00:14<00:26, 18.86it/s]
 37%|###6      | 288/781 [00:15<00:25, 19.16it/s]
 37%|###7      | 290/781 [00:15<00:25, 19.22it/s]
 37%|###7      | 292/781 [00:15<00:25, 19.26it/s]
 38%|###7      | 294/781 [00:15<00:25, 19.28it/s]
 38%|###7      | 296/781 [00:15<00:25, 19.31it/s]
 38%|###8      | 298/781 [00:15<00:25, 19.26it/s]
 38%|###8      | 300/781 [00:15<00:24, 19.26it/s]
 39%|###8      | 302/781 [00:15<00:24, 19.24it/s]
 39%|###8      | 304/781 [00:15<00:24, 19.26it/s]
 39%|###9      | 306/781 [00:16<00:24, 19.25it/s]
 39%|###9      | 308/781 [00:16<00:24, 19.28it/s]
 40%|###9      | 310/781 [00:16<00:24, 19.11it/s]
 40%|###9      | 312/781 [00:16<00:24, 19.29it/s]
 40%|####      | 314/781 [00:16<00:24, 19.34it/s]
 40%|####      | 316/781 [00:16<00:23, 19.40it/s]
 41%|####      | 318/781 [00:16<00:23, 19.38it/s]
 41%|####      | 320/781 [00:16<00:23, 19.36it/s]
 41%|####1     | 322/781 [00:16<00:23, 19.18it/s]
 41%|####1     | 324/781 [00:16<00:23, 19.06it/s]
 42%|####1     | 326/781 [00:17<00:23, 18.97it/s]
 42%|####1     | 328/781 [00:17<00:23, 18.92it/s]
 42%|####2     | 330/781 [00:17<00:23, 19.01it/s]
 43%|####2     | 332/781 [00:17<00:23, 18.95it/s]
 43%|####2     | 334/781 [00:17<00:23, 18.91it/s]
 43%|####3     | 336/781 [00:17<00:23, 18.93it/s]
 43%|####3     | 338/781 [00:17<00:23, 18.98it/s]
 44%|####3     | 340/781 [00:17<00:23, 18.76it/s]
 44%|####3     | 342/781 [00:17<00:23, 19.00it/s]
 44%|####4     | 344/781 [00:18<00:23, 18.82it/s]
 44%|####4     | 346/781 [00:18<00:22, 19.10it/s]
 45%|####4     | 348/781 [00:18<00:23, 18.77it/s]
 45%|####4     | 350/781 [00:18<00:22, 18.91it/s]
 45%|####5     | 352/781 [00:18<00:22, 18.70it/s]
 45%|####5     | 354/781 [00:18<00:22, 18.85it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.63it/s]
 46%|####5     | 358/781 [00:18<00:22, 18.66it/s]
 46%|####6     | 360/781 [00:18<00:22, 18.84it/s]
 46%|####6     | 362/781 [00:18<00:21, 19.17it/s]
 47%|####6     | 364/781 [00:19<00:21, 19.09it/s]
 47%|####6     | 366/781 [00:19<00:21, 18.98it/s]
 47%|####7     | 368/781 [00:19<00:21, 19.20it/s]
 47%|####7     | 370/781 [00:19<00:21, 19.24it/s]
 48%|####7     | 372/781 [00:19<00:21, 19.07it/s]
 48%|####7     | 374/781 [00:19<00:21, 19.04it/s]
 48%|####8     | 376/781 [00:19<00:21, 19.06it/s]
 48%|####8     | 378/781 [00:19<00:21, 19.15it/s]
 49%|####8     | 380/781 [00:19<00:20, 19.33it/s]
 49%|####8     | 382/781 [00:19<00:20, 19.29it/s]
 49%|####9     | 384/781 [00:20<00:20, 19.11it/s]
 49%|####9     | 386/781 [00:20<00:20, 19.35it/s]
 50%|####9     | 388/781 [00:20<00:20, 19.20it/s]
 50%|####9     | 390/781 [00:20<00:20, 19.33it/s]
 50%|#####     | 392/781 [00:20<00:20, 19.18it/s]
 50%|#####     | 394/781 [00:20<00:20, 19.19it/s]
 51%|#####     | 396/781 [00:20<00:19, 19.35it/s]
 51%|#####     | 398/781 [00:20<00:19, 19.16it/s]
 51%|#####1    | 400/781 [00:20<00:19, 19.21it/s]
 51%|#####1    | 402/781 [00:21<00:19, 19.18it/s]
 52%|#####1    | 404/781 [00:21<00:19, 19.03it/s]
 52%|#####1    | 406/781 [00:21<00:19, 18.93it/s]
 52%|#####2    | 408/781 [00:21<00:19, 18.89it/s]
 52%|#####2    | 410/781 [00:21<00:19, 18.93it/s]
 53%|#####2    | 412/781 [00:21<00:19, 19.06it/s]
 53%|#####3    | 414/781 [00:21<00:19, 19.16it/s]
 53%|#####3    | 416/781 [00:21<00:18, 19.21it/s]
 54%|#####3    | 418/781 [00:21<00:18, 19.28it/s]
 54%|#####3    | 420/781 [00:21<00:18, 19.48it/s]
 54%|#####4    | 422/781 [00:22<00:18, 19.27it/s]
 54%|#####4    | 424/781 [00:22<00:18, 19.29it/s]
 55%|#####4    | 426/781 [00:22<00:18, 19.40it/s]
 55%|#####4    | 428/781 [00:22<00:18, 19.23it/s]
 55%|#####5    | 430/781 [00:22<00:18, 19.26it/s]
 55%|#####5    | 432/781 [00:22<00:18, 19.25it/s]
 56%|#####5    | 434/781 [00:22<00:18, 19.20it/s]
 56%|#####5    | 436/781 [00:22<00:17, 19.23it/s]
 56%|#####6    | 438/781 [00:22<00:17, 19.26it/s]
 56%|#####6    | 440/781 [00:23<00:17, 19.33it/s]
 57%|#####6    | 442/781 [00:23<00:17, 19.31it/s]
 57%|#####6    | 444/781 [00:23<00:17, 19.47it/s]
 57%|#####7    | 446/781 [00:23<00:17, 19.28it/s]
 57%|#####7    | 448/781 [00:23<00:17, 19.32it/s]
 58%|#####7    | 450/781 [00:23<00:16, 19.48it/s]
 58%|#####7    | 452/781 [00:23<00:17, 19.13it/s]
 58%|#####8    | 454/781 [00:23<00:17, 19.06it/s]
 58%|#####8    | 456/781 [00:23<00:17, 19.08it/s]
 59%|#####8    | 458/781 [00:23<00:16, 19.11it/s]
 59%|#####8    | 460/781 [00:24<00:16, 19.19it/s]
 59%|#####9    | 462/781 [00:24<00:16, 19.23it/s]
 59%|#####9    | 464/781 [00:24<00:16, 19.26it/s]
 60%|#####9    | 466/781 [00:24<00:16, 19.24it/s]
 60%|#####9    | 468/781 [00:24<00:16, 19.26it/s]
 60%|######    | 470/781 [00:24<00:16, 19.18it/s]
 60%|######    | 472/781 [00:24<00:16, 19.26it/s]
 61%|######    | 474/781 [00:24<00:15, 19.24it/s]
 61%|######    | 476/781 [00:24<00:15, 19.28it/s]
 61%|######1   | 478/781 [00:24<00:15, 19.29it/s]
 61%|######1   | 480/781 [00:25<00:15, 19.31it/s]
 62%|######1   | 482/781 [00:25<00:15, 19.31it/s]
 62%|######1   | 484/781 [00:25<00:15, 19.33it/s]
 62%|######2   | 486/781 [00:25<00:15, 19.37it/s]
 62%|######2   | 488/781 [00:25<00:15, 19.08it/s]
 63%|######2   | 490/781 [00:25<00:15, 19.14it/s]
 63%|######2   | 492/781 [00:25<00:15, 19.21it/s]
 63%|######3   | 494/781 [00:25<00:14, 19.36it/s]
 64%|######3   | 496/781 [00:25<00:14, 19.21it/s]
 64%|######3   | 498/781 [00:26<00:14, 19.20it/s]
 64%|######4   | 500/781 [00:26<00:14, 19.23it/s]
 64%|######4   | 502/781 [00:26<00:14, 19.28it/s]
 65%|######4   | 504/781 [00:26<00:14, 19.37it/s]
 65%|######4   | 506/781 [00:26<00:14, 19.36it/s]
 65%|######5   | 508/781 [00:26<00:14, 19.43it/s]
 65%|######5   | 510/781 [00:26<00:13, 19.56it/s]
 66%|######5   | 512/781 [00:26<00:13, 19.28it/s]
 66%|######5   | 514/781 [00:26<00:13, 19.22it/s]
 66%|######6   | 516/781 [00:26<00:13, 19.35it/s]
 66%|######6   | 518/781 [00:27<00:13, 18.99it/s]
 67%|######6   | 520/781 [00:27<00:13, 18.93it/s]
 67%|######6   | 522/781 [00:27<00:13, 18.99it/s]
 67%|######7   | 524/781 [00:27<00:13, 18.83it/s]
 67%|######7   | 526/781 [00:27<00:13, 18.98it/s]
 68%|######7   | 528/781 [00:27<00:13, 19.02it/s]
 68%|######7   | 530/781 [00:27<00:13, 19.09it/s]
 68%|######8   | 532/781 [00:27<00:13, 19.05it/s]
 68%|######8   | 534/781 [00:27<00:12, 19.09it/s]
 69%|######8   | 536/781 [00:28<00:12, 19.10it/s]
 69%|######8   | 538/781 [00:28<00:12, 18.86it/s]
 69%|######9   | 540/781 [00:28<00:12, 18.93it/s]
 69%|######9   | 542/781 [00:28<00:12, 18.88it/s]
 70%|######9   | 544/781 [00:28<00:12, 18.98it/s]
 70%|######9   | 546/781 [00:28<00:12, 19.20it/s]
 70%|#######   | 548/781 [00:28<00:12, 18.99it/s]
 70%|#######   | 550/781 [00:28<00:12, 19.04it/s]
 71%|#######   | 552/781 [00:28<00:11, 19.08it/s]
 71%|#######   | 554/781 [00:28<00:11, 19.08it/s]
 71%|#######1  | 556/781 [00:29<00:11, 19.28it/s]
 71%|#######1  | 558/781 [00:29<00:11, 19.27it/s]
 72%|#######1  | 560/781 [00:29<00:11, 19.13it/s]
 72%|#######1  | 562/781 [00:29<00:11, 19.34it/s]
 72%|#######2  | 564/781 [00:29<00:11, 19.32it/s]
 72%|#######2  | 566/781 [00:29<00:11, 19.16it/s]
 73%|#######2  | 568/781 [00:29<00:11, 19.17it/s]
 73%|#######2  | 570/781 [00:29<00:10, 19.34it/s]
 73%|#######3  | 572/781 [00:29<00:10, 19.15it/s]
 73%|#######3  | 574/781 [00:30<00:10, 19.33it/s]
 74%|#######3  | 576/781 [00:30<00:10, 19.31it/s]
 74%|#######4  | 578/781 [00:30<00:10, 19.11it/s]
 74%|#######4  | 580/781 [00:30<00:10, 19.14it/s]
 75%|#######4  | 582/781 [00:30<00:10, 19.34it/s]
 75%|#######4  | 584/781 [00:30<00:10, 19.21it/s]
 75%|#######5  | 586/781 [00:30<00:10, 18.91it/s]
 75%|#######5  | 588/781 [00:30<00:10, 19.02it/s]
 76%|#######5  | 590/781 [00:30<00:10, 18.93it/s]
 76%|#######5  | 592/781 [00:30<00:09, 19.02it/s]
 76%|#######6  | 594/781 [00:31<00:09, 19.27it/s]
 76%|#######6  | 596/781 [00:31<00:09, 19.27it/s]
 77%|#######6  | 598/781 [00:31<00:09, 19.29it/s]
 77%|#######6  | 600/781 [00:31<00:09, 19.29it/s]
 77%|#######7  | 602/781 [00:31<00:09, 19.07it/s]
 77%|#######7  | 604/781 [00:31<00:09, 19.28it/s]
 78%|#######7  | 606/781 [00:31<00:09, 19.30it/s]
 78%|#######7  | 608/781 [00:31<00:09, 19.13it/s]
 78%|#######8  | 610/781 [00:31<00:08, 19.18it/s]
 78%|#######8  | 612/781 [00:31<00:08, 19.07it/s]
 79%|#######8  | 614/781 [00:32<00:08, 19.28it/s]
 79%|#######8  | 616/781 [00:32<00:08, 19.12it/s]
 79%|#######9  | 618/781 [00:32<00:08, 19.18it/s]
 79%|#######9  | 620/781 [00:32<00:08, 19.22it/s]
 80%|#######9  | 622/781 [00:32<00:08, 19.26it/s]
 80%|#######9  | 624/781 [00:32<00:08, 19.46it/s]
 80%|########  | 626/781 [00:32<00:08, 19.25it/s]
 80%|########  | 628/781 [00:32<00:07, 19.30it/s]
 81%|########  | 630/781 [00:32<00:07, 19.30it/s]
 81%|########  | 632/781 [00:33<00:07, 19.46it/s]
 81%|########1 | 634/781 [00:33<00:07, 19.25it/s]
 81%|########1 | 636/781 [00:33<00:07, 19.28it/s]
 82%|########1 | 638/781 [00:33<00:07, 19.47it/s]
 82%|########1 | 640/781 [00:33<00:07, 19.42it/s]
 82%|########2 | 642/781 [00:33<00:07, 19.38it/s]
 82%|########2 | 644/781 [00:33<00:07, 19.36it/s]
 83%|########2 | 646/781 [00:33<00:07, 19.15it/s]
 83%|########2 | 648/781 [00:33<00:06, 19.17it/s]
 83%|########3 | 650/781 [00:33<00:06, 19.21it/s]
 83%|########3 | 652/781 [00:34<00:06, 19.42it/s]
 84%|########3 | 654/781 [00:34<00:06, 19.19it/s]
 84%|########3 | 656/781 [00:34<00:06, 19.24it/s]
 84%|########4 | 658/781 [00:34<00:06, 19.23it/s]
 85%|########4 | 660/781 [00:34<00:06, 19.26it/s]
 85%|########4 | 662/781 [00:34<00:06, 19.26it/s]
 85%|########5 | 664/781 [00:34<00:06, 19.27it/s]
 85%|########5 | 666/781 [00:34<00:05, 19.39it/s]
 86%|########5 | 668/781 [00:34<00:05, 19.21it/s]
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 18%|#7        | 28/157 [00:01<00:08, 16.08it/s]
 19%|#9        | 30/157 [00:01<00:07, 15.98it/s]
 20%|##        | 32/157 [00:02<00:07, 16.10it/s]
 22%|##1       | 34/157 [00:02<00:07, 16.40it/s]
 23%|##2       | 36/157 [00:02<00:07, 16.62it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.45it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.55it/s]
 27%|##6       | 42/157 [00:02<00:06, 16.44it/s]
 28%|##8       | 44/157 [00:02<00:06, 16.20it/s]
 29%|##9       | 46/157 [00:02<00:06, 16.07it/s]
 31%|###       | 48/157 [00:03<00:06, 15.91it/s]
 32%|###1      | 50/157 [00:03<00:06, 15.88it/s]
 33%|###3      | 52/157 [00:03<00:06, 15.91it/s]
 34%|###4      | 54/157 [00:03<00:06, 15.89it/s]
 36%|###5      | 56/157 [00:03<00:06, 16.03it/s]
 37%|###6      | 58/157 [00:03<00:06, 15.95it/s]
 38%|###8      | 60/157 [00:03<00:06, 15.81it/s]
 39%|###9      | 62/157 [00:03<00:05, 16.18it/s]
 41%|####      | 64/157 [00:04<00:05, 16.19it/s]
 42%|####2     | 66/157 [00:04<00:05, 16.11it/s]
 43%|####3     | 68/157 [00:04<00:05, 16.10it/s]
 45%|####4     | 70/157 [00:04<00:05, 16.00it/s]
 46%|####5     | 72/157 [00:04<00:05, 16.16it/s]
 47%|####7     | 74/157 [00:04<00:05, 15.99it/s]
 48%|####8     | 76/157 [00:04<00:05, 16.04it/s]
 50%|####9     | 78/157 [00:04<00:04, 16.05it/s]
 51%|#####     | 80/157 [00:04<00:04, 16.26it/s]
 52%|#####2    | 82/157 [00:05<00:04, 16.11it/s]
 54%|#####3    | 84/157 [00:05<00:04, 15.97it/s]
 55%|#####4    | 86/157 [00:05<00:04, 15.92it/s]
 56%|#####6    | 88/157 [00:05<00:04, 16.23it/s]
 57%|#####7    | 90/157 [00:05<00:04, 16.19it/s]
 59%|#####8    | 92/157 [00:05<00:03, 16.46it/s]
 60%|#####9    | 94/157 [00:05<00:03, 16.54it/s]
 61%|######1   | 96/157 [00:05<00:03, 16.51it/s]
 62%|######2   | 98/157 [00:06<00:03, 16.69it/s]
 64%|######3   | 100/157 [00:06<00:03, 16.54it/s]
 65%|######4   | 102/157 [00:06<00:03, 16.44it/s]
 66%|######6   | 104/157 [00:06<00:03, 16.35it/s]
 68%|######7   | 106/157 [00:06<00:03, 16.60it/s]
 69%|######8   | 108/157 [00:06<00:02, 16.48it/s]
 70%|#######   | 110/157 [00:06<00:02, 16.39it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.28it/s]
 73%|#######2  | 114/157 [00:07<00:02, 16.26it/s]
 74%|#######3  | 116/157 [00:07<00:02, 16.25it/s]
 75%|#######5  | 118/157 [00:07<00:02, 16.42it/s]
 76%|#######6  | 120/157 [00:07<00:02, 16.66it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.97it/s]
 79%|#######8  | 124/157 [00:07<00:01, 16.75it/s]
 80%|########  | 126/157 [00:07<00:01, 17.09it/s]
 82%|########1 | 128/157 [00:07<00:01, 16.94it/s]
 83%|########2 | 130/157 [00:08<00:01, 16.94it/s]
 84%|########4 | 132/157 [00:08<00:01, 16.83it/s]
 85%|########5 | 134/157 [00:08<00:01, 16.63it/s]
 87%|########6 | 136/157 [00:08<00:01, 16.53it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.96it/s]
 89%|########9 | 140/157 [00:08<00:00, 17.27it/s]
 90%|######### | 142/157 [00:08<00:00, 17.22it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.75it/s]
 93%|#########2| 146/157 [00:08<00:00, 16.68it/s]
 94%|#########4| 148/157 [00:09<00:00, 16.75it/s]
 96%|#########5| 150/157 [00:09<00:00, 16.57it/s]
 97%|#########6| 152/157 [00:09<00:00, 16.58it/s]
 98%|#########8| 154/157 [00:09<00:00, 16.62it/s]
 99%|#########9| 156/157 [00:09<00:00, 16.80it/s]
100%|##########| 157/157 [00:09<00:00, 16.35it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:49, 15.85it/s]
  1%|          | 4/781 [00:00<00:45, 17.06it/s]
  1%|          | 6/781 [00:00<00:44, 17.25it/s]
  1%|1         | 8/781 [00:00<00:43, 17.78it/s]
  1%|1         | 11/781 [00:00<00:41, 18.72it/s]
  2%|1         | 13/781 [00:00<00:41, 18.47it/s]
  2%|1         | 15/781 [00:00<00:41, 18.29it/s]
  2%|2         | 17/781 [00:00<00:42, 17.95it/s]
  2%|2         | 19/781 [00:01<00:41, 18.21it/s]
  3%|2         | 21/781 [00:01<00:41, 18.13it/s]
  3%|2         | 23/781 [00:01<00:41, 18.29it/s]
  3%|3         | 25/781 [00:01<00:41, 18.21it/s]
  3%|3         | 27/781 [00:01<00:41, 18.05it/s]
  4%|3         | 29/781 [00:01<00:41, 18.02it/s]
  4%|3         | 31/781 [00:01<00:41, 17.98it/s]
  4%|4         | 33/781 [00:01<00:40, 18.35it/s]
  4%|4         | 35/781 [00:01<00:41, 18.05it/s]
  5%|4         | 37/781 [00:02<00:41, 17.86it/s]
  5%|4         | 39/781 [00:02<00:41, 18.05it/s]
  5%|5         | 41/781 [00:02<00:40, 18.24it/s]
  6%|5         | 43/781 [00:02<00:40, 18.25it/s]
  6%|5         | 45/781 [00:02<00:40, 18.36it/s]
  6%|6         | 47/781 [00:02<00:39, 18.57it/s]
  6%|6         | 49/781 [00:02<00:40, 18.11it/s]
  7%|6         | 51/781 [00:02<00:40, 17.82it/s]
  7%|6         | 53/781 [00:02<00:41, 17.71it/s]
  7%|7         | 55/781 [00:03<00:40, 17.93it/s]
  7%|7         | 57/781 [00:03<00:40, 17.75it/s]
  8%|7         | 59/781 [00:03<00:40, 18.01it/s]
  8%|7         | 61/781 [00:03<00:39, 18.19it/s]
  8%|8         | 63/781 [00:03<00:39, 18.16it/s]
  8%|8         | 65/781 [00:03<00:38, 18.45it/s]
  9%|8         | 67/781 [00:03<00:39, 18.18it/s]
  9%|8         | 69/781 [00:03<00:39, 18.06it/s]
  9%|9         | 71/781 [00:03<00:39, 17.77it/s]
  9%|9         | 73/781 [00:04<00:40, 17.54it/s]
 10%|9         | 75/781 [00:04<00:40, 17.64it/s]
 10%|9         | 77/781 [00:04<00:39, 17.72it/s]
 10%|#         | 79/781 [00:04<00:38, 18.04it/s]
 10%|#         | 81/781 [00:04<00:39, 17.86it/s]
 11%|#         | 83/781 [00:04<00:39, 17.72it/s]
 11%|#         | 85/781 [00:04<00:39, 17.66it/s]
 11%|#1        | 87/781 [00:04<00:38, 18.03it/s]
 11%|#1        | 89/781 [00:04<00:38, 17.99it/s]
 12%|#1        | 91/781 [00:05<00:38, 17.90it/s]
 12%|#1        | 93/781 [00:05<00:38, 18.09it/s]
 12%|#2        | 95/781 [00:05<00:38, 17.90it/s]
 12%|#2        | 97/781 [00:05<00:38, 17.76it/s]
 13%|#2        | 99/781 [00:05<00:38, 17.69it/s]
 13%|#2        | 101/781 [00:05<00:37, 17.97it/s]
 13%|#3        | 103/781 [00:05<00:37, 17.85it/s]
 13%|#3        | 105/781 [00:05<00:37, 18.13it/s]
 14%|#3        | 107/781 [00:05<00:36, 18.40it/s]
 14%|#3        | 109/781 [00:06<00:36, 18.24it/s]
 14%|#4        | 111/781 [00:06<00:36, 18.17it/s]
 14%|#4        | 113/781 [00:06<00:36, 18.10it/s]
 15%|#4        | 115/781 [00:06<00:37, 18.00it/s]
 15%|#4        | 117/781 [00:06<00:37, 17.81it/s]
 15%|#5        | 119/781 [00:06<00:37, 17.68it/s]
 15%|#5        | 121/781 [00:06<00:36, 18.20it/s]
 16%|#5        | 123/781 [00:06<00:35, 18.45it/s]
 16%|#6        | 125/781 [00:06<00:34, 18.79it/s]
 16%|#6        | 127/781 [00:07<00:35, 18.52it/s]
 17%|#6        | 129/781 [00:07<00:35, 18.29it/s]
 17%|#6        | 131/781 [00:07<00:35, 18.54it/s]
 17%|#7        | 133/781 [00:07<00:35, 18.33it/s]
 17%|#7        | 135/781 [00:07<00:35, 18.17it/s]
 18%|#7        | 137/781 [00:07<00:35, 18.08it/s]
 18%|#7        | 139/781 [00:07<00:35, 18.00it/s]
 18%|#8        | 142/781 [00:07<00:34, 18.61it/s]
 18%|#8        | 144/781 [00:07<00:34, 18.40it/s]
 19%|#8        | 146/781 [00:08<00:34, 18.64it/s]
 19%|#8        | 148/781 [00:08<00:34, 18.42it/s]
 19%|#9        | 150/781 [00:08<00:34, 18.21it/s]
 19%|#9        | 152/781 [00:08<00:34, 18.29it/s]
 20%|#9        | 154/781 [00:08<00:34, 18.28it/s]
 20%|#9        | 156/781 [00:08<00:34, 18.16it/s]
 20%|##        | 158/781 [00:08<00:34, 18.11it/s]
 20%|##        | 160/781 [00:08<00:34, 18.06it/s]
 21%|##        | 162/781 [00:08<00:34, 18.03it/s]
 21%|##        | 164/781 [00:09<00:34, 17.91it/s]
 21%|##1       | 166/781 [00:09<00:33, 18.25it/s]
 22%|##1       | 168/781 [00:09<00:33, 18.53it/s]
 22%|##1       | 170/781 [00:09<00:33, 18.33it/s]
 22%|##2       | 172/781 [00:09<00:33, 18.19it/s]
 22%|##2       | 174/781 [00:09<00:33, 18.10it/s]
 23%|##2       | 176/781 [00:09<00:33, 18.28it/s]
 23%|##2       | 178/781 [00:09<00:32, 18.57it/s]
 23%|##3       | 180/781 [00:09<00:32, 18.75it/s]
 23%|##3       | 183/781 [00:10<00:30, 19.44it/s]
 24%|##3       | 185/781 [00:10<00:30, 19.42it/s]
 24%|##3       | 187/781 [00:10<00:30, 19.38it/s]
 24%|##4       | 189/781 [00:10<00:31, 19.01it/s]
 24%|##4       | 191/781 [00:10<00:31, 18.50it/s]
 25%|##4       | 193/781 [00:10<00:32, 18.29it/s]
 25%|##4       | 195/781 [00:10<00:32, 18.17it/s]
 25%|##5       | 197/781 [00:10<00:32, 18.07it/s]
 25%|##5       | 199/781 [00:10<00:32, 18.06it/s]
 26%|##5       | 201/781 [00:11<00:31, 18.13it/s]
 26%|##5       | 203/781 [00:11<00:31, 18.27it/s]
 26%|##6       | 205/781 [00:11<00:31, 18.25it/s]
 27%|##6       | 207/781 [00:11<00:31, 18.18it/s]
 27%|##6       | 209/781 [00:11<00:31, 18.07it/s]
 27%|##7       | 211/781 [00:11<00:31, 18.01it/s]
 27%|##7       | 213/781 [00:11<00:30, 18.32it/s]
 28%|##7       | 215/781 [00:11<00:31, 18.22it/s]
 28%|##7       | 217/781 [00:11<00:31, 18.14it/s]
 28%|##8       | 219/781 [00:12<00:31, 18.08it/s]
 28%|##8       | 221/781 [00:12<00:31, 18.05it/s]
 29%|##8       | 223/781 [00:12<00:30, 18.27it/s]
 29%|##8       | 225/781 [00:12<00:29, 18.54it/s]
 29%|##9       | 227/781 [00:12<00:29, 18.89it/s]
 29%|##9       | 230/781 [00:12<00:28, 19.43it/s]
 30%|##9       | 232/781 [00:12<00:28, 19.23it/s]
 30%|##9       | 234/781 [00:12<00:29, 18.81it/s]
 30%|###       | 236/781 [00:12<00:29, 18.37it/s]
 30%|###       | 238/781 [00:13<00:29, 18.31it/s]
 31%|###       | 241/781 [00:13<00:28, 18.76it/s]
 31%|###1      | 243/781 [00:13<00:29, 18.38it/s]
 31%|###1      | 245/781 [00:13<00:29, 18.45it/s]
 32%|###1      | 247/781 [00:13<00:29, 18.20it/s]
 32%|###1      | 249/781 [00:13<00:29, 18.07it/s]
 32%|###2      | 251/781 [00:13<00:29, 17.98it/s]
 32%|###2      | 253/781 [00:13<00:29, 17.94it/s]
 33%|###2      | 255/781 [00:14<00:29, 18.13it/s]
 33%|###2      | 257/781 [00:14<00:28, 18.32it/s]
 33%|###3      | 259/781 [00:14<00:29, 17.95it/s]
 33%|###3      | 261/781 [00:14<00:29, 17.70it/s]
 34%|###3      | 263/781 [00:14<00:29, 17.57it/s]
 34%|###3      | 265/781 [00:14<00:29, 17.40it/s]
 34%|###4      | 267/781 [00:14<00:29, 17.72it/s]
 34%|###4      | 269/781 [00:14<00:28, 17.87it/s]
 35%|###4      | 271/781 [00:14<00:28, 18.11it/s]
 35%|###4      | 273/781 [00:15<00:27, 18.25it/s]
 35%|###5      | 275/781 [00:15<00:27, 18.13it/s]
 35%|###5      | 277/781 [00:15<00:28, 17.92it/s]
 36%|###5      | 279/781 [00:15<00:28, 17.89it/s]
 36%|###5      | 281/781 [00:15<00:28, 17.84it/s]
 36%|###6      | 283/781 [00:15<00:27, 18.06it/s]
 36%|###6      | 285/781 [00:15<00:27, 18.08it/s]
 37%|###6      | 287/781 [00:15<00:27, 17.96it/s]
 37%|###7      | 289/781 [00:15<00:27, 17.93it/s]
 37%|###7      | 291/781 [00:16<00:26, 18.16it/s]
 38%|###7      | 293/781 [00:16<00:27, 17.91it/s]
 38%|###7      | 295/781 [00:16<00:27, 17.75it/s]
 38%|###8      | 297/781 [00:16<00:27, 17.68it/s]
 38%|###8      | 299/781 [00:16<00:26, 17.94it/s]
 39%|###8      | 301/781 [00:16<00:26, 18.25it/s]
 39%|###8      | 303/781 [00:16<00:26, 18.13it/s]
 39%|###9      | 305/781 [00:16<00:25, 18.39it/s]
 39%|###9      | 307/781 [00:16<00:26, 18.13it/s]
 40%|###9      | 309/781 [00:17<00:26, 17.88it/s]
 40%|###9      | 311/781 [00:17<00:26, 17.70it/s]
 40%|####      | 313/781 [00:17<00:26, 17.93it/s]
 40%|####      | 315/781 [00:17<00:26, 17.78it/s]
 41%|####      | 317/781 [00:17<00:26, 17.68it/s]
 41%|####      | 319/781 [00:17<00:26, 17.71it/s]
 41%|####1     | 321/781 [00:17<00:25, 17.97it/s]
 41%|####1     | 323/781 [00:17<00:25, 17.91it/s]
 42%|####1     | 325/781 [00:17<00:25, 17.90it/s]
 42%|####1     | 327/781 [00:18<00:25, 17.51it/s]
 42%|####2     | 329/781 [00:18<00:25, 17.56it/s]
 42%|####2     | 331/781 [00:18<00:25, 17.98it/s]
 43%|####2     | 333/781 [00:18<00:24, 17.96it/s]
 43%|####2     | 335/781 [00:18<00:24, 18.51it/s]
 43%|####3     | 337/781 [00:18<00:24, 18.45it/s]
 43%|####3     | 339/781 [00:18<00:24, 18.29it/s]
 44%|####3     | 341/781 [00:18<00:24, 18.18it/s]
 44%|####3     | 343/781 [00:18<00:23, 18.31it/s]
 44%|####4     | 346/781 [00:19<00:23, 18.89it/s]
 45%|####4     | 349/781 [00:19<00:22, 19.15it/s]
 45%|####4     | 351/781 [00:19<00:22, 18.82it/s]
 45%|####5     | 353/781 [00:19<00:22, 18.91it/s]
 45%|####5     | 355/781 [00:19<00:22, 18.82it/s]
 46%|####5     | 357/781 [00:19<00:22, 19.02it/s]
 46%|####5     | 359/781 [00:19<00:21, 19.29it/s]
 46%|####6     | 361/781 [00:19<00:21, 19.40it/s]
 46%|####6     | 363/781 [00:19<00:22, 18.94it/s]
 47%|####6     | 365/781 [00:20<00:22, 18.61it/s]
 47%|####6     | 367/781 [00:20<00:22, 18.62it/s]
 47%|####7     | 369/781 [00:20<00:21, 18.74it/s]
 48%|####7     | 371/781 [00:20<00:21, 18.85it/s]
 48%|####7     | 373/781 [00:20<00:21, 18.66it/s]
 48%|####8     | 375/781 [00:20<00:21, 18.76it/s]
 48%|####8     | 377/781 [00:20<00:21, 18.84it/s]
 49%|####8     | 379/781 [00:20<00:21, 18.55it/s]
 49%|####8     | 381/781 [00:20<00:21, 18.32it/s]
 49%|####9     | 383/781 [00:21<00:21, 18.50it/s]
 49%|####9     | 386/781 [00:21<00:20, 19.14it/s]
 50%|####9     | 388/781 [00:21<00:20, 18.91it/s]
 50%|####9     | 390/781 [00:21<00:21, 18.56it/s]
 50%|#####     | 392/781 [00:21<00:20, 18.61it/s]
 50%|#####     | 394/781 [00:21<00:20, 18.50it/s]
 51%|#####     | 397/781 [00:21<00:20, 18.89it/s]
 51%|#####1    | 399/781 [00:21<00:20, 18.63it/s]
 51%|#####1    | 401/781 [00:21<00:20, 18.76it/s]
 52%|#####1    | 403/781 [00:22<00:20, 18.52it/s]
 52%|#####1    | 405/781 [00:22<00:20, 18.54it/s]
 52%|#####2    | 407/781 [00:22<00:20, 18.31it/s]
 52%|#####2    | 409/781 [00:22<00:20, 18.39it/s]
 53%|#####2    | 411/781 [00:22<00:20, 18.35it/s]
 53%|#####3    | 414/781 [00:22<00:19, 19.06it/s]
 53%|#####3    | 416/781 [00:22<00:19, 18.85it/s]
 54%|#####3    | 418/781 [00:22<00:19, 18.90it/s]
 54%|#####3    | 420/781 [00:22<00:19, 18.97it/s]
 54%|#####4    | 422/781 [00:23<00:19, 18.63it/s]
 54%|#####4    | 424/781 [00:23<00:19, 18.41it/s]
 55%|#####4    | 426/781 [00:23<00:19, 18.26it/s]
 55%|#####4    | 428/781 [00:23<00:19, 18.15it/s]
 55%|#####5    | 430/781 [00:23<00:19, 18.01it/s]
 55%|#####5    | 432/781 [00:23<00:19, 17.83it/s]
 56%|#####5    | 434/781 [00:23<00:19, 18.16it/s]
 56%|#####5    | 436/781 [00:23<00:19, 18.07it/s]
 56%|#####6    | 438/781 [00:24<00:19, 17.83it/s]
 56%|#####6    | 440/781 [00:24<00:19, 17.82it/s]
 57%|#####6    | 442/781 [00:24<00:18, 18.31it/s]
 57%|#####6    | 444/781 [00:24<00:18, 18.28it/s]
 57%|#####7    | 446/781 [00:24<00:18, 18.19it/s]
 57%|#####7    | 448/781 [00:24<00:18, 18.42it/s]
 58%|#####7    | 450/781 [00:24<00:17, 18.75it/s]
 58%|#####7    | 452/781 [00:24<00:17, 18.56it/s]
 58%|#####8    | 454/781 [00:24<00:17, 18.75it/s]
 59%|#####8    | 457/781 [00:25<00:16, 19.30it/s]
 59%|#####8    | 459/781 [00:25<00:16, 19.13it/s]
 59%|#####9    | 461/781 [00:25<00:16, 19.30it/s]
 59%|#####9    | 463/781 [00:25<00:16, 19.14it/s]
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100%|##########| 781/781 [00:42<00:00, 18.38it/s]




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Validation Progress:  64%|######3   | 28/44 [00:30<00:17,  1.12s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:11,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:11,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:11,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:11,  1.09s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.19s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.15s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.15s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.15s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.14s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.14s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.14s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.14s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.17s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.17s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.17s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.17s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.18s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.18s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.18s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.18s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:04<00:00,  4.19s/it]
100%|##########| 1/1 [00:04<00:00,  4.19s/it]

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  3%|2         | 4/157 [00:00<00:10, 15.03it/s]
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  8%|7         | 12/157 [00:00<00:09, 15.94it/s]
  9%|8         | 14/157 [00:00<00:08, 16.04it/s]
 10%|#         | 16/157 [00:01<00:08, 16.10it/s]
 11%|#1        | 18/157 [00:01<00:08, 16.16it/s]
 13%|#2        | 20/157 [00:01<00:08, 16.22it/s]
 14%|#4        | 22/157 [00:01<00:08, 16.25it/s]
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 17%|#6        | 26/157 [00:01<00:08, 16.28it/s]
 18%|#7        | 28/157 [00:01<00:07, 16.29it/s]
 19%|#9        | 30/157 [00:01<00:07, 16.27it/s]
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 22%|##1       | 34/157 [00:02<00:07, 16.26it/s]
 23%|##2       | 36/157 [00:02<00:07, 16.25it/s]
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 39%|###9      | 62/157 [00:03<00:05, 16.22it/s]
 41%|####      | 64/157 [00:03<00:05, 16.18it/s]
 42%|####2     | 66/157 [00:04<00:05, 16.05it/s]
 43%|####3     | 68/157 [00:04<00:05, 15.99it/s]
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 50%|####9     | 78/157 [00:04<00:04, 15.93it/s]
 51%|#####     | 80/157 [00:04<00:04, 15.92it/s]
 52%|#####2    | 82/157 [00:05<00:04, 15.92it/s]
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 57%|#####7    | 90/157 [00:05<00:04, 16.00it/s]
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 61%|######1   | 96/157 [00:05<00:03, 15.95it/s]
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 80%|########  | 126/157 [00:07<00:01, 15.91it/s]
 82%|########1 | 128/157 [00:07<00:01, 15.89it/s]
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 90%|######### | 142/157 [00:08<00:00, 16.17it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.20it/s]
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100%|##########| 157/157 [00:09<00:00, 16.13it/s]

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  7%|7         | 56/781 [00:03<00:40, 17.96it/s]
  7%|7         | 58/781 [00:03<00:40, 17.98it/s]
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  8%|7         | 62/781 [00:03<00:39, 17.98it/s]
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  9%|8         | 68/781 [00:03<00:39, 18.00it/s]
  9%|8         | 70/781 [00:03<00:39, 17.90it/s]
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 10%|#         | 82/781 [00:04<00:39, 17.92it/s]
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 11%|#1        | 86/781 [00:04<00:38, 17.94it/s]
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 14%|#3        | 106/781 [00:05<00:37, 17.98it/s]
 14%|#3        | 108/781 [00:06<00:37, 17.98it/s]
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 14%|#4        | 112/781 [00:06<00:37, 18.00it/s]
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 15%|#5        | 118/781 [00:06<00:36, 17.99it/s]
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 16%|#6        | 126/781 [00:07<00:36, 18.03it/s]
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 17%|#6        | 132/781 [00:07<00:36, 17.99it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.95it/s]
 17%|#7        | 136/781 [00:07<00:35, 17.96it/s]
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 20%|##        | 158/781 [00:08<00:35, 17.74it/s]
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 21%|##        | 162/781 [00:09<00:34, 17.89it/s]
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 21%|##1       | 166/781 [00:09<00:34, 17.96it/s]
 22%|##1       | 168/781 [00:09<00:34, 17.98it/s]
 22%|##1       | 170/781 [00:09<00:33, 17.99it/s]
 22%|##2       | 172/781 [00:09<00:33, 18.01it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.98it/s]
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 23%|##3       | 180/781 [00:10<00:33, 17.99it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.96it/s]
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 24%|##3       | 186/781 [00:10<00:33, 17.95it/s]
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 33%|###2      | 254/781 [00:14<00:29, 17.80it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.81it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.86it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.89it/s]
 34%|###3      | 262/781 [00:14<00:28, 17.93it/s]
 34%|###3      | 264/781 [00:14<00:28, 17.85it/s]
 34%|###4      | 266/781 [00:14<00:28, 17.90it/s]
 34%|###4      | 268/781 [00:15<00:28, 17.93it/s]
 35%|###4      | 270/781 [00:15<00:28, 17.95it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.93it/s]
 35%|###5      | 274/781 [00:15<00:28, 17.94it/s]
 35%|###5      | 276/781 [00:15<00:28, 17.93it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.90it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.83it/s]
 36%|###6      | 282/781 [00:15<00:28, 17.72it/s]
 36%|###6      | 284/781 [00:15<00:28, 17.62it/s]
 37%|###6      | 286/781 [00:16<00:28, 17.57it/s]
 37%|###6      | 288/781 [00:16<00:28, 17.58it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.57it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.57it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.63it/s]
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 38%|###8      | 298/781 [00:16<00:27, 17.80it/s]
 38%|###8      | 300/781 [00:16<00:26, 17.83it/s]
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 39%|###9      | 306/781 [00:17<00:26, 17.80it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.83it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.77it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.64it/s]
 40%|####      | 314/781 [00:17<00:26, 17.57it/s]
 40%|####      | 316/781 [00:17<00:26, 17.65it/s]
 41%|####      | 318/781 [00:17<00:26, 17.68it/s]
 41%|####      | 320/781 [00:17<00:25, 17.82it/s]
 41%|####1     | 322/781 [00:18<00:25, 17.99it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.99it/s]
 42%|####1     | 326/781 [00:18<00:25, 18.09it/s]
 42%|####1     | 328/781 [00:18<00:24, 18.18it/s]
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 45%|####4     | 350/781 [00:19<00:23, 17.96it/s]
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 50%|####9     | 388/781 [00:21<00:21, 18.52it/s]
 50%|####9     | 390/781 [00:21<00:21, 18.53it/s]
 50%|#####     | 392/781 [00:21<00:20, 18.54it/s]
 50%|#####     | 394/781 [00:21<00:20, 18.53it/s]
 51%|#####     | 396/781 [00:22<00:20, 18.54it/s]
 51%|#####     | 398/781 [00:22<00:20, 18.53it/s]
 51%|#####1    | 400/781 [00:22<00:20, 18.48it/s]
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 70%|#######   | 548/781 [00:30<00:11, 19.48it/s]
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 71%|#######1  | 555/781 [00:30<00:12, 18.82it/s]
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 80%|#######9  | 621/781 [00:34<00:08, 19.14it/s]
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 80%|########  | 626/781 [00:34<00:07, 19.55it/s]
 80%|########  | 628/781 [00:34<00:07, 19.15it/s]
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100%|#########9| 780/781 [00:42<00:00, 19.51it/s]
100%|##########| 781/781 [00:42<00:00, 18.28it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:40,  1.05it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.04it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:01<00:44,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.03s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:45,  1.07s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:42,  1.03s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.02s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.02s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.02s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:41,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:42,  1.09s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:42,  1.09s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:42,  1.09s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:43,  1.11s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:39,  1.05s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:39,  1.05s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:39,  1.05s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:40,  1.06s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:39,  1.06s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:39,  1.06s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:39,  1.06s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:39,  1.06s/it]
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  8%|7         | 61/781 [00:03<00:38, 18.52it/s]
  8%|8         | 63/781 [00:03<00:39, 18.29it/s]
  8%|8         | 65/781 [00:03<00:39, 18.14it/s]
  9%|8         | 67/781 [00:03<00:39, 18.25it/s]
  9%|8         | 69/781 [00:03<00:38, 18.59it/s]
  9%|9         | 72/781 [00:03<00:36, 19.20it/s]
 10%|9         | 75/781 [00:03<00:35, 19.65it/s]
 10%|9         | 77/781 [00:04<00:36, 19.50it/s]
 10%|#         | 80/781 [00:04<00:35, 19.91it/s]
 10%|#         | 82/781 [00:04<00:35, 19.71it/s]
 11%|#         | 85/781 [00:04<00:34, 20.01it/s]
 11%|#1        | 87/781 [00:04<00:35, 19.52it/s]
 11%|#1        | 89/781 [00:04<00:36, 18.98it/s]
 12%|#1        | 92/781 [00:04<00:35, 19.18it/s]
 12%|#2        | 94/781 [00:04<00:36, 19.07it/s]
 12%|#2        | 97/781 [00:05<00:34, 19.59it/s]
 13%|#2        | 99/781 [00:05<00:35, 19.39it/s]
 13%|#2        | 101/781 [00:05<00:35, 19.08it/s]
 13%|#3        | 103/781 [00:05<00:35, 18.97it/s]
 14%|#3        | 106/781 [00:05<00:34, 19.57it/s]
 14%|#3        | 109/781 [00:05<00:33, 19.93it/s]
 14%|#4        | 111/781 [00:05<00:34, 19.48it/s]
 14%|#4        | 113/781 [00:05<00:34, 19.25it/s]
 15%|#4        | 116/781 [00:06<00:33, 19.71it/s]
 15%|#5        | 119/781 [00:06<00:33, 19.80it/s]
 16%|#5        | 122/781 [00:06<00:32, 19.99it/s]
 16%|#5        | 124/781 [00:06<00:32, 19.92it/s]
 16%|#6        | 126/781 [00:06<00:33, 19.73it/s]
 17%|#6        | 129/781 [00:06<00:33, 19.59it/s]
 17%|#6        | 131/781 [00:06<00:34, 19.07it/s]
 17%|#7        | 133/781 [00:06<00:33, 19.09it/s]
 17%|#7        | 135/781 [00:07<00:33, 19.09it/s]
 18%|#7        | 137/781 [00:07<00:34, 18.64it/s]
 18%|#7        | 139/781 [00:07<00:34, 18.61it/s]
 18%|#8        | 141/781 [00:07<00:34, 18.78it/s]
 18%|#8        | 144/781 [00:07<00:32, 19.47it/s]
 19%|#8        | 146/781 [00:07<00:33, 19.05it/s]
 19%|#9        | 149/781 [00:07<00:32, 19.48it/s]
 19%|#9        | 152/781 [00:07<00:31, 19.69it/s]
 20%|#9        | 154/781 [00:08<00:32, 19.10it/s]
 20%|#9        | 156/781 [00:08<00:33, 18.75it/s]
 20%|##        | 159/781 [00:08<00:32, 19.28it/s]
 21%|##        | 162/781 [00:08<00:31, 19.45it/s]
 21%|##1       | 165/781 [00:08<00:31, 19.76it/s]
 21%|##1       | 167/781 [00:08<00:31, 19.61it/s]
 22%|##1       | 170/781 [00:08<00:30, 19.96it/s]
 22%|##2       | 173/781 [00:09<00:30, 19.97it/s]
 23%|##2       | 176/781 [00:09<00:30, 20.11it/s]
 23%|##2       | 179/781 [00:09<00:30, 19.71it/s]
 23%|##3       | 182/781 [00:09<00:30, 19.91it/s]
 24%|##3       | 185/781 [00:09<00:29, 20.18it/s]
 24%|##4       | 188/781 [00:09<00:30, 19.60it/s]
 24%|##4       | 191/781 [00:09<00:29, 19.92it/s]
 25%|##4       | 194/781 [00:10<00:29, 20.15it/s]
 25%|##5       | 197/781 [00:10<00:28, 20.32it/s]
 26%|##5       | 200/781 [00:10<00:28, 20.47it/s]
 26%|##5       | 203/781 [00:10<00:29, 19.90it/s]
 26%|##6       | 206/781 [00:10<00:28, 19.85it/s]
 27%|##6       | 208/781 [00:10<00:29, 19.61it/s]
 27%|##6       | 210/781 [00:10<00:29, 19.55it/s]
 27%|##7       | 212/781 [00:10<00:29, 19.20it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.89it/s]
 28%|##7       | 216/781 [00:11<00:30, 18.79it/s]
 28%|##8       | 219/781 [00:11<00:29, 19.37it/s]
 28%|##8       | 222/781 [00:11<00:28, 19.73it/s]
 29%|##8       | 225/781 [00:11<00:27, 20.01it/s]
 29%|##9       | 227/781 [00:11<00:28, 19.75it/s]
 29%|##9       | 229/781 [00:11<00:28, 19.40it/s]
 30%|##9       | 231/781 [00:11<00:28, 19.16it/s]
 30%|##9       | 234/781 [00:12<00:27, 19.65it/s]
 30%|###       | 236/781 [00:12<00:28, 19.10it/s]
 30%|###       | 238/781 [00:12<00:28, 19.09it/s]
 31%|###       | 240/781 [00:12<00:28, 19.00it/s]
 31%|###1      | 243/781 [00:12<00:27, 19.31it/s]
 31%|###1      | 245/781 [00:12<00:28, 18.92it/s]
 32%|###1      | 247/781 [00:12<00:28, 18.98it/s]
 32%|###1      | 249/781 [00:12<00:28, 18.64it/s]
 32%|###2      | 251/781 [00:13<00:27, 18.98it/s]
 32%|###2      | 253/781 [00:13<00:27, 19.15it/s]
 33%|###2      | 255/781 [00:13<00:27, 19.20it/s]
 33%|###2      | 257/781 [00:13<00:27, 18.82it/s]
 33%|###3      | 259/781 [00:13<00:28, 18.51it/s]
 34%|###3      | 262/781 [00:13<00:27, 19.19it/s]
 34%|###3      | 265/781 [00:13<00:26, 19.46it/s]
 34%|###4      | 267/781 [00:13<00:26, 19.27it/s]
 35%|###4      | 270/781 [00:13<00:25, 19.70it/s]
 35%|###4      | 272/781 [00:14<00:25, 19.70it/s]
 35%|###5      | 275/781 [00:14<00:25, 19.94it/s]
 35%|###5      | 277/781 [00:14<00:25, 19.87it/s]
 36%|###5      | 279/781 [00:14<00:25, 19.56it/s]
 36%|###5      | 281/781 [00:14<00:25, 19.59it/s]
 36%|###6      | 283/781 [00:14<00:26, 19.01it/s]
 36%|###6      | 285/781 [00:14<00:26, 18.51it/s]
 37%|###6      | 287/781 [00:14<00:27, 18.18it/s]
 37%|###7      | 289/781 [00:14<00:26, 18.56it/s]
 37%|###7      | 291/781 [00:15<00:26, 18.45it/s]
 38%|###7      | 293/781 [00:15<00:26, 18.52it/s]
 38%|###7      | 295/781 [00:15<00:26, 18.59it/s]
 38%|###8      | 297/781 [00:15<00:26, 18.35it/s]
 38%|###8      | 299/781 [00:15<00:26, 18.13it/s]
 39%|###8      | 302/781 [00:15<00:25, 18.88it/s]
 39%|###8      | 304/781 [00:15<00:25, 19.06it/s]
 39%|###9      | 306/781 [00:15<00:25, 18.81it/s]
 39%|###9      | 308/781 [00:16<00:25, 18.85it/s]
 40%|###9      | 310/781 [00:16<00:25, 18.50it/s]
 40%|####      | 313/781 [00:16<00:24, 18.91it/s]
 40%|####      | 316/781 [00:16<00:24, 19.34it/s]
 41%|####      | 318/781 [00:16<00:24, 19.05it/s]
 41%|####      | 320/781 [00:16<00:24, 18.71it/s]
 41%|####1     | 322/781 [00:16<00:24, 18.81it/s]
 41%|####1     | 324/781 [00:16<00:24, 18.76it/s]
 42%|####1     | 326/781 [00:16<00:23, 18.97it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.26it/s]
 42%|####2     | 330/781 [00:17<00:23, 19.34it/s]
 43%|####2     | 332/781 [00:17<00:23, 18.83it/s]
 43%|####2     | 334/781 [00:17<00:24, 18.55it/s]
 43%|####3     | 336/781 [00:17<00:23, 18.69it/s]
 43%|####3     | 338/781 [00:17<00:23, 18.81it/s]
 44%|####3     | 340/781 [00:17<00:23, 18.53it/s]
 44%|####3     | 342/781 [00:17<00:24, 18.10it/s]
 44%|####4     | 344/781 [00:17<00:23, 18.50it/s]
 44%|####4     | 346/781 [00:18<00:23, 18.76it/s]
 45%|####4     | 348/781 [00:18<00:23, 18.33it/s]
 45%|####4     | 350/781 [00:18<00:22, 18.75it/s]
 45%|####5     | 352/781 [00:18<00:22, 18.88it/s]
 45%|####5     | 354/781 [00:18<00:23, 18.52it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.57it/s]
 46%|####5     | 358/781 [00:18<00:22, 18.85it/s]
 46%|####6     | 360/781 [00:18<00:22, 18.49it/s]
 46%|####6     | 362/781 [00:18<00:22, 18.25it/s]
 47%|####6     | 364/781 [00:18<00:22, 18.36it/s]
 47%|####6     | 367/781 [00:19<00:21, 19.16it/s]
 47%|####7     | 369/781 [00:19<00:21, 18.92it/s]
 48%|####7     | 371/781 [00:19<00:21, 18.95it/s]
 48%|####7     | 373/781 [00:19<00:21, 18.89it/s]
 48%|####8     | 375/781 [00:19<00:21, 18.69it/s]
 48%|####8     | 377/781 [00:19<00:21, 18.77it/s]
 49%|####8     | 379/781 [00:19<00:21, 18.71it/s]
 49%|####8     | 382/781 [00:19<00:20, 19.16it/s]
 49%|####9     | 384/781 [00:20<00:21, 18.80it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.52it/s]
 50%|####9     | 388/781 [00:20<00:20, 18.88it/s]
 50%|####9     | 390/781 [00:20<00:20, 18.92it/s]
 50%|#####     | 393/781 [00:20<00:19, 19.48it/s]
 51%|#####     | 395/781 [00:20<00:19, 19.51it/s]
 51%|#####     | 398/781 [00:20<00:19, 19.76it/s]
 51%|#####1    | 400/781 [00:20<00:19, 19.73it/s]
 51%|#####1    | 402/781 [00:20<00:19, 19.43it/s]
 52%|#####1    | 404/781 [00:21<00:19, 19.46it/s]
 52%|#####2    | 407/781 [00:21<00:18, 19.76it/s]
 52%|#####2    | 409/781 [00:21<00:19, 19.57it/s]
 53%|#####2    | 411/781 [00:21<00:19, 19.20it/s]
 53%|#####2    | 413/781 [00:21<00:19, 19.03it/s]
 53%|#####3    | 415/781 [00:21<00:19, 18.63it/s]
 53%|#####3    | 417/781 [00:21<00:19, 18.68it/s]
 54%|#####3    | 420/781 [00:21<00:19, 18.93it/s]
 54%|#####4    | 422/781 [00:22<00:19, 18.44it/s]
 54%|#####4    | 424/781 [00:22<00:19, 18.43it/s]
 55%|#####4    | 426/781 [00:22<00:19, 18.47it/s]
 55%|#####4    | 428/781 [00:22<00:18, 18.86it/s]
 55%|#####5    | 430/781 [00:22<00:18, 19.04it/s]
 55%|#####5    | 432/781 [00:22<00:18, 19.26it/s]
 56%|#####5    | 435/781 [00:22<00:17, 19.52it/s]
 56%|#####5    | 437/781 [00:22<00:17, 19.25it/s]
 56%|#####6    | 439/781 [00:22<00:17, 19.05it/s]
 56%|#####6    | 441/781 [00:23<00:18, 18.79it/s]
 57%|#####6    | 443/781 [00:23<00:18, 18.53it/s]
 57%|#####6    | 445/781 [00:23<00:18, 18.57it/s]
 57%|#####7    | 447/781 [00:23<00:18, 18.44it/s]
 57%|#####7    | 449/781 [00:23<00:18, 18.25it/s]
 58%|#####7    | 451/781 [00:23<00:18, 18.12it/s]
 58%|#####8    | 453/781 [00:23<00:18, 18.01it/s]
 58%|#####8    | 455/781 [00:23<00:18, 17.97it/s]
 59%|#####8    | 457/781 [00:23<00:17, 18.04it/s]
 59%|#####8    | 459/781 [00:24<00:17, 17.97it/s]
 59%|#####9    | 461/781 [00:24<00:17, 18.18it/s]
 59%|#####9    | 463/781 [00:24<00:17, 17.92it/s]
 60%|#####9    | 465/781 [00:24<00:17, 17.99it/s]
 60%|#####9    | 467/781 [00:24<00:17, 18.40it/s]
 60%|######    | 469/781 [00:24<00:16, 18.63it/s]
 60%|######    | 471/781 [00:24<00:16, 18.49it/s]
 61%|######    | 473/781 [00:24<00:16, 18.39it/s]
 61%|######    | 475/781 [00:24<00:16, 18.24it/s]
 61%|######1   | 477/781 [00:25<00:16, 18.11it/s]
 61%|######1   | 479/781 [00:25<00:16, 18.37it/s]
 62%|######1   | 481/781 [00:25<00:16, 18.18it/s]
 62%|######1   | 483/781 [00:25<00:16, 18.32it/s]
 62%|######2   | 485/781 [00:25<00:15, 18.68it/s]
 62%|######2   | 487/781 [00:25<00:15, 18.40it/s]
 63%|######2   | 489/781 [00:25<00:16, 18.21it/s]
 63%|######2   | 491/781 [00:25<00:16, 18.10it/s]
 63%|######3   | 493/781 [00:25<00:15, 18.29it/s]
 63%|######3   | 495/781 [00:25<00:15, 18.26it/s]
 64%|######3   | 497/781 [00:26<00:15, 18.11it/s]
 64%|######3   | 499/781 [00:26<00:15, 18.02it/s]
 64%|######4   | 501/781 [00:26<00:15, 17.96it/s]
 64%|######4   | 503/781 [00:26<00:15, 18.20it/s]
 65%|######4   | 505/781 [00:26<00:15, 18.21it/s]
 65%|######4   | 507/781 [00:26<00:14, 18.46it/s]
 65%|######5   | 509/781 [00:26<00:14, 18.52it/s]
 65%|######5   | 511/781 [00:26<00:14, 18.66it/s]
 66%|######5   | 513/781 [00:26<00:14, 18.51it/s]
 66%|######6   | 516/781 [00:27<00:13, 19.17it/s]
 66%|######6   | 518/781 [00:27<00:13, 18.91it/s]
 67%|######6   | 520/781 [00:27<00:13, 18.83it/s]
 67%|######6   | 522/781 [00:27<00:13, 19.05it/s]
 67%|######7   | 524/781 [00:27<00:13, 19.09it/s]
 67%|######7   | 526/781 [00:27<00:13, 18.73it/s]
 68%|######7   | 528/781 [00:27<00:13, 18.72it/s]
 68%|######7   | 530/781 [00:27<00:13, 18.57it/s]
 68%|######8   | 532/781 [00:27<00:13, 18.63it/s]
 68%|######8   | 534/781 [00:28<00:13, 18.80it/s]
 69%|######8   | 537/781 [00:28<00:12, 19.40it/s]
 69%|######9   | 539/781 [00:28<00:12, 19.31it/s]
 69%|######9   | 541/781 [00:28<00:12, 19.26it/s]
 70%|######9   | 544/781 [00:28<00:12, 19.69it/s]
 70%|######9   | 546/781 [00:28<00:12, 19.52it/s]
 70%|#######   | 548/781 [00:28<00:12, 19.26it/s]
 71%|#######   | 551/781 [00:28<00:11, 19.77it/s]
 71%|#######   | 553/781 [00:29<00:11, 19.69it/s]
 71%|#######1  | 555/781 [00:29<00:11, 19.75it/s]
 71%|#######1  | 558/781 [00:29<00:11, 19.71it/s]
 72%|#######1  | 560/781 [00:29<00:11, 19.75it/s]
 72%|#######2  | 563/781 [00:29<00:10, 20.11it/s]
 72%|#######2  | 566/781 [00:29<00:10, 20.34it/s]
 73%|#######2  | 569/781 [00:29<00:10, 20.14it/s]
 73%|#######3  | 572/781 [00:30<00:10, 19.99it/s]
 74%|#######3  | 575/781 [00:30<00:10, 20.24it/s]
 74%|#######4  | 578/781 [00:30<00:09, 20.40it/s]
 74%|#######4  | 581/781 [00:30<00:09, 20.20it/s]
 75%|#######4  | 584/781 [00:30<00:09, 20.38it/s]
 75%|#######5  | 587/781 [00:30<00:09, 20.17it/s]
 76%|#######5  | 590/781 [00:30<00:09, 20.32it/s]
 76%|#######5  | 593/781 [00:31<00:09, 20.47it/s]
 76%|#######6  | 596/781 [00:31<00:09, 20.25it/s]
 77%|#######6  | 599/781 [00:31<00:08, 20.26it/s]
 77%|#######7  | 602/781 [00:31<00:08, 19.92it/s]
 77%|#######7  | 605/781 [00:31<00:08, 20.03it/s]
 78%|#######7  | 608/781 [00:31<00:08, 20.27it/s]
 78%|#######8  | 611/781 [00:31<00:08, 20.14it/s]
 79%|#######8  | 614/781 [00:32<00:08, 19.79it/s]
 79%|#######8  | 616/781 [00:32<00:08, 19.59it/s]
 79%|#######9  | 618/781 [00:32<00:08, 19.57it/s]
 79%|#######9  | 620/781 [00:32<00:08, 19.28it/s]
 80%|#######9  | 622/781 [00:32<00:08, 19.36it/s]
 80%|#######9  | 624/781 [00:32<00:08, 19.13it/s]
 80%|########  | 626/781 [00:32<00:08, 18.93it/s]
 80%|########  | 628/781 [00:32<00:08, 19.00it/s]
 81%|########  | 630/781 [00:32<00:07, 19.03it/s]
 81%|########  | 632/781 [00:33<00:07, 19.04it/s]
 81%|########1 | 634/781 [00:33<00:07, 19.05it/s]
 81%|########1 | 636/781 [00:33<00:07, 19.18it/s]
 82%|########1 | 638/781 [00:33<00:07, 19.33it/s]
 82%|########1 | 640/781 [00:33<00:07, 19.49it/s]
 82%|########2 | 642/781 [00:33<00:07, 19.59it/s]
 82%|########2 | 644/781 [00:33<00:06, 19.63it/s]
 83%|########2 | 646/781 [00:33<00:06, 19.64it/s]
 83%|########2 | 648/781 [00:33<00:06, 19.70it/s]
 83%|########3 | 650/781 [00:33<00:06, 19.75it/s]
 83%|########3 | 652/781 [00:34<00:06, 19.78it/s]
 84%|########3 | 654/781 [00:34<00:06, 19.79it/s]
 84%|########3 | 656/781 [00:34<00:06, 19.81it/s]
 84%|########4 | 658/781 [00:34<00:06, 19.78it/s]
 85%|########4 | 660/781 [00:34<00:06, 19.77it/s]
 85%|########4 | 662/781 [00:34<00:06, 19.74it/s]
 85%|########5 | 664/781 [00:34<00:05, 19.74it/s]
 85%|########5 | 666/781 [00:34<00:05, 19.75it/s]
 86%|########5 | 668/781 [00:34<00:05, 19.77it/s]
 86%|########5 | 670/781 [00:34<00:05, 19.78it/s]
 86%|########6 | 672/781 [00:35<00:05, 19.81it/s]
 86%|########6 | 674/781 [00:35<00:05, 19.82it/s]
 87%|########6 | 676/781 [00:35<00:05, 19.82it/s]
 87%|########6 | 678/781 [00:35<00:05, 19.64it/s]
 87%|########7 | 680/781 [00:35<00:05, 19.61it/s]
 87%|########7 | 682/781 [00:35<00:05, 19.70it/s]
 88%|########7 | 684/781 [00:35<00:04, 19.75it/s]
 88%|########7 | 686/781 [00:35<00:04, 19.77it/s]
 88%|########8 | 688/781 [00:35<00:04, 19.80it/s]
 88%|########8 | 690/781 [00:35<00:04, 19.82it/s]
 89%|########8 | 692/781 [00:36<00:04, 19.83it/s]
 89%|########8 | 694/781 [00:36<00:04, 19.82it/s]
 89%|########9 | 696/781 [00:36<00:04, 19.85it/s]
 89%|########9 | 698/781 [00:36<00:04, 19.83it/s]
 90%|########9 | 700/781 [00:36<00:04, 19.85it/s]
 90%|########9 | 702/781 [00:36<00:03, 19.84it/s]
 90%|######### | 704/781 [00:36<00:03, 19.80it/s]
 90%|######### | 706/781 [00:36<00:03, 19.64it/s]
 91%|######### | 708/781 [00:36<00:03, 19.55it/s]
 91%|######### | 710/781 [00:36<00:03, 19.53it/s]
 91%|#########1| 712/781 [00:37<00:03, 19.64it/s]
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100%|##########| 781/781 [00:40<00:00, 19.19it/s]




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 46%|####6     | 73/157 [00:04<00:05, 16.71it/s]
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 49%|####9     | 77/157 [00:04<00:04, 16.71it/s]
 50%|#####     | 79/157 [00:04<00:04, 16.51it/s]
 52%|#####1    | 81/157 [00:04<00:04, 16.65it/s]
 53%|#####2    | 83/157 [00:05<00:04, 16.77it/s]
 54%|#####4    | 85/157 [00:05<00:04, 16.64it/s]
 55%|#####5    | 87/157 [00:05<00:04, 16.56it/s]
 57%|#####6    | 89/157 [00:05<00:04, 16.67it/s]
 58%|#####7    | 91/157 [00:05<00:03, 16.53it/s]
 59%|#####9    | 93/157 [00:05<00:03, 16.51it/s]
 61%|######    | 95/157 [00:05<00:03, 16.49it/s]
 62%|######1   | 97/157 [00:05<00:03, 16.48it/s]
 63%|######3   | 99/157 [00:06<00:03, 16.48it/s]
 64%|######4   | 101/157 [00:06<00:03, 16.65it/s]
 66%|######5   | 103/157 [00:06<00:03, 16.67it/s]
 67%|######6   | 105/157 [00:06<00:03, 16.72it/s]
 68%|######8   | 107/157 [00:06<00:03, 16.62it/s]
 69%|######9   | 109/157 [00:06<00:02, 16.64it/s]
 71%|#######   | 111/157 [00:06<00:02, 16.84it/s]
 72%|#######1  | 113/157 [00:06<00:02, 16.79it/s]
 73%|#######3  | 115/157 [00:07<00:02, 16.64it/s]
 75%|#######4  | 117/157 [00:07<00:02, 16.75it/s]
 76%|#######5  | 119/157 [00:07<00:02, 16.76it/s]
 77%|#######7  | 121/157 [00:07<00:02, 16.62it/s]
 78%|#######8  | 123/157 [00:07<00:02, 16.63it/s]
 80%|#######9  | 125/157 [00:07<00:01, 16.78it/s]
 81%|########  | 127/157 [00:07<00:01, 16.74it/s]
 82%|########2 | 129/157 [00:07<00:01, 16.74it/s]
 83%|########3 | 131/157 [00:07<00:01, 16.73it/s]
 85%|########4 | 133/157 [00:08<00:01, 16.73it/s]
 86%|########5 | 135/157 [00:08<00:01, 16.60it/s]
 87%|########7 | 137/157 [00:08<00:01, 16.72it/s]
 89%|########8 | 139/157 [00:08<00:01, 16.71it/s]
 90%|########9 | 141/157 [00:08<00:00, 16.72it/s]
 91%|#########1| 143/157 [00:08<00:00, 16.74it/s]
 92%|#########2| 145/157 [00:08<00:00, 16.76it/s]
 94%|#########3| 147/157 [00:08<00:00, 16.73it/s]
 95%|#########4| 149/157 [00:09<00:00, 16.74it/s]
 96%|#########6| 151/157 [00:09<00:00, 16.61it/s]
 97%|#########7| 153/157 [00:09<00:00, 16.75it/s]
 99%|#########8| 155/157 [00:09<00:00, 16.73it/s]
100%|##########| 157/157 [00:09<00:00, 16.51it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:42, 18.46it/s]
  1%|          | 4/781 [00:00<00:41, 18.56it/s]
  1%|          | 6/781 [00:00<00:41, 18.58it/s]
  1%|1         | 8/781 [00:00<00:41, 18.63it/s]
  1%|1         | 10/781 [00:00<00:41, 18.61it/s]
  2%|1         | 12/781 [00:00<00:41, 18.63it/s]
  2%|1         | 14/781 [00:00<00:41, 18.62it/s]
  2%|2         | 16/781 [00:00<00:41, 18.63it/s]
  2%|2         | 18/781 [00:00<00:40, 18.63it/s]
  3%|2         | 20/781 [00:01<00:41, 18.53it/s]
  3%|2         | 22/781 [00:01<00:40, 18.55it/s]
  3%|3         | 24/781 [00:01<00:40, 18.64it/s]
  3%|3         | 26/781 [00:01<00:40, 18.61it/s]
  4%|3         | 28/781 [00:01<00:40, 18.70it/s]
  4%|3         | 30/781 [00:01<00:40, 18.72it/s]
  4%|4         | 32/781 [00:01<00:40, 18.67it/s]
  4%|4         | 34/781 [00:01<00:40, 18.62it/s]
  5%|4         | 36/781 [00:01<00:40, 18.61it/s]
  5%|4         | 38/781 [00:02<00:39, 18.67it/s]
  5%|5         | 40/781 [00:02<00:39, 18.53it/s]
  5%|5         | 42/781 [00:02<00:39, 18.55it/s]
  6%|5         | 44/781 [00:02<00:39, 18.57it/s]
  6%|5         | 46/781 [00:02<00:39, 18.65it/s]
  6%|6         | 48/781 [00:02<00:39, 18.63it/s]
  6%|6         | 50/781 [00:02<00:39, 18.62it/s]
  7%|6         | 52/781 [00:02<00:39, 18.61it/s]
  7%|6         | 54/781 [00:02<00:39, 18.61it/s]
  7%|7         | 56/781 [00:03<00:38, 18.61it/s]
  7%|7         | 58/781 [00:03<00:38, 18.61it/s]
  8%|7         | 60/781 [00:03<00:38, 18.65it/s]
  8%|7         | 62/781 [00:03<00:38, 18.65it/s]
  8%|8         | 64/781 [00:03<00:38, 18.61it/s]
  8%|8         | 66/781 [00:03<00:38, 18.58it/s]
  9%|8         | 68/781 [00:03<00:38, 18.59it/s]
  9%|8         | 70/781 [00:03<00:38, 18.65it/s]
  9%|9         | 72/781 [00:03<00:38, 18.65it/s]
  9%|9         | 74/781 [00:03<00:37, 18.64it/s]
 10%|9         | 76/781 [00:04<00:37, 18.64it/s]
 10%|9         | 78/781 [00:04<00:37, 18.61it/s]
 10%|#         | 80/781 [00:04<00:37, 18.62it/s]
 10%|#         | 82/781 [00:04<00:37, 18.62it/s]
 11%|#         | 84/781 [00:04<00:37, 18.61it/s]
 11%|#1        | 86/781 [00:04<00:37, 18.60it/s]
 11%|#1        | 88/781 [00:04<00:37, 18.44it/s]
 12%|#1        | 90/781 [00:04<00:37, 18.43it/s]
 12%|#1        | 92/781 [00:04<00:37, 18.49it/s]
 12%|#2        | 94/781 [00:05<00:37, 18.50it/s]
 12%|#2        | 96/781 [00:05<00:37, 18.48it/s]
 13%|#2        | 98/781 [00:05<00:37, 18.29it/s]
 13%|#2        | 100/781 [00:05<00:36, 18.43it/s]
 13%|#3        | 102/781 [00:05<00:36, 18.48it/s]
 13%|#3        | 104/781 [00:05<00:36, 18.52it/s]
 14%|#3        | 106/781 [00:05<00:36, 18.68it/s]
 14%|#3        | 108/781 [00:05<00:36, 18.57it/s]
 14%|#4        | 110/781 [00:05<00:35, 18.86it/s]
 14%|#4        | 112/781 [00:06<00:35, 18.92it/s]
 15%|#4        | 114/781 [00:06<00:35, 18.87it/s]
 15%|#4        | 116/781 [00:06<00:35, 18.75it/s]
 15%|#5        | 118/781 [00:06<00:35, 18.64it/s]
 15%|#5        | 120/781 [00:06<00:35, 18.36it/s]
 16%|#5        | 122/781 [00:06<00:35, 18.70it/s]
 16%|#5        | 124/781 [00:06<00:35, 18.70it/s]
 16%|#6        | 126/781 [00:06<00:34, 18.83it/s]
 16%|#6        | 128/781 [00:06<00:34, 18.97it/s]
 17%|#6        | 130/781 [00:06<00:34, 19.04it/s]
 17%|#6        | 132/781 [00:07<00:34, 18.88it/s]
 17%|#7        | 134/781 [00:07<00:34, 18.94it/s]
 17%|#7        | 136/781 [00:07<00:33, 18.98it/s]
 18%|#7        | 138/781 [00:07<00:33, 19.04it/s]
 18%|#7        | 140/781 [00:07<00:33, 19.01it/s]
 18%|#8        | 142/781 [00:07<00:33, 19.22it/s]
 18%|#8        | 144/781 [00:07<00:33, 19.03it/s]
 19%|#8        | 146/781 [00:07<00:33, 19.24it/s]
 19%|#8        | 148/781 [00:07<00:33, 19.16it/s]
 19%|#9        | 150/781 [00:08<00:32, 19.12it/s]
 19%|#9        | 152/781 [00:08<00:33, 18.97it/s]
 20%|#9        | 154/781 [00:08<00:32, 19.01it/s]
 20%|#9        | 156/781 [00:08<00:32, 19.16it/s]
 20%|##        | 158/781 [00:08<00:32, 19.14it/s]
 20%|##        | 160/781 [00:08<00:32, 18.99it/s]
 21%|##        | 162/781 [00:08<00:32, 19.16it/s]
 21%|##        | 164/781 [00:08<00:32, 18.95it/s]
 21%|##1       | 166/781 [00:08<00:32, 18.86it/s]
 22%|##1       | 168/781 [00:08<00:32, 19.11it/s]
 22%|##1       | 170/781 [00:09<00:32, 19.02it/s]
 22%|##2       | 172/781 [00:09<00:31, 19.17it/s]
 22%|##2       | 174/781 [00:09<00:32, 18.89it/s]
 23%|##2       | 176/781 [00:09<00:32, 18.77it/s]
 23%|##2       | 178/781 [00:09<00:31, 18.90it/s]
 23%|##3       | 180/781 [00:09<00:32, 18.72it/s]
 23%|##3       | 182/781 [00:09<00:32, 18.68it/s]
 24%|##3       | 184/781 [00:09<00:31, 18.66it/s]
 24%|##3       | 186/781 [00:09<00:32, 18.59it/s]
 24%|##4       | 188/781 [00:10<00:32, 18.40it/s]
 24%|##4       | 190/781 [00:10<00:31, 18.59it/s]
 25%|##4       | 192/781 [00:10<00:31, 18.42it/s]
 25%|##4       | 194/781 [00:10<00:31, 18.61it/s]
 25%|##5       | 196/781 [00:10<00:31, 18.56it/s]
 25%|##5       | 198/781 [00:10<00:31, 18.57it/s]
 26%|##5       | 200/781 [00:10<00:31, 18.38it/s]
 26%|##5       | 202/781 [00:10<00:31, 18.51it/s]
 26%|##6       | 204/781 [00:10<00:31, 18.54it/s]
 26%|##6       | 206/781 [00:11<00:31, 18.37it/s]
 27%|##6       | 208/781 [00:11<00:30, 18.59it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.52it/s]
 27%|##7       | 212/781 [00:11<00:30, 18.54it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.37it/s]
 28%|##7       | 216/781 [00:11<00:30, 18.61it/s]
 28%|##7       | 218/781 [00:11<00:30, 18.66it/s]
 28%|##8       | 220/781 [00:11<00:30, 18.42it/s]
 28%|##8       | 222/781 [00:11<00:30, 18.60it/s]
 29%|##8       | 224/781 [00:11<00:29, 18.60it/s]
 29%|##8       | 226/781 [00:12<00:29, 18.58it/s]
 29%|##9       | 228/781 [00:12<00:30, 18.43it/s]
 29%|##9       | 230/781 [00:12<00:29, 18.64it/s]
 30%|##9       | 232/781 [00:12<00:29, 18.52it/s]
 30%|##9       | 234/781 [00:12<00:29, 18.43it/s]
 30%|###       | 236/781 [00:12<00:29, 18.48it/s]
 30%|###       | 238/781 [00:12<00:29, 18.63it/s]
 31%|###       | 240/781 [00:12<00:28, 18.69it/s]
 31%|###       | 242/781 [00:12<00:28, 18.59it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.18it/s]
 31%|###1      | 246/781 [00:13<00:28, 18.53it/s]
 32%|###1      | 248/781 [00:13<00:28, 18.70it/s]
 32%|###2      | 250/781 [00:13<00:28, 18.84it/s]
 32%|###2      | 252/781 [00:13<00:27, 18.91it/s]
 33%|###2      | 254/781 [00:13<00:28, 18.80it/s]
 33%|###2      | 256/781 [00:13<00:27, 19.04it/s]
 33%|###3      | 258/781 [00:13<00:27, 18.88it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.10it/s]
 34%|###3      | 262/781 [00:14<00:27, 19.10it/s]
 34%|###3      | 264/781 [00:14<00:27, 19.07it/s]
 34%|###4      | 266/781 [00:14<00:26, 19.11it/s]
 34%|###4      | 268/781 [00:14<00:27, 18.95it/s]
 35%|###4      | 270/781 [00:14<00:26, 18.99it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.16it/s]
 35%|###5      | 274/781 [00:14<00:26, 18.79it/s]
 35%|###5      | 276/781 [00:14<00:27, 18.56it/s]
 36%|###5      | 278/781 [00:14<00:27, 18.49it/s]
 36%|###5      | 280/781 [00:14<00:27, 18.48it/s]
 36%|###6      | 282/781 [00:15<00:27, 18.42it/s]
 36%|###6      | 284/781 [00:15<00:27, 18.07it/s]
 37%|###6      | 286/781 [00:15<00:27, 18.29it/s]
 37%|###6      | 288/781 [00:15<00:26, 18.44it/s]
 37%|###7      | 290/781 [00:15<00:26, 18.43it/s]
 37%|###7      | 292/781 [00:15<00:26, 18.77it/s]
 38%|###7      | 294/781 [00:15<00:25, 18.82it/s]
 38%|###7      | 296/781 [00:15<00:25, 19.03it/s]
 38%|###8      | 298/781 [00:15<00:25, 19.21it/s]
 38%|###8      | 300/781 [00:16<00:25, 18.93it/s]
 39%|###8      | 302/781 [00:16<00:25, 19.04it/s]
 39%|###8      | 304/781 [00:16<00:24, 19.15it/s]
 39%|###9      | 306/781 [00:16<00:25, 18.83it/s]
 39%|###9      | 308/781 [00:16<00:24, 18.95it/s]
 40%|###9      | 310/781 [00:16<00:24, 19.09it/s]
 40%|###9      | 312/781 [00:16<00:24, 19.21it/s]
 40%|####      | 314/781 [00:16<00:24, 18.87it/s]
 40%|####      | 316/781 [00:16<00:24, 19.02it/s]
 41%|####      | 318/781 [00:16<00:24, 19.16it/s]
 41%|####      | 320/781 [00:17<00:23, 19.27it/s]
 41%|####1     | 322/781 [00:17<00:23, 19.14it/s]
 41%|####1     | 324/781 [00:17<00:24, 18.93it/s]
 42%|####1     | 326/781 [00:17<00:24, 18.86it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.00it/s]
 42%|####2     | 330/781 [00:17<00:23, 18.92it/s]
 43%|####2     | 332/781 [00:17<00:23, 18.88it/s]
 43%|####2     | 334/781 [00:17<00:23, 19.03it/s]
 43%|####3     | 336/781 [00:17<00:23, 18.93it/s]
 43%|####3     | 338/781 [00:18<00:23, 19.10it/s]
 44%|####3     | 340/781 [00:18<00:22, 19.21it/s]
 44%|####3     | 342/781 [00:18<00:23, 19.02it/s]
 44%|####4     | 344/781 [00:18<00:23, 18.96it/s]
 44%|####4     | 346/781 [00:18<00:22, 19.14it/s]
 45%|####4     | 348/781 [00:18<00:22, 19.03it/s]
 45%|####4     | 350/781 [00:18<00:22, 18.77it/s]
 45%|####5     | 352/781 [00:18<00:22, 18.78it/s]
 45%|####5     | 354/781 [00:18<00:22, 18.67it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.53it/s]
 46%|####5     | 358/781 [00:19<00:22, 18.41it/s]
 46%|####6     | 360/781 [00:19<00:22, 18.53it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.66it/s]
 47%|####6     | 364/781 [00:19<00:22, 18.27it/s]
 47%|####6     | 366/781 [00:19<00:22, 18.43it/s]
 47%|####7     | 368/781 [00:19<00:22, 18.57it/s]
 47%|####7     | 370/781 [00:19<00:22, 18.26it/s]
 48%|####7     | 372/781 [00:19<00:22, 18.42it/s]
 48%|####7     | 374/781 [00:19<00:22, 18.38it/s]
 48%|####8     | 376/781 [00:20<00:22, 18.16it/s]
 48%|####8     | 378/781 [00:20<00:22, 18.25it/s]
 49%|####8     | 380/781 [00:20<00:21, 18.52it/s]
 49%|####8     | 382/781 [00:20<00:21, 18.67it/s]
 49%|####9     | 384/781 [00:20<00:21, 18.74it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.51it/s]
 50%|####9     | 388/781 [00:20<00:20, 18.75it/s]
 50%|####9     | 390/781 [00:20<00:20, 18.64it/s]
 50%|#####     | 392/781 [00:20<00:20, 18.74it/s]
 50%|#####     | 394/781 [00:21<00:20, 18.85it/s]
 51%|#####     | 396/781 [00:21<00:20, 18.60it/s]
 51%|#####     | 398/781 [00:21<00:20, 18.67it/s]
 51%|#####1    | 400/781 [00:21<00:20, 18.70it/s]
 51%|#####1    | 402/781 [00:21<00:20, 18.75it/s]
 52%|#####1    | 404/781 [00:21<00:19, 18.99it/s]
 52%|#####1    | 406/781 [00:21<00:19, 19.11it/s]
 52%|#####2    | 408/781 [00:21<00:19, 19.00it/s]
 52%|#####2    | 410/781 [00:21<00:19, 19.10it/s]
 53%|#####2    | 412/781 [00:21<00:19, 18.90it/s]
 53%|#####3    | 414/781 [00:22<00:19, 18.73it/s]
 53%|#####3    | 416/781 [00:22<00:19, 18.90it/s]
 54%|#####3    | 418/781 [00:22<00:18, 19.16it/s]
 54%|#####3    | 420/781 [00:22<00:18, 19.33it/s]
 54%|#####4    | 422/781 [00:22<00:18, 19.49it/s]
 54%|#####4    | 425/781 [00:22<00:18, 19.70it/s]
 55%|#####4    | 427/781 [00:22<00:18, 19.50it/s]
 55%|#####4    | 429/781 [00:22<00:17, 19.58it/s]
 55%|#####5    | 431/781 [00:22<00:17, 19.65it/s]
 56%|#####5    | 434/781 [00:23<00:17, 19.58it/s]
 56%|#####5    | 436/781 [00:23<00:17, 19.24it/s]
 56%|#####6    | 438/781 [00:23<00:17, 19.15it/s]
 56%|#####6    | 440/781 [00:23<00:17, 18.95it/s]
 57%|#####6    | 442/781 [00:23<00:17, 18.94it/s]
 57%|#####6    | 444/781 [00:23<00:17, 18.79it/s]
 57%|#####7    | 446/781 [00:23<00:18, 18.48it/s]
 57%|#####7    | 448/781 [00:23<00:17, 18.60it/s]
 58%|#####7    | 450/781 [00:23<00:17, 18.89it/s]
 58%|#####7    | 452/781 [00:24<00:17, 19.11it/s]
 58%|#####8    | 454/781 [00:24<00:17, 18.94it/s]
 58%|#####8    | 456/781 [00:24<00:16, 19.14it/s]
 59%|#####8    | 458/781 [00:24<00:17, 18.90it/s]
 59%|#####8    | 460/781 [00:24<00:16, 19.09it/s]
 59%|#####9    | 462/781 [00:24<00:16, 19.12it/s]
 59%|#####9    | 464/781 [00:24<00:16, 18.93it/s]
 60%|#####9    | 466/781 [00:24<00:16, 18.89it/s]
 60%|#####9    | 468/781 [00:24<00:16, 19.15it/s]
 60%|######    | 470/781 [00:25<00:16, 19.36it/s]
 60%|######    | 472/781 [00:25<00:15, 19.42it/s]
 61%|######    | 474/781 [00:25<00:16, 19.03it/s]
 61%|######    | 476/781 [00:25<00:15, 19.24it/s]
 61%|######1   | 478/781 [00:25<00:15, 19.18it/s]
 61%|######1   | 480/781 [00:25<00:15, 19.26it/s]
 62%|######1   | 482/781 [00:25<00:15, 18.80it/s]
 62%|######1   | 484/781 [00:25<00:15, 18.82it/s]
 62%|######2   | 486/781 [00:25<00:15, 18.62it/s]
 62%|######2   | 488/781 [00:25<00:15, 18.64it/s]
 63%|######2   | 490/781 [00:26<00:15, 18.58it/s]
 63%|######2   | 492/781 [00:26<00:15, 18.52it/s]
 63%|######3   | 494/781 [00:26<00:15, 18.48it/s]
 64%|######3   | 496/781 [00:26<00:15, 18.65it/s]
 64%|######3   | 498/781 [00:26<00:15, 18.75it/s]
 64%|######4   | 500/781 [00:26<00:15, 18.57it/s]
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100%|#########9| 780/781 [00:41<00:00, 18.41it/s]
100%|##########| 781/781 [00:41<00:00, 18.64it/s]




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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:38<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:38<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:38<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:38<00:09,  1.16s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:44<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:44<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:44<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:44<00:03,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.01it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:47<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:05<00:00,  5.51s/it]
100%|##########| 1/1 [00:05<00:00,  5.51s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:11, 13.60it/s]
  3%|2         | 4/157 [00:00<00:11, 13.91it/s]
  4%|3         | 6/157 [00:00<00:10, 14.71it/s]
  5%|5         | 8/157 [00:00<00:09, 15.65it/s]
  6%|6         | 10/157 [00:00<00:09, 16.23it/s]
  8%|7         | 12/157 [00:00<00:08, 16.61it/s]
  9%|8         | 14/157 [00:00<00:08, 16.87it/s]
 10%|#         | 16/157 [00:00<00:08, 17.05it/s]
 11%|#1        | 18/157 [00:01<00:08, 17.15it/s]
 13%|#2        | 20/157 [00:01<00:07, 17.15it/s]
 14%|#4        | 22/157 [00:01<00:07, 17.20it/s]
 15%|#5        | 24/157 [00:01<00:07, 17.18it/s]
 17%|#6        | 26/157 [00:01<00:07, 17.19it/s]
 18%|#7        | 28/157 [00:01<00:07, 17.16it/s]
 19%|#9        | 30/157 [00:01<00:07, 17.08it/s]
 20%|##        | 32/157 [00:01<00:07, 17.15it/s]
 22%|##1       | 34/157 [00:02<00:07, 17.07it/s]
 23%|##2       | 36/157 [00:02<00:07, 17.17it/s]
 24%|##4       | 38/157 [00:02<00:06, 17.16it/s]
 25%|##5       | 40/157 [00:02<00:06, 17.20it/s]
 27%|##6       | 42/157 [00:02<00:06, 17.28it/s]
 28%|##8       | 44/157 [00:02<00:06, 17.18it/s]
 29%|##9       | 46/157 [00:02<00:06, 17.00it/s]
 31%|###       | 48/157 [00:02<00:06, 16.97it/s]
 32%|###1      | 50/157 [00:02<00:06, 17.00it/s]
 33%|###3      | 52/157 [00:03<00:06, 17.03it/s]
 34%|###4      | 54/157 [00:03<00:06, 17.02it/s]
 36%|###5      | 56/157 [00:03<00:05, 17.00it/s]
 37%|###6      | 58/157 [00:03<00:05, 16.99it/s]
 38%|###8      | 60/157 [00:03<00:05, 17.13it/s]
 39%|###9      | 62/157 [00:03<00:05, 17.23it/s]
 41%|####      | 64/157 [00:03<00:05, 17.29it/s]
 42%|####2     | 66/157 [00:03<00:05, 17.37it/s]
 43%|####3     | 68/157 [00:04<00:05, 17.23it/s]
 45%|####4     | 70/157 [00:04<00:05, 17.14it/s]
 46%|####5     | 72/157 [00:04<00:04, 17.11it/s]
 47%|####7     | 74/157 [00:04<00:04, 17.14it/s]
 48%|####8     | 76/157 [00:04<00:04, 17.10it/s]
 50%|####9     | 78/157 [00:04<00:04, 17.07it/s]
 51%|#####     | 80/157 [00:04<00:04, 17.08it/s]
 52%|#####2    | 82/157 [00:04<00:04, 17.10it/s]
 54%|#####3    | 84/157 [00:04<00:04, 17.11it/s]
 55%|#####4    | 86/157 [00:05<00:04, 17.13it/s]
 56%|#####6    | 88/157 [00:05<00:04, 17.20it/s]
 57%|#####7    | 90/157 [00:05<00:03, 17.24it/s]
 59%|#####8    | 92/157 [00:05<00:03, 17.29it/s]
 60%|#####9    | 94/157 [00:05<00:03, 17.31it/s]
 61%|######1   | 96/157 [00:05<00:03, 17.32it/s]
 62%|######2   | 98/157 [00:05<00:03, 17.35it/s]
 64%|######3   | 100/157 [00:05<00:03, 17.36it/s]
 65%|######4   | 102/157 [00:05<00:03, 17.38it/s]
 66%|######6   | 104/157 [00:06<00:03, 17.41it/s]
 68%|######7   | 106/157 [00:06<00:02, 17.41it/s]
 69%|######8   | 108/157 [00:06<00:02, 17.41it/s]
 70%|#######   | 110/157 [00:06<00:02, 17.38it/s]
 71%|#######1  | 112/157 [00:06<00:02, 17.42it/s]
 73%|#######2  | 114/157 [00:06<00:02, 17.36it/s]
 74%|#######3  | 116/157 [00:06<00:02, 17.35it/s]
 75%|#######5  | 118/157 [00:06<00:02, 17.29it/s]
 76%|#######6  | 120/157 [00:07<00:02, 17.33it/s]
 78%|#######7  | 122/157 [00:07<00:02, 17.35it/s]
 79%|#######8  | 124/157 [00:07<00:01, 17.37it/s]
 80%|########  | 126/157 [00:07<00:01, 17.38it/s]
 82%|########1 | 128/157 [00:07<00:01, 17.15it/s]
 83%|########2 | 130/157 [00:07<00:01, 16.98it/s]
 84%|########4 | 132/157 [00:07<00:01, 16.84it/s]
 85%|########5 | 134/157 [00:07<00:01, 16.80it/s]
 87%|########6 | 136/157 [00:07<00:01, 16.69it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.73it/s]
 89%|########9 | 140/157 [00:08<00:01, 16.82it/s]
 90%|######### | 142/157 [00:08<00:00, 16.91it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.95it/s]
 93%|#########2| 146/157 [00:08<00:00, 16.98it/s]
 94%|#########4| 148/157 [00:08<00:00, 17.08it/s]
 96%|#########5| 150/157 [00:08<00:00, 17.21it/s]
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 99%|#########9| 156/157 [00:09<00:00, 17.33it/s]
100%|##########| 157/157 [00:09<00:00, 17.12it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:45, 16.96it/s]
  1%|          | 4/781 [00:00<00:47, 16.31it/s]
  1%|          | 6/781 [00:00<00:48, 16.09it/s]
  1%|1         | 8/781 [00:00<00:48, 16.01it/s]
  1%|1         | 10/781 [00:00<00:46, 16.42it/s]
  2%|1         | 12/781 [00:00<00:44, 17.15it/s]
  2%|1         | 14/781 [00:00<00:43, 17.80it/s]
  2%|2         | 16/781 [00:00<00:41, 18.30it/s]
  2%|2         | 18/781 [00:01<00:41, 18.56it/s]
  3%|2         | 20/781 [00:01<00:40, 18.65it/s]
  3%|2         | 22/781 [00:01<00:40, 18.56it/s]
  3%|3         | 24/781 [00:01<00:40, 18.52it/s]
  3%|3         | 26/781 [00:01<00:40, 18.48it/s]
  4%|3         | 28/781 [00:01<00:40, 18.46it/s]
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  4%|4         | 32/781 [00:01<00:40, 18.44it/s]
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  5%|4         | 36/781 [00:02<00:40, 18.42it/s]
  5%|4         | 38/781 [00:02<00:40, 18.34it/s]
  5%|5         | 40/781 [00:02<00:40, 18.21it/s]
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  6%|5         | 44/781 [00:02<00:40, 17.98it/s]
  6%|5         | 46/781 [00:02<00:40, 18.11it/s]
  6%|6         | 48/781 [00:02<00:40, 18.03it/s]
  6%|6         | 50/781 [00:02<00:40, 18.03it/s]
  7%|6         | 52/781 [00:02<00:40, 18.17it/s]
  7%|6         | 54/781 [00:03<00:39, 18.19it/s]
  7%|7         | 56/781 [00:03<00:39, 18.24it/s]
  7%|7         | 58/781 [00:03<00:39, 18.31it/s]
  8%|7         | 60/781 [00:03<00:39, 18.19it/s]
  8%|7         | 62/781 [00:03<00:39, 18.12it/s]
  8%|8         | 64/781 [00:03<00:39, 18.06it/s]
  8%|8         | 66/781 [00:03<00:39, 18.05it/s]
  9%|8         | 68/781 [00:03<00:39, 18.05it/s]
  9%|8         | 70/781 [00:03<00:39, 18.07it/s]
  9%|9         | 72/781 [00:03<00:39, 18.04it/s]
  9%|9         | 74/781 [00:04<00:39, 18.01it/s]
 10%|9         | 76/781 [00:04<00:39, 18.02it/s]
 10%|9         | 78/781 [00:04<00:38, 18.06it/s]
 10%|#         | 80/781 [00:04<00:38, 18.05it/s]
 10%|#         | 82/781 [00:04<00:38, 18.04it/s]
 11%|#         | 84/781 [00:04<00:38, 18.02it/s]
 11%|#1        | 86/781 [00:04<00:38, 18.01it/s]
 11%|#1        | 88/781 [00:04<00:38, 18.00it/s]
 12%|#1        | 90/781 [00:04<00:38, 18.14it/s]
 12%|#1        | 92/781 [00:05<00:37, 18.24it/s]
 12%|#2        | 94/781 [00:05<00:37, 18.24it/s]
 12%|#2        | 96/781 [00:05<00:37, 18.17it/s]
 13%|#2        | 98/781 [00:05<00:37, 18.24it/s]
 13%|#2        | 100/781 [00:05<00:37, 18.31it/s]
 13%|#3        | 102/781 [00:05<00:37, 18.22it/s]
 13%|#3        | 104/781 [00:05<00:37, 18.13it/s]
 14%|#3        | 106/781 [00:05<00:37, 18.15it/s]
 14%|#3        | 108/781 [00:05<00:36, 18.26it/s]
 14%|#4        | 110/781 [00:06<00:36, 18.34it/s]
 14%|#4        | 112/781 [00:06<00:36, 18.36it/s]
 15%|#4        | 114/781 [00:06<00:36, 18.42it/s]
 15%|#4        | 116/781 [00:06<00:36, 18.45it/s]
 15%|#5        | 118/781 [00:06<00:35, 18.49it/s]
 15%|#5        | 120/781 [00:06<00:35, 18.48it/s]
 16%|#5        | 122/781 [00:06<00:35, 18.51it/s]
 16%|#5        | 124/781 [00:06<00:35, 18.50it/s]
 16%|#6        | 126/781 [00:06<00:35, 18.46it/s]
 16%|#6        | 128/781 [00:07<00:35, 18.32it/s]
 17%|#6        | 130/781 [00:07<00:35, 18.24it/s]
 17%|#6        | 132/781 [00:07<00:35, 18.14it/s]
 17%|#7        | 134/781 [00:07<00:35, 18.07it/s]
 17%|#7        | 136/781 [00:07<00:35, 18.03it/s]
 18%|#7        | 138/781 [00:07<00:35, 18.04it/s]
 18%|#7        | 140/781 [00:07<00:35, 17.88it/s]
 18%|#8        | 142/781 [00:07<00:35, 18.08it/s]
 18%|#8        | 144/781 [00:07<00:34, 18.21it/s]
 19%|#8        | 146/781 [00:08<00:34, 18.30it/s]
 19%|#8        | 148/781 [00:08<00:34, 18.32it/s]
 19%|#9        | 150/781 [00:08<00:34, 18.37it/s]
 19%|#9        | 152/781 [00:08<00:34, 18.43it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.47it/s]
 20%|#9        | 156/781 [00:08<00:33, 18.52it/s]
 20%|##        | 158/781 [00:08<00:33, 18.52it/s]
 20%|##        | 160/781 [00:08<00:33, 18.53it/s]
 21%|##        | 162/781 [00:08<00:33, 18.51it/s]
 21%|##        | 164/781 [00:09<00:33, 18.51it/s]
 21%|##1       | 166/781 [00:09<00:33, 18.51it/s]
 22%|##1       | 168/781 [00:09<00:33, 18.52it/s]
 22%|##1       | 170/781 [00:09<00:32, 18.53it/s]
 22%|##2       | 172/781 [00:09<00:32, 18.53it/s]
 22%|##2       | 174/781 [00:09<00:32, 18.52it/s]
 23%|##2       | 176/781 [00:09<00:32, 18.54it/s]
 23%|##2       | 178/781 [00:09<00:32, 18.53it/s]
 23%|##3       | 180/781 [00:09<00:32, 18.55it/s]
 23%|##3       | 182/781 [00:10<00:32, 18.54it/s]
 24%|##3       | 184/781 [00:10<00:32, 18.54it/s]
 24%|##3       | 186/781 [00:10<00:32, 18.55it/s]
 24%|##4       | 188/781 [00:10<00:31, 18.55it/s]
 24%|##4       | 190/781 [00:10<00:31, 18.56it/s]
 25%|##4       | 192/781 [00:10<00:31, 18.55it/s]
 25%|##4       | 194/781 [00:10<00:31, 18.55it/s]
 25%|##5       | 196/781 [00:10<00:31, 18.54it/s]
 25%|##5       | 198/781 [00:10<00:31, 18.57it/s]
 26%|##5       | 200/781 [00:10<00:31, 18.53it/s]
 26%|##5       | 202/781 [00:11<00:31, 18.51it/s]
 26%|##6       | 204/781 [00:11<00:31, 18.44it/s]
 26%|##6       | 206/781 [00:11<00:31, 18.43it/s]
 27%|##6       | 208/781 [00:11<00:31, 18.43it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.42it/s]
 27%|##7       | 212/781 [00:11<00:30, 18.41it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.43it/s]
 28%|##7       | 216/781 [00:11<00:30, 18.43it/s]
 28%|##7       | 218/781 [00:11<00:30, 18.42it/s]
 28%|##8       | 220/781 [00:12<00:30, 18.37it/s]
 28%|##8       | 222/781 [00:12<00:30, 18.35it/s]
 29%|##8       | 224/781 [00:12<00:30, 18.29it/s]
 29%|##8       | 226/781 [00:12<00:30, 18.33it/s]
 29%|##9       | 228/781 [00:12<00:30, 18.34it/s]
 29%|##9       | 230/781 [00:12<00:30, 18.22it/s]
 30%|##9       | 232/781 [00:12<00:29, 18.30it/s]
 30%|##9       | 234/781 [00:12<00:30, 18.20it/s]
 30%|###       | 236/781 [00:12<00:29, 18.22it/s]
 30%|###       | 238/781 [00:13<00:29, 18.22it/s]
 31%|###       | 240/781 [00:13<00:29, 18.22it/s]
 31%|###       | 242/781 [00:13<00:29, 18.16it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.23it/s]
 31%|###1      | 246/781 [00:13<00:29, 18.22it/s]
 32%|###1      | 248/781 [00:13<00:29, 18.27it/s]
 32%|###2      | 250/781 [00:13<00:29, 18.25it/s]
 32%|###2      | 252/781 [00:13<00:28, 18.33it/s]
 33%|###2      | 254/781 [00:13<00:28, 18.33it/s]
 33%|###2      | 256/781 [00:14<00:28, 18.38it/s]
 33%|###3      | 258/781 [00:14<00:28, 18.40it/s]
 33%|###3      | 260/781 [00:14<00:28, 18.40it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.39it/s]
 34%|###3      | 264/781 [00:14<00:28, 18.38it/s]
 34%|###4      | 266/781 [00:14<00:27, 18.42it/s]
 34%|###4      | 268/781 [00:14<00:28, 18.31it/s]
 35%|###4      | 270/781 [00:14<00:28, 18.19it/s]
 35%|###4      | 272/781 [00:14<00:27, 18.21it/s]
 35%|###5      | 274/781 [00:15<00:27, 18.21it/s]
 35%|###5      | 276/781 [00:15<00:27, 18.25it/s]
 36%|###5      | 278/781 [00:15<00:27, 18.14it/s]
 36%|###5      | 280/781 [00:15<00:27, 18.11it/s]
 36%|###6      | 282/781 [00:15<00:27, 18.21it/s]
 36%|###6      | 284/781 [00:15<00:27, 18.29it/s]
 37%|###6      | 286/781 [00:15<00:27, 18.33it/s]
 37%|###6      | 288/781 [00:15<00:26, 18.35it/s]
 37%|###7      | 290/781 [00:15<00:26, 18.36it/s]
 37%|###7      | 292/781 [00:15<00:26, 18.36it/s]
 38%|###7      | 294/781 [00:16<00:26, 18.38it/s]
 38%|###7      | 296/781 [00:16<00:26, 18.39it/s]
 38%|###8      | 298/781 [00:16<00:26, 18.24it/s]
 38%|###8      | 300/781 [00:16<00:26, 18.17it/s]
 39%|###8      | 302/781 [00:16<00:26, 18.09it/s]
 39%|###8      | 304/781 [00:16<00:26, 18.06it/s]
 39%|###9      | 306/781 [00:16<00:26, 18.04it/s]
 39%|###9      | 308/781 [00:16<00:26, 18.02it/s]
 40%|###9      | 310/781 [00:16<00:26, 18.00it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.99it/s]
 40%|####      | 314/781 [00:17<00:25, 17.99it/s]
 40%|####      | 316/781 [00:17<00:25, 18.10it/s]
 41%|####      | 318/781 [00:17<00:25, 18.21it/s]
 41%|####      | 320/781 [00:17<00:25, 18.29it/s]
 41%|####1     | 322/781 [00:17<00:25, 18.32it/s]
 41%|####1     | 324/781 [00:17<00:24, 18.36it/s]
 42%|####1     | 326/781 [00:17<00:24, 18.40it/s]
 42%|####1     | 328/781 [00:17<00:24, 18.41it/s]
 42%|####2     | 330/781 [00:18<00:24, 18.42it/s]
 43%|####2     | 332/781 [00:18<00:24, 18.46it/s]
 43%|####2     | 334/781 [00:18<00:24, 18.45it/s]
 43%|####3     | 336/781 [00:18<00:24, 18.46it/s]
 43%|####3     | 338/781 [00:18<00:24, 18.45it/s]
 44%|####3     | 340/781 [00:18<00:23, 18.47it/s]
 44%|####3     | 342/781 [00:18<00:23, 18.35it/s]
 44%|####4     | 344/781 [00:18<00:23, 18.29it/s]
 44%|####4     | 346/781 [00:18<00:23, 18.17it/s]
 45%|####4     | 348/781 [00:19<00:23, 18.24it/s]
 45%|####4     | 350/781 [00:19<00:23, 18.27it/s]
 45%|####5     | 352/781 [00:19<00:23, 18.31it/s]
 45%|####5     | 354/781 [00:19<00:23, 18.34it/s]
 46%|####5     | 356/781 [00:19<00:23, 18.34it/s]
 46%|####5     | 358/781 [00:19<00:23, 18.36it/s]
 46%|####6     | 360/781 [00:19<00:22, 18.33it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.28it/s]
 47%|####6     | 364/781 [00:19<00:22, 18.23it/s]
 47%|####6     | 366/781 [00:20<00:22, 18.15it/s]
 47%|####7     | 368/781 [00:20<00:22, 18.25it/s]
 47%|####7     | 370/781 [00:20<00:22, 18.34it/s]
 48%|####7     | 372/781 [00:20<00:22, 18.38it/s]
 48%|####7     | 374/781 [00:20<00:22, 18.41it/s]
 48%|####8     | 376/781 [00:20<00:21, 18.44it/s]
 48%|####8     | 378/781 [00:20<00:31, 12.98it/s]
 49%|####8     | 380/781 [00:20<00:28, 14.24it/s]
 49%|####8     | 382/781 [00:21<00:26, 15.30it/s]
 49%|####9     | 384/781 [00:21<00:24, 16.08it/s]
 49%|####9     | 386/781 [00:21<00:23, 16.59it/s]
 50%|####9     | 388/781 [00:21<00:23, 16.95it/s]
 50%|####9     | 390/781 [00:21<00:22, 17.21it/s]
 50%|#####     | 392/781 [00:21<00:22, 17.46it/s]
 50%|#####     | 394/781 [00:21<00:21, 17.75it/s]
 51%|#####     | 396/781 [00:21<00:21, 17.96it/s]
 51%|#####     | 398/781 [00:21<00:21, 17.98it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.98it/s]
 51%|#####1    | 402/781 [00:22<00:21, 18.00it/s]
 52%|#####1    | 404/781 [00:22<00:20, 18.06it/s]
 52%|#####1    | 406/781 [00:22<00:20, 18.07it/s]
 52%|#####2    | 408/781 [00:22<00:20, 17.84it/s]
 52%|#####2    | 410/781 [00:22<00:20, 17.70it/s]
 53%|#####2    | 412/781 [00:22<00:20, 17.63it/s]
 53%|#####3    | 414/781 [00:22<00:20, 17.77it/s]
 53%|#####3    | 416/781 [00:22<00:20, 17.90it/s]
 54%|#####3    | 418/781 [00:23<00:20, 17.97it/s]
 54%|#####3    | 420/781 [00:23<00:20, 18.03it/s]
 54%|#####4    | 422/781 [00:23<00:19, 18.05it/s]
 54%|#####4    | 424/781 [00:23<00:19, 17.99it/s]
 55%|#####4    | 426/781 [00:23<00:19, 18.26it/s]
 55%|#####4    | 428/781 [00:23<00:19, 18.28it/s]
 55%|#####5    | 430/781 [00:23<00:19, 18.24it/s]
 55%|#####5    | 432/781 [00:23<00:19, 18.28it/s]
 56%|#####5    | 434/781 [00:23<00:18, 18.45it/s]
 56%|#####5    | 436/781 [00:24<00:18, 18.59it/s]
 56%|#####6    | 438/781 [00:24<00:18, 18.65it/s]
 56%|#####6    | 440/781 [00:24<00:18, 18.51it/s]
 57%|#####6    | 442/781 [00:24<00:18, 18.43it/s]
 57%|#####6    | 444/781 [00:24<00:18, 18.57it/s]
 57%|#####7    | 446/781 [00:24<00:17, 18.67it/s]
 57%|#####7    | 448/781 [00:24<00:17, 18.77it/s]
 58%|#####7    | 450/781 [00:24<00:17, 18.85it/s]
 58%|#####7    | 452/781 [00:24<00:17, 18.74it/s]
 58%|#####8    | 454/781 [00:25<00:17, 18.47it/s]
 58%|#####8    | 456/781 [00:25<00:17, 18.60it/s]
 59%|#####8    | 458/781 [00:25<00:17, 18.43it/s]
 59%|#####8    | 460/781 [00:25<00:17, 18.52it/s]
 59%|#####9    | 462/781 [00:25<00:16, 18.80it/s]
 59%|#####9    | 464/781 [00:25<00:17, 18.61it/s]
 60%|#####9    | 466/781 [00:25<00:17, 18.49it/s]
 60%|#####9    | 468/781 [00:25<00:17, 18.39it/s]
 60%|######    | 470/781 [00:25<00:16, 18.73it/s]
 60%|######    | 472/781 [00:25<00:16, 18.60it/s]
 61%|######    | 474/781 [00:26<00:16, 18.46it/s]
 61%|######    | 476/781 [00:26<00:16, 18.57it/s]
 61%|######1   | 478/781 [00:26<00:16, 18.85it/s]
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 62%|######1   | 482/781 [00:26<00:15, 19.01it/s]
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 62%|######2   | 486/781 [00:26<00:15, 18.91it/s]
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 63%|######2   | 490/781 [00:26<00:15, 18.94it/s]
 63%|######2   | 492/781 [00:27<00:15, 18.70it/s]
 63%|######3   | 494/781 [00:27<00:15, 18.56it/s]
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 64%|######3   | 498/781 [00:27<00:14, 18.90it/s]
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 66%|######5   | 512/781 [00:28<00:14, 18.76it/s]
 66%|######5   | 514/781 [00:28<00:14, 18.53it/s]
 66%|######6   | 516/781 [00:28<00:14, 18.43it/s]
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 69%|######8   | 536/781 [00:29<00:13, 18.47it/s]
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 69%|######9   | 540/781 [00:29<00:13, 18.44it/s]
 69%|######9   | 542/781 [00:29<00:13, 18.35it/s]
 70%|######9   | 544/781 [00:29<00:12, 18.45it/s]
 70%|######9   | 546/781 [00:29<00:12, 18.62it/s]
 70%|#######   | 548/781 [00:30<00:12, 18.47it/s]
 70%|#######   | 550/781 [00:30<00:12, 18.59it/s]
 71%|#######   | 552/781 [00:30<00:12, 18.75it/s]
 71%|#######   | 554/781 [00:30<00:12, 18.78it/s]
 71%|#######1  | 556/781 [00:30<00:12, 18.63it/s]
 71%|#######1  | 558/781 [00:30<00:12, 18.49it/s]
 72%|#######1  | 560/781 [00:30<00:11, 18.65it/s]
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 72%|#######2  | 564/781 [00:30<00:11, 18.85it/s]
 72%|#######2  | 566/781 [00:30<00:11, 19.04it/s]
 73%|#######2  | 568/781 [00:31<00:11, 19.00it/s]
 73%|#######2  | 570/781 [00:31<00:11, 19.14it/s]
 73%|#######3  | 572/781 [00:31<00:10, 19.26it/s]
 73%|#######3  | 574/781 [00:31<00:10, 19.36it/s]
 74%|#######3  | 576/781 [00:31<00:10, 19.43it/s]
 74%|#######4  | 578/781 [00:31<00:10, 19.49it/s]
 74%|#######4  | 580/781 [00:31<00:10, 19.54it/s]
 75%|#######4  | 582/781 [00:31<00:10, 19.59it/s]
 75%|#######4  | 584/781 [00:31<00:10, 19.50it/s]
 75%|#######5  | 586/781 [00:32<00:10, 19.38it/s]
 75%|#######5  | 588/781 [00:32<00:10, 19.27it/s]
 76%|#######5  | 590/781 [00:32<00:09, 19.36it/s]
 76%|#######5  | 592/781 [00:32<00:09, 19.15it/s]
 76%|#######6  | 594/781 [00:32<00:09, 19.21it/s]
 76%|#######6  | 596/781 [00:32<00:09, 19.28it/s]
 77%|#######6  | 598/781 [00:32<00:09, 19.29it/s]
 77%|#######6  | 600/781 [00:32<00:09, 19.44it/s]
 77%|#######7  | 602/781 [00:32<00:09, 19.24it/s]
 77%|#######7  | 604/781 [00:32<00:09, 19.00it/s]
 78%|#######7  | 606/781 [00:33<00:09, 18.92it/s]
 78%|#######7  | 608/781 [00:33<00:09, 18.90it/s]
 78%|#######8  | 610/781 [00:33<00:09, 18.89it/s]
 78%|#######8  | 612/781 [00:33<00:08, 18.89it/s]
 79%|#######8  | 614/781 [00:33<00:08, 19.06it/s]
 79%|#######8  | 616/781 [00:33<00:08, 19.02it/s]
 79%|#######9  | 618/781 [00:33<00:08, 18.97it/s]
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 80%|#######9  | 622/781 [00:33<00:08, 19.12it/s]
 80%|#######9  | 624/781 [00:34<00:08, 18.83it/s]
 80%|########  | 626/781 [00:34<00:08, 19.02it/s]
 80%|########  | 628/781 [00:34<00:08, 18.94it/s]
 81%|########  | 630/781 [00:34<00:07, 19.16it/s]
 81%|########  | 632/781 [00:34<00:07, 19.30it/s]
 81%|########1 | 634/781 [00:34<00:07, 19.41it/s]
 81%|########1 | 636/781 [00:34<00:07, 19.50it/s]
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 82%|########1 | 640/781 [00:34<00:07, 19.40it/s]
 82%|########2 | 642/781 [00:34<00:07, 19.07it/s]
 82%|########2 | 644/781 [00:35<00:07, 18.84it/s]
 83%|########2 | 646/781 [00:35<00:07, 18.68it/s]
 83%|########2 | 648/781 [00:35<00:07, 18.81it/s]
 83%|########3 | 650/781 [00:35<00:06, 18.84it/s]
 83%|########3 | 652/781 [00:35<00:06, 18.99it/s]
 84%|########3 | 654/781 [00:35<00:06, 18.80it/s]
 84%|########3 | 656/781 [00:35<00:06, 18.73it/s]
 84%|########4 | 658/781 [00:35<00:06, 18.64it/s]
 85%|########4 | 660/781 [00:35<00:06, 18.32it/s]
 85%|########4 | 662/781 [00:36<00:06, 18.13it/s]
 85%|########5 | 664/781 [00:36<00:06, 18.34it/s]
 85%|########5 | 666/781 [00:36<00:06, 18.15it/s]
 86%|########5 | 668/781 [00:36<00:06, 18.36it/s]
 86%|########5 | 670/781 [00:36<00:06, 18.17it/s]
 86%|########6 | 672/781 [00:36<00:05, 18.21it/s]
 86%|########6 | 674/781 [00:36<00:05, 18.08it/s]
 87%|########6 | 676/781 [00:36<00:05, 18.20it/s]
 87%|########6 | 678/781 [00:36<00:05, 18.38it/s]
 87%|########7 | 680/781 [00:37<00:05, 18.14it/s]
 87%|########7 | 682/781 [00:37<00:05, 18.19it/s]
 88%|########7 | 684/781 [00:37<00:05, 18.23it/s]
 88%|########7 | 686/781 [00:37<00:05, 18.06it/s]
 88%|########8 | 688/781 [00:37<00:05, 18.11it/s]
 88%|########8 | 690/781 [00:37<00:05, 18.20it/s]
 89%|########8 | 692/781 [00:37<00:04, 18.44it/s]
 89%|########8 | 694/781 [00:37<00:04, 18.40it/s]
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 90%|########9 | 700/781 [00:38<00:04, 18.54it/s]
 90%|########9 | 702/781 [00:38<00:04, 18.68it/s]
 90%|######### | 704/781 [00:38<00:04, 18.56it/s]
 90%|######### | 706/781 [00:38<00:04, 18.34it/s]
 91%|######### | 708/781 [00:38<00:04, 18.20it/s]
 91%|######### | 710/781 [00:38<00:03, 18.27it/s]
 91%|#########1| 712/781 [00:38<00:03, 18.25it/s]
 91%|#########1| 714/781 [00:38<00:03, 18.42it/s]
 92%|#########1| 716/781 [00:38<00:03, 18.19it/s]
 92%|#########1| 718/781 [00:39<00:03, 18.37it/s]
 92%|#########2| 720/781 [00:39<00:03, 18.37it/s]
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 93%|#########2| 724/781 [00:39<00:03, 18.70it/s]
 93%|#########2| 726/781 [00:39<00:02, 18.59it/s]
 93%|#########3| 728/781 [00:39<00:02, 18.30it/s]
 93%|#########3| 730/781 [00:39<00:02, 18.12it/s]
 94%|#########3| 732/781 [00:39<00:02, 18.48it/s]
 94%|#########3| 734/781 [00:39<00:02, 18.57it/s]
 94%|#########4| 736/781 [00:40<00:02, 18.80it/s]
 94%|#########4| 738/781 [00:40<00:02, 18.77it/s]
 95%|#########4| 740/781 [00:40<00:02, 18.53it/s]
 95%|#########5| 742/781 [00:40<00:02, 18.52it/s]
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 96%|#########5| 748/781 [00:40<00:01, 18.80it/s]
 96%|#########6| 750/781 [00:40<00:01, 18.80it/s]
 96%|#########6| 752/781 [00:40<00:01, 18.74it/s]
 97%|#########6| 754/781 [00:41<00:01, 18.48it/s]
 97%|#########6| 756/781 [00:41<00:01, 18.45it/s]
 97%|#########7| 758/781 [00:41<00:01, 18.53it/s]
 97%|#########7| 760/781 [00:41<00:01, 18.60it/s]
 98%|#########7| 762/781 [00:41<00:01, 18.39it/s]
 98%|#########7| 764/781 [00:41<00:00, 18.69it/s]
 98%|#########8| 766/781 [00:41<00:00, 18.68it/s]
 98%|#########8| 768/781 [00:41<00:00, 18.77it/s]
 99%|#########8| 770/781 [00:41<00:00, 18.89it/s]
 99%|#########8| 772/781 [00:41<00:00, 18.92it/s]
 99%|#########9| 774/781 [00:42<00:00, 19.02it/s]
 99%|#########9| 776/781 [00:42<00:00, 18.72it/s]
100%|#########9| 778/781 [00:42<00:00, 18.60it/s]
100%|#########9| 780/781 [00:42<00:00, 18.64it/s]
100%|##########| 781/781 [00:42<00:00, 18.39it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:40,  1.06it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.04it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:01<00:45,  1.07s/it]
Validation Progress:   5%|4         | 2/44 [00:01<00:42,  1.01s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   7%|6         | 3/44 [00:02<00:40,  1.01it/s]
Validation Progress:   7%|6         | 3/44 [00:02<00:40,  1.00it/s]
Validation Progress:   7%|6         | 3/44 [00:02<00:40,  1.00it/s]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.02it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.02it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.01it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.02it/s]
Validation Progress:  11%|#1        | 5/44 [00:05<00:39,  1.02s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:39,  1.02s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:39,  1.02s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.03s/it]
Validation Progress:  14%|#3        | 6/44 [00:05<00:37,  1.02it/s]
Validation Progress:  14%|#3        | 6/44 [00:05<00:37,  1.02it/s]
Validation Progress:  14%|#3        | 6/44 [00:05<00:37,  1.02it/s]
Validation Progress:  14%|#3        | 6/44 [00:06<00:38,  1.00s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.03s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.03s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:38,  1.03s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:38,  1.04s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.00s/it]
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  7%|7         | 58/781 [00:03<00:38, 18.98it/s]
  8%|7         | 60/781 [00:03<00:38, 18.89it/s]
  8%|7         | 62/781 [00:03<00:37, 18.99it/s]
  8%|8         | 64/781 [00:03<00:37, 19.10it/s]
  8%|8         | 66/781 [00:03<00:37, 19.08it/s]
  9%|8         | 68/781 [00:03<00:37, 19.15it/s]
  9%|8         | 70/781 [00:03<00:37, 19.19it/s]
  9%|9         | 72/781 [00:03<00:37, 19.10it/s]
  9%|9         | 74/781 [00:03<00:37, 18.99it/s]
 10%|9         | 76/781 [00:04<00:37, 18.89it/s]
 10%|9         | 78/781 [00:04<00:36, 19.02it/s]
 10%|#         | 80/781 [00:04<00:36, 19.12it/s]
 10%|#         | 82/781 [00:04<00:36, 19.20it/s]
 11%|#         | 84/781 [00:04<00:36, 19.06it/s]
 11%|#1        | 86/781 [00:04<00:36, 18.92it/s]
 11%|#1        | 88/781 [00:04<00:36, 18.84it/s]
 12%|#1        | 90/781 [00:04<00:36, 18.80it/s]
 12%|#1        | 92/781 [00:04<00:36, 18.80it/s]
 12%|#2        | 94/781 [00:04<00:36, 18.81it/s]
 12%|#2        | 96/781 [00:05<00:36, 18.81it/s]
 13%|#2        | 98/781 [00:05<00:36, 18.87it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.03it/s]
 13%|#3        | 102/781 [00:05<00:35, 18.99it/s]
 13%|#3        | 104/781 [00:05<00:35, 18.94it/s]
 14%|#3        | 106/781 [00:05<00:35, 18.87it/s]
 14%|#3        | 108/781 [00:05<00:35, 18.85it/s]
 14%|#4        | 110/781 [00:05<00:35, 18.83it/s]
 14%|#4        | 112/781 [00:05<00:35, 18.65it/s]
 15%|#4        | 114/781 [00:06<00:35, 18.62it/s]
 15%|#4        | 116/781 [00:06<00:35, 18.69it/s]
 15%|#5        | 118/781 [00:06<00:35, 18.73it/s]
 15%|#5        | 120/781 [00:06<00:35, 18.81it/s]
 16%|#5        | 122/781 [00:06<00:35, 18.77it/s]
 16%|#5        | 124/781 [00:06<00:35, 18.75it/s]
 16%|#6        | 126/781 [00:06<00:34, 18.76it/s]
 16%|#6        | 128/781 [00:06<00:34, 18.79it/s]
 17%|#6        | 130/781 [00:06<00:34, 18.73it/s]
 17%|#6        | 132/781 [00:06<00:34, 18.69it/s]
 17%|#7        | 134/781 [00:07<00:34, 18.66it/s]
 17%|#7        | 136/781 [00:07<00:34, 18.72it/s]
 18%|#7        | 138/781 [00:07<00:34, 18.72it/s]
 18%|#7        | 140/781 [00:07<00:34, 18.72it/s]
 18%|#8        | 142/781 [00:07<00:34, 18.71it/s]
 18%|#8        | 144/781 [00:07<00:33, 18.77it/s]
 19%|#8        | 146/781 [00:07<00:33, 18.79it/s]
 19%|#8        | 148/781 [00:07<00:33, 18.80it/s]
 19%|#9        | 150/781 [00:07<00:33, 18.82it/s]
 19%|#9        | 152/781 [00:08<00:33, 18.83it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.84it/s]
 20%|#9        | 156/781 [00:08<00:33, 18.82it/s]
 20%|##        | 158/781 [00:08<00:33, 18.81it/s]
 20%|##        | 160/781 [00:08<00:32, 18.85it/s]
 21%|##        | 162/781 [00:08<00:32, 18.81it/s]
 21%|##        | 164/781 [00:08<00:32, 18.81it/s]
 21%|##1       | 166/781 [00:08<00:32, 18.81it/s]
 22%|##1       | 168/781 [00:08<00:32, 18.81it/s]
 22%|##1       | 170/781 [00:09<00:32, 18.74it/s]
 22%|##2       | 172/781 [00:09<00:32, 18.73it/s]
 22%|##2       | 174/781 [00:09<00:32, 18.77it/s]
 23%|##2       | 176/781 [00:09<00:31, 18.93it/s]
 23%|##2       | 178/781 [00:09<00:31, 19.07it/s]
 23%|##3       | 180/781 [00:09<00:31, 19.17it/s]
 23%|##3       | 182/781 [00:09<00:31, 19.26it/s]
 24%|##3       | 184/781 [00:09<00:30, 19.31it/s]
 24%|##3       | 186/781 [00:09<00:31, 19.09it/s]
 24%|##4       | 188/781 [00:09<00:31, 18.92it/s]
 24%|##4       | 190/781 [00:10<00:31, 18.93it/s]
 25%|##4       | 192/781 [00:10<00:31, 18.89it/s]
 25%|##4       | 194/781 [00:10<00:31, 18.83it/s]
 25%|##5       | 196/781 [00:10<00:31, 18.86it/s]
 25%|##5       | 198/781 [00:10<00:30, 18.81it/s]
 26%|##5       | 200/781 [00:10<00:30, 18.81it/s]
 26%|##5       | 202/781 [00:10<00:30, 18.80it/s]
 26%|##6       | 204/781 [00:10<00:30, 18.87it/s]
 26%|##6       | 206/781 [00:10<00:30, 18.85it/s]
 27%|##6       | 208/781 [00:11<00:30, 18.84it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.85it/s]
 27%|##7       | 212/781 [00:11<00:32, 17.63it/s]
 27%|##7       | 214/781 [00:11<00:31, 17.99it/s]
 28%|##7       | 216/781 [00:11<00:30, 18.25it/s]
 28%|##7       | 218/781 [00:11<00:30, 18.49it/s]
 28%|##8       | 220/781 [00:11<00:30, 18.60it/s]
 28%|##8       | 222/781 [00:11<00:29, 18.68it/s]
 29%|##8       | 224/781 [00:11<00:29, 18.73it/s]
 29%|##8       | 226/781 [00:11<00:29, 18.83it/s]
 29%|##9       | 228/781 [00:12<00:29, 18.82it/s]
 29%|##9       | 230/781 [00:12<00:29, 18.80it/s]
 30%|##9       | 232/781 [00:12<00:29, 18.83it/s]
 30%|##9       | 234/781 [00:12<00:29, 18.84it/s]
 30%|###       | 236/781 [00:12<00:28, 18.86it/s]
 30%|###       | 238/781 [00:12<00:28, 18.87it/s]
 31%|###       | 240/781 [00:12<00:28, 18.89it/s]
 31%|###       | 242/781 [00:12<00:28, 18.89it/s]
 31%|###1      | 244/781 [00:12<00:28, 18.87it/s]
 31%|###1      | 246/781 [00:13<00:28, 18.85it/s]
 32%|###1      | 248/781 [00:13<00:28, 18.76it/s]
 32%|###2      | 250/781 [00:13<00:28, 18.81it/s]
 32%|###2      | 252/781 [00:13<00:28, 18.73it/s]
 33%|###2      | 254/781 [00:13<00:27, 18.84it/s]
 33%|###2      | 256/781 [00:13<00:27, 18.98it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.05it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.13it/s]
 34%|###3      | 262/781 [00:13<00:27, 19.19it/s]
 34%|###3      | 264/781 [00:14<00:26, 19.19it/s]
 34%|###4      | 266/781 [00:14<00:26, 19.22it/s]
 34%|###4      | 268/781 [00:14<00:26, 19.25it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.17it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.17it/s]
 35%|###5      | 274/781 [00:14<00:26, 19.13it/s]
 35%|###5      | 276/781 [00:14<00:26, 18.98it/s]
 36%|###5      | 278/781 [00:14<00:26, 19.02it/s]
 36%|###5      | 280/781 [00:14<00:26, 18.88it/s]
 36%|###6      | 282/781 [00:14<00:26, 18.62it/s]
 36%|###6      | 284/781 [00:15<00:26, 18.60it/s]
 37%|###6      | 286/781 [00:15<00:26, 18.73it/s]
 37%|###6      | 288/781 [00:15<00:26, 18.54it/s]
 37%|###7      | 290/781 [00:15<00:26, 18.68it/s]
 37%|###7      | 292/781 [00:15<00:25, 18.83it/s]
 38%|###7      | 294/781 [00:15<00:25, 18.99it/s]
 38%|###7      | 296/781 [00:15<00:25, 18.91it/s]
 38%|###8      | 298/781 [00:15<00:25, 19.13it/s]
 38%|###8      | 300/781 [00:15<00:25, 18.95it/s]
 39%|###8      | 302/781 [00:16<00:25, 18.99it/s]
 39%|###8      | 304/781 [00:16<00:25, 19.00it/s]
 39%|###9      | 306/781 [00:16<00:24, 19.19it/s]
 39%|###9      | 308/781 [00:16<00:24, 19.17it/s]
 40%|###9      | 310/781 [00:16<00:24, 18.98it/s]
 40%|###9      | 312/781 [00:16<00:24, 19.02it/s]
 40%|####      | 314/781 [00:16<00:24, 19.05it/s]
 40%|####      | 316/781 [00:16<00:24, 19.29it/s]
 41%|####      | 318/781 [00:16<00:24, 19.29it/s]
 41%|####      | 320/781 [00:16<00:24, 19.08it/s]
 41%|####1     | 322/781 [00:17<00:23, 19.19it/s]
 41%|####1     | 324/781 [00:17<00:24, 19.03it/s]
 42%|####1     | 326/781 [00:17<00:23, 19.07it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.09it/s]
 42%|####2     | 330/781 [00:17<00:23, 19.25it/s]
 43%|####2     | 332/781 [00:17<00:23, 19.05it/s]
 43%|####2     | 334/781 [00:17<00:23, 19.06it/s]
 43%|####3     | 336/781 [00:17<00:23, 19.27it/s]
 43%|####3     | 338/781 [00:17<00:23, 19.05it/s]
 44%|####3     | 340/781 [00:17<00:23, 19.10it/s]
 44%|####3     | 342/781 [00:18<00:22, 19.30it/s]
 44%|####4     | 344/781 [00:18<00:22, 19.12it/s]
 44%|####4     | 346/781 [00:18<00:22, 19.14it/s]
 45%|####4     | 348/781 [00:18<00:22, 19.16it/s]
 45%|####4     | 350/781 [00:18<00:22, 19.18it/s]
 45%|####5     | 352/781 [00:18<00:22, 19.17it/s]
 45%|####5     | 354/781 [00:18<00:22, 19.33it/s]
 46%|####5     | 356/781 [00:18<00:22, 19.29it/s]
 46%|####5     | 358/781 [00:18<00:21, 19.27it/s]
 46%|####6     | 360/781 [00:19<00:21, 19.26it/s]
 46%|####6     | 362/781 [00:19<00:21, 19.08it/s]
 47%|####6     | 364/781 [00:19<00:21, 19.23it/s]
 47%|####6     | 366/781 [00:19<00:21, 18.91it/s]
 47%|####7     | 368/781 [00:19<00:21, 18.88it/s]
 47%|####7     | 370/781 [00:19<00:22, 18.64it/s]
 48%|####7     | 372/781 [00:19<00:21, 18.68it/s]
 48%|####7     | 374/781 [00:19<00:21, 18.85it/s]
 48%|####8     | 376/781 [00:19<00:21, 18.57it/s]
 48%|####8     | 378/781 [00:20<00:21, 18.64it/s]
 49%|####8     | 380/781 [00:20<00:21, 18.45it/s]
 49%|####8     | 382/781 [00:20<00:21, 18.58it/s]
 49%|####9     | 384/781 [00:20<00:21, 18.59it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.60it/s]
 50%|####9     | 388/781 [00:20<00:21, 18.42it/s]
 50%|####9     | 390/781 [00:20<00:20, 18.63it/s]
 50%|#####     | 392/781 [00:20<00:21, 18.46it/s]
 50%|#####     | 394/781 [00:20<00:20, 18.45it/s]
 51%|#####     | 396/781 [00:20<00:20, 18.61it/s]
 51%|#####     | 398/781 [00:21<00:20, 18.59it/s]
 51%|#####1    | 400/781 [00:21<00:20, 18.57it/s]
 51%|#####1    | 402/781 [00:21<00:20, 18.40it/s]
 52%|#####1    | 404/781 [00:21<00:20, 18.57it/s]
 52%|#####1    | 406/781 [00:21<00:20, 18.55it/s]
 52%|#####2    | 408/781 [00:21<00:20, 18.54it/s]
 52%|#####2    | 410/781 [00:21<00:20, 18.35it/s]
 53%|#####2    | 412/781 [00:21<00:20, 18.43it/s]
 53%|#####3    | 414/781 [00:21<00:19, 18.44it/s]
 53%|#####3    | 416/781 [00:22<00:19, 18.47it/s]
 54%|#####3    | 418/781 [00:22<00:19, 18.62it/s]
 54%|#####3    | 420/781 [00:22<00:19, 18.61it/s]
 54%|#####4    | 422/781 [00:22<00:19, 18.57it/s]
 54%|#####4    | 424/781 [00:22<00:19, 18.55it/s]
 55%|#####4    | 426/781 [00:22<00:19, 18.39it/s]
 55%|#####4    | 428/781 [00:22<00:19, 18.45it/s]
 55%|#####5    | 430/781 [00:22<00:18, 18.58it/s]
 55%|#####5    | 432/781 [00:22<00:18, 18.55it/s]
 56%|#####5    | 434/781 [00:23<00:18, 18.55it/s]
 56%|#####5    | 436/781 [00:23<00:18, 18.40it/s]
 56%|#####6    | 438/781 [00:23<00:18, 18.71it/s]
 56%|#####6    | 440/781 [00:23<00:18, 18.72it/s]
 57%|#####6    | 442/781 [00:23<00:18, 18.57it/s]
 57%|#####6    | 444/781 [00:23<00:18, 18.28it/s]
 57%|#####7    | 446/781 [00:23<00:18, 18.22it/s]
 57%|#####7    | 448/781 [00:23<00:18, 18.31it/s]
 58%|#####7    | 450/781 [00:23<00:18, 18.37it/s]
 58%|#####7    | 452/781 [00:24<00:17, 18.40it/s]
 58%|#####8    | 454/781 [00:24<00:17, 18.49it/s]
 58%|#####8    | 456/781 [00:24<00:17, 18.69it/s]
 59%|#####8    | 458/781 [00:24<00:17, 18.73it/s]
 59%|#####8    | 460/781 [00:24<00:17, 18.68it/s]
 59%|#####9    | 462/781 [00:24<00:17, 18.62it/s]
 59%|#####9    | 464/781 [00:24<00:17, 18.62it/s]
 60%|#####9    | 466/781 [00:24<00:16, 18.57it/s]
 60%|#####9    | 468/781 [00:24<00:16, 18.59it/s]
 60%|######    | 470/781 [00:24<00:16, 18.62it/s]
 60%|######    | 472/781 [00:25<00:16, 18.64it/s]
 61%|######    | 474/781 [00:25<00:16, 18.66it/s]
 61%|######    | 476/781 [00:25<00:16, 18.69it/s]
 61%|######1   | 478/781 [00:25<00:16, 18.74it/s]
 61%|######1   | 480/781 [00:25<00:16, 18.72it/s]
 62%|######1   | 482/781 [00:25<00:15, 18.75it/s]
 62%|######1   | 484/781 [00:25<00:15, 18.75it/s]
 62%|######2   | 486/781 [00:25<00:15, 18.74it/s]
 62%|######2   | 488/781 [00:25<00:15, 18.77it/s]
 63%|######2   | 490/781 [00:26<00:15, 18.74it/s]
 63%|######2   | 492/781 [00:26<00:15, 18.76it/s]
 63%|######3   | 494/781 [00:26<00:15, 18.77it/s]
 64%|######3   | 496/781 [00:26<00:15, 18.78it/s]
 64%|######3   | 498/781 [00:26<00:15, 18.81it/s]
 64%|######4   | 500/781 [00:26<00:14, 18.79it/s]
 64%|######4   | 502/781 [00:26<00:14, 18.83it/s]
 65%|######4   | 504/781 [00:26<00:14, 19.04it/s]
 65%|######4   | 506/781 [00:26<00:14, 19.13it/s]
 65%|######5   | 508/781 [00:26<00:14, 19.22it/s]
 65%|######5   | 510/781 [00:27<00:14, 19.27it/s]
 66%|######5   | 512/781 [00:27<00:13, 19.35it/s]
 66%|######5   | 514/781 [00:27<00:13, 19.37it/s]
 66%|######6   | 516/781 [00:27<00:13, 19.38it/s]
 66%|######6   | 518/781 [00:27<00:13, 19.36it/s]
 67%|######6   | 520/781 [00:27<00:13, 19.37it/s]
 67%|######6   | 522/781 [00:27<00:13, 19.33it/s]
 67%|######7   | 524/781 [00:27<00:13, 19.33it/s]
 67%|######7   | 526/781 [00:27<00:13, 19.34it/s]
 68%|######7   | 528/781 [00:28<00:13, 19.38it/s]
 68%|######7   | 530/781 [00:28<00:12, 19.35it/s]
 68%|######8   | 532/781 [00:28<00:12, 19.34it/s]
 68%|######8   | 534/781 [00:28<00:12, 19.32it/s]
 69%|######8   | 536/781 [00:28<00:12, 19.36it/s]
 69%|######8   | 538/781 [00:28<00:12, 19.34it/s]
 69%|######9   | 540/781 [00:28<00:12, 19.30it/s]
 69%|######9   | 542/781 [00:28<00:12, 19.28it/s]
 70%|######9   | 544/781 [00:28<00:12, 19.29it/s]
 70%|######9   | 546/781 [00:28<00:12, 19.26it/s]
 70%|#######   | 548/781 [00:29<00:12, 19.27it/s]
 70%|#######   | 550/781 [00:29<00:11, 19.27it/s]
 71%|#######   | 552/781 [00:29<00:11, 19.31it/s]
 71%|#######   | 554/781 [00:29<00:11, 19.31it/s]
 71%|#######1  | 556/781 [00:29<00:11, 19.31it/s]
 71%|#######1  | 558/781 [00:29<00:11, 19.27it/s]
 72%|#######1  | 560/781 [00:29<00:11, 19.32it/s]
 72%|#######1  | 562/781 [00:29<00:11, 19.28it/s]
 72%|#######2  | 564/781 [00:29<00:11, 19.18it/s]
 72%|#######2  | 566/781 [00:29<00:11, 19.14it/s]
 73%|#######2  | 568/781 [00:30<00:11, 19.12it/s]
 73%|#######2  | 570/781 [00:30<00:11, 19.11it/s]
 73%|#######3  | 572/781 [00:30<00:11, 18.92it/s]
 73%|#######3  | 574/781 [00:30<00:10, 18.83it/s]
 74%|#######3  | 576/781 [00:30<00:10, 18.79it/s]
 74%|#######4  | 578/781 [00:30<00:10, 18.75it/s]
 74%|#######4  | 580/781 [00:30<00:10, 18.72it/s]
 75%|#######4  | 582/781 [00:30<00:10, 18.70it/s]
 75%|#######4  | 584/781 [00:30<00:10, 18.67it/s]
 75%|#######5  | 586/781 [00:31<00:10, 18.70it/s]
 75%|#######5  | 588/781 [00:31<00:10, 18.64it/s]
 76%|#######5  | 590/781 [00:31<00:10, 18.65it/s]
 76%|#######5  | 592/781 [00:31<00:10, 18.64it/s]
 76%|#######6  | 594/781 [00:31<00:10, 18.69it/s]
 76%|#######6  | 596/781 [00:31<00:09, 18.69it/s]
 77%|#######6  | 598/781 [00:31<00:09, 18.69it/s]
 77%|#######6  | 600/781 [00:31<00:09, 18.67it/s]
 77%|#######7  | 602/781 [00:31<00:09, 18.70it/s]
 77%|#######7  | 604/781 [00:32<00:09, 18.73it/s]
 78%|#######7  | 606/781 [00:32<00:09, 18.88it/s]
 78%|#######7  | 608/781 [00:32<00:09, 18.92it/s]
 78%|#######8  | 610/781 [00:32<00:08, 19.02it/s]
 78%|#######8  | 612/781 [00:32<00:08, 19.10it/s]
 79%|#######8  | 614/781 [00:32<00:08, 19.18it/s]
 79%|#######8  | 616/781 [00:32<00:08, 19.23it/s]
 79%|#######9  | 618/781 [00:32<00:08, 19.10it/s]
 79%|#######9  | 620/781 [00:32<00:08, 19.02it/s]
 80%|#######9  | 622/781 [00:32<00:08, 18.95it/s]
 80%|#######9  | 624/781 [00:33<00:08, 19.05it/s]
 80%|########  | 626/781 [00:33<00:08, 19.04it/s]
 80%|########  | 628/781 [00:33<00:08, 19.04it/s]
 81%|########  | 630/781 [00:33<00:07, 19.14it/s]
 81%|########  | 632/781 [00:33<00:07, 19.10it/s]
 81%|########1 | 634/781 [00:33<00:07, 19.08it/s]
 81%|########1 | 636/781 [00:33<00:07, 18.75it/s]
 82%|########1 | 638/781 [00:33<00:07, 18.60it/s]
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100%|##########| 1/1 [00:06<00:00,  6.99s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:09, 15.55it/s]
  3%|2         | 4/157 [00:00<00:09, 16.28it/s]
  4%|3         | 6/157 [00:00<00:09, 16.35it/s]
  5%|5         | 8/157 [00:00<00:08, 17.08it/s]
  6%|6         | 10/157 [00:00<00:08, 17.22it/s]
  8%|7         | 12/157 [00:00<00:08, 16.77it/s]
  9%|8         | 14/157 [00:00<00:08, 16.84it/s]
 10%|#         | 16/157 [00:00<00:08, 17.15it/s]
 11%|#1        | 18/157 [00:01<00:08, 16.90it/s]
 13%|#2        | 20/157 [00:01<00:08, 16.98it/s]
 14%|#4        | 22/157 [00:01<00:07, 16.90it/s]
 15%|#5        | 24/157 [00:01<00:07, 17.30it/s]
 17%|#6        | 26/157 [00:01<00:07, 17.01it/s]
 18%|#7        | 28/157 [00:01<00:07, 16.84it/s]
 19%|#9        | 30/157 [00:01<00:07, 16.99it/s]
 20%|##        | 32/157 [00:01<00:07, 17.01it/s]
 22%|##1       | 34/157 [00:02<00:07, 16.87it/s]
 23%|##2       | 36/157 [00:02<00:07, 17.16it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.83it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.57it/s]
 27%|##6       | 42/157 [00:02<00:07, 16.37it/s]
 28%|##8       | 44/157 [00:02<00:06, 16.20it/s]
 29%|##9       | 46/157 [00:02<00:06, 16.11it/s]
 31%|###       | 48/157 [00:02<00:06, 16.07it/s]
 32%|###1      | 50/157 [00:03<00:06, 16.08it/s]
 33%|###3      | 52/157 [00:03<00:06, 16.13it/s]
 34%|###4      | 54/157 [00:03<00:06, 16.16it/s]
 36%|###5      | 56/157 [00:03<00:06, 16.16it/s]
 37%|###6      | 58/157 [00:03<00:06, 16.19it/s]
 38%|###8      | 60/157 [00:03<00:05, 16.21it/s]
 39%|###9      | 62/157 [00:03<00:05, 16.21it/s]
 41%|####      | 64/157 [00:03<00:05, 16.19it/s]
 42%|####2     | 66/157 [00:03<00:05, 16.20it/s]
 43%|####3     | 68/157 [00:04<00:05, 16.22it/s]
 45%|####4     | 70/157 [00:04<00:05, 16.19it/s]
 46%|####5     | 72/157 [00:04<00:05, 16.17it/s]
 47%|####7     | 74/157 [00:04<00:05, 16.05it/s]
 48%|####8     | 76/157 [00:04<00:05, 15.96it/s]
 50%|####9     | 78/157 [00:04<00:04, 15.91it/s]
 51%|#####     | 80/157 [00:04<00:04, 15.96it/s]
 52%|#####2    | 82/157 [00:04<00:04, 15.94it/s]
 54%|#####3    | 84/157 [00:05<00:04, 15.86it/s]
 55%|#####4    | 86/157 [00:05<00:04, 15.80it/s]
 56%|#####6    | 88/157 [00:05<00:04, 15.76it/s]
 57%|#####7    | 90/157 [00:05<00:04, 15.71it/s]
 59%|#####8    | 92/157 [00:05<00:04, 15.71it/s]
 60%|#####9    | 94/157 [00:05<00:03, 15.76it/s]
 61%|######1   | 96/157 [00:05<00:03, 15.73it/s]
 62%|######2   | 98/157 [00:06<00:03, 15.71it/s]
 64%|######3   | 100/157 [00:06<00:03, 15.73it/s]
 65%|######4   | 102/157 [00:06<00:03, 15.74it/s]
 66%|######6   | 104/157 [00:06<00:03, 15.77it/s]
 68%|######7   | 106/157 [00:06<00:03, 15.79it/s]
 69%|######8   | 108/157 [00:06<00:03, 15.83it/s]
 70%|#######   | 110/157 [00:06<00:02, 15.80it/s]
 71%|#######1  | 112/157 [00:06<00:02, 15.81it/s]
 73%|#######2  | 114/157 [00:07<00:02, 15.79it/s]
 74%|#######3  | 116/157 [00:07<00:02, 15.77it/s]
 75%|#######5  | 118/157 [00:07<00:02, 15.77it/s]
 76%|#######6  | 120/157 [00:07<00:02, 15.82it/s]
 78%|#######7  | 122/157 [00:07<00:02, 15.80it/s]
 79%|#######8  | 124/157 [00:07<00:02, 15.81it/s]
 80%|########  | 126/157 [00:07<00:01, 15.78it/s]
 82%|########1 | 128/157 [00:07<00:01, 15.78it/s]
 83%|########2 | 130/157 [00:08<00:01, 15.74it/s]
 84%|########4 | 132/157 [00:08<00:01, 15.75it/s]
 85%|########5 | 134/157 [00:08<00:01, 15.80it/s]
 87%|########6 | 136/157 [00:08<00:01, 15.73it/s]
 88%|########7 | 138/157 [00:08<00:01, 15.67it/s]
 89%|########9 | 140/157 [00:08<00:01, 15.68it/s]
 90%|######### | 142/157 [00:08<00:00, 15.73it/s]
 92%|#########1| 144/157 [00:08<00:00, 15.77it/s]
 93%|#########2| 146/157 [00:09<00:00, 15.76it/s]
 94%|#########4| 148/157 [00:09<00:00, 15.77it/s]
 96%|#########5| 150/157 [00:09<00:00, 15.75it/s]
 97%|#########6| 152/157 [00:09<00:00, 15.87it/s]
 98%|#########8| 154/157 [00:09<00:00, 15.99it/s]
 99%|#########9| 156/157 [00:09<00:00, 16.06it/s]
100%|##########| 157/157 [00:09<00:00, 16.18it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:42, 18.24it/s]
  1%|          | 4/781 [00:00<00:43, 17.99it/s]
  1%|          | 6/781 [00:00<00:43, 17.88it/s]
  1%|1         | 8/781 [00:00<00:43, 17.83it/s]
  1%|1         | 10/781 [00:00<00:43, 17.81it/s]
  2%|1         | 12/781 [00:00<00:43, 17.83it/s]
  2%|1         | 14/781 [00:00<00:43, 17.82it/s]
  2%|2         | 16/781 [00:00<00:42, 17.81it/s]
  2%|2         | 18/781 [00:01<00:42, 17.80it/s]
  3%|2         | 20/781 [00:01<00:42, 17.80it/s]
  3%|2         | 22/781 [00:01<00:42, 17.81it/s]
  3%|3         | 24/781 [00:01<00:42, 17.80it/s]
  3%|3         | 26/781 [00:01<00:42, 17.80it/s]
  4%|3         | 28/781 [00:01<00:42, 17.80it/s]
  4%|3         | 30/781 [00:01<00:42, 17.80it/s]
  4%|4         | 32/781 [00:01<00:42, 17.80it/s]
  4%|4         | 34/781 [00:01<00:42, 17.60it/s]
  5%|4         | 36/781 [00:02<00:42, 17.51it/s]
  5%|4         | 38/781 [00:02<00:42, 17.33it/s]
  5%|5         | 40/781 [00:02<00:42, 17.37it/s]
  5%|5         | 42/781 [00:02<00:42, 17.36it/s]
  6%|5         | 44/781 [00:02<00:42, 17.20it/s]
  6%|5         | 46/781 [00:02<00:42, 17.22it/s]
  6%|6         | 48/781 [00:02<00:42, 17.34it/s]
  6%|6         | 50/781 [00:02<00:41, 17.47it/s]
  7%|6         | 52/781 [00:02<00:41, 17.60it/s]
  7%|6         | 54/781 [00:03<00:41, 17.59it/s]
  7%|7         | 56/781 [00:03<00:41, 17.51it/s]
  7%|7         | 58/781 [00:03<00:41, 17.51it/s]
  8%|7         | 60/781 [00:03<00:41, 17.48it/s]
  8%|7         | 62/781 [00:03<00:40, 17.60it/s]
  8%|8         | 64/781 [00:03<00:40, 17.67it/s]
  8%|8         | 66/781 [00:03<00:40, 17.77it/s]
  9%|8         | 68/781 [00:03<00:39, 17.84it/s]
  9%|8         | 70/781 [00:03<00:39, 17.84it/s]
  9%|9         | 72/781 [00:04<00:39, 17.86it/s]
  9%|9         | 74/781 [00:04<00:39, 17.91it/s]
 10%|9         | 76/781 [00:04<00:39, 17.93it/s]
 10%|9         | 78/781 [00:04<00:39, 17.94it/s]
 10%|#         | 80/781 [00:04<00:39, 17.96it/s]
 10%|#         | 82/781 [00:04<00:38, 17.97it/s]
 11%|#         | 84/781 [00:04<00:38, 17.99it/s]
 11%|#1        | 86/781 [00:04<00:38, 17.84it/s]
 11%|#1        | 88/781 [00:04<00:39, 17.71it/s]
 12%|#1        | 90/781 [00:05<00:39, 17.62it/s]
 12%|#1        | 92/781 [00:05<00:38, 17.70it/s]
 12%|#2        | 94/781 [00:05<00:38, 17.77it/s]
 12%|#2        | 96/781 [00:05<00:38, 17.84it/s]
 13%|#2        | 98/781 [00:05<00:38, 17.89it/s]
 13%|#2        | 100/781 [00:05<00:38, 17.90it/s]
 13%|#3        | 102/781 [00:05<00:37, 17.93it/s]
 13%|#3        | 104/781 [00:05<00:37, 17.95it/s]
 14%|#3        | 106/781 [00:05<00:37, 17.95it/s]
 14%|#3        | 108/781 [00:06<00:37, 17.95it/s]
 14%|#4        | 110/781 [00:06<00:37, 17.95it/s]
 14%|#4        | 112/781 [00:06<00:37, 17.96it/s]
 15%|#4        | 114/781 [00:06<00:37, 17.97it/s]
 15%|#4        | 116/781 [00:06<00:37, 17.96it/s]
 15%|#5        | 118/781 [00:06<00:36, 17.95it/s]
 15%|#5        | 120/781 [00:06<00:36, 17.96it/s]
 16%|#5        | 122/781 [00:06<00:36, 17.97it/s]
 16%|#5        | 124/781 [00:06<00:36, 17.95it/s]
 16%|#6        | 126/781 [00:07<00:36, 17.95it/s]
 16%|#6        | 128/781 [00:07<00:36, 17.97it/s]
 17%|#6        | 130/781 [00:07<00:36, 17.95it/s]
 17%|#6        | 132/781 [00:07<00:36, 17.94it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.93it/s]
 17%|#7        | 136/781 [00:07<00:35, 17.94it/s]
 18%|#7        | 138/781 [00:07<00:35, 17.97it/s]
 18%|#7        | 140/781 [00:07<00:35, 17.95it/s]
 18%|#8        | 142/781 [00:07<00:35, 17.95it/s]
 18%|#8        | 144/781 [00:08<00:35, 17.94it/s]
 19%|#8        | 146/781 [00:08<00:35, 17.96it/s]
 19%|#8        | 148/781 [00:08<00:35, 17.97it/s]
 19%|#9        | 150/781 [00:08<00:35, 17.99it/s]
 19%|#9        | 152/781 [00:08<00:35, 17.92it/s]
 20%|#9        | 154/781 [00:08<00:35, 17.80it/s]
 20%|#9        | 156/781 [00:08<00:35, 17.83it/s]
 20%|##        | 158/781 [00:08<00:34, 17.84it/s]
 20%|##        | 160/781 [00:08<00:34, 17.86it/s]
 21%|##        | 162/781 [00:09<00:34, 17.90it/s]
 21%|##        | 164/781 [00:09<00:34, 17.65it/s]
 21%|##1       | 166/781 [00:09<00:34, 17.75it/s]
 22%|##1       | 168/781 [00:09<00:34, 17.80it/s]
 22%|##1       | 170/781 [00:09<00:34, 17.84it/s]
 22%|##2       | 172/781 [00:09<00:34, 17.86it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.88it/s]
 23%|##2       | 176/781 [00:09<00:33, 17.88it/s]
 23%|##2       | 178/781 [00:09<00:33, 17.90it/s]
 23%|##3       | 180/781 [00:10<00:33, 17.89it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.90it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.90it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.81it/s]
 24%|##4       | 188/781 [00:10<00:33, 17.70it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.71it/s]
 25%|##4       | 192/781 [00:10<00:33, 17.76it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.82it/s]
 25%|##5       | 196/781 [00:11<00:32, 17.85it/s]
 25%|##5       | 198/781 [00:11<00:32, 17.87it/s]
 26%|##5       | 200/781 [00:11<00:32, 17.89it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.92it/s]
 26%|##6       | 204/781 [00:11<00:32, 17.92it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.88it/s]
 27%|##6       | 208/781 [00:11<00:32, 17.74it/s]
 27%|##6       | 210/781 [00:11<00:32, 17.62it/s]
 27%|##7       | 212/781 [00:11<00:32, 17.53it/s]
 27%|##7       | 214/781 [00:12<00:32, 17.51it/s]
 28%|##7       | 216/781 [00:12<00:32, 17.57it/s]
 28%|##7       | 218/781 [00:12<00:32, 17.53it/s]
 28%|##8       | 220/781 [00:12<00:31, 17.60it/s]
 28%|##8       | 222/781 [00:12<00:31, 17.63it/s]
 29%|##8       | 224/781 [00:12<00:31, 17.61it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.67it/s]
 29%|##9       | 228/781 [00:12<00:31, 17.73it/s]
 29%|##9       | 230/781 [00:12<00:31, 17.63it/s]
 30%|##9       | 232/781 [00:13<00:31, 17.68it/s]
 30%|##9       | 234/781 [00:13<00:31, 17.61it/s]
 30%|###       | 236/781 [00:13<00:30, 17.65it/s]
 30%|###       | 238/781 [00:13<00:30, 17.72it/s]
 31%|###       | 240/781 [00:13<00:30, 17.75it/s]
 31%|###       | 242/781 [00:13<00:30, 17.78it/s]
 31%|###1      | 244/781 [00:13<00:30, 17.80it/s]
 31%|###1      | 246/781 [00:13<00:30, 17.83it/s]
 32%|###1      | 248/781 [00:13<00:29, 17.85it/s]
 32%|###2      | 250/781 [00:14<00:29, 17.87it/s]
 32%|###2      | 252/781 [00:14<00:29, 17.85it/s]
 33%|###2      | 254/781 [00:14<00:29, 17.85it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.87it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.85it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.86it/s]
 34%|###3      | 262/781 [00:14<00:29, 17.86it/s]
 34%|###3      | 264/781 [00:14<00:28, 17.86it/s]
 34%|###4      | 266/781 [00:14<00:28, 17.83it/s]
 34%|###4      | 268/781 [00:15<00:28, 17.76it/s]
 35%|###4      | 270/781 [00:15<00:28, 17.65it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.61it/s]
 35%|###5      | 274/781 [00:15<00:28, 17.57it/s]
 35%|###5      | 276/781 [00:15<00:28, 17.61it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.62it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.66it/s]
 36%|###6      | 282/781 [00:15<00:28, 17.64it/s]
 36%|###6      | 284/781 [00:15<00:28, 17.58it/s]
 37%|###6      | 286/781 [00:16<00:28, 17.52it/s]
 37%|###6      | 288/781 [00:16<00:28, 17.49it/s]
 37%|###7      | 290/781 [00:16<00:28, 17.49it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.47it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.45it/s]
 38%|###7      | 296/781 [00:16<00:27, 17.48it/s]
 38%|###8      | 298/781 [00:16<00:27, 17.47it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.47it/s]
 39%|###8      | 302/781 [00:17<00:27, 17.30it/s]
 39%|###8      | 304/781 [00:17<00:27, 17.45it/s]
 39%|###9      | 306/781 [00:17<00:26, 17.61it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.61it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.57it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.55it/s]
 40%|####      | 314/781 [00:17<00:26, 17.66it/s]
 40%|####      | 316/781 [00:17<00:26, 17.73it/s]
 41%|####      | 318/781 [00:17<00:26, 17.80it/s]
 41%|####      | 320/781 [00:18<00:25, 17.85it/s]
 41%|####1     | 322/781 [00:18<00:25, 17.80it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.83it/s]
 42%|####1     | 326/781 [00:18<00:25, 17.87it/s]
 42%|####1     | 328/781 [00:18<00:25, 17.85it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.88it/s]
 43%|####2     | 332/781 [00:18<00:25, 17.85it/s]
 43%|####2     | 334/781 [00:18<00:25, 17.86it/s]
 43%|####3     | 336/781 [00:18<00:24, 17.88it/s]
 43%|####3     | 338/781 [00:19<00:24, 17.91it/s]
 44%|####3     | 340/781 [00:19<00:24, 17.92it/s]
 44%|####3     | 342/781 [00:19<00:24, 17.92it/s]
 44%|####4     | 344/781 [00:19<00:24, 17.92it/s]
 44%|####4     | 346/781 [00:19<00:24, 17.89it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.89it/s]
 45%|####4     | 350/781 [00:19<00:24, 17.91it/s]
 45%|####5     | 352/781 [00:19<00:24, 17.86it/s]
 45%|####5     | 354/781 [00:19<00:23, 17.88it/s]
 46%|####5     | 356/781 [00:20<00:23, 17.86it/s]
 46%|####5     | 358/781 [00:20<00:23, 17.84it/s]
 46%|####6     | 360/781 [00:20<00:23, 17.84it/s]
 46%|####6     | 362/781 [00:20<00:23, 17.88it/s]
 47%|####6     | 364/781 [00:20<00:23, 17.90it/s]
 47%|####6     | 366/781 [00:20<00:23, 17.91it/s]
 47%|####7     | 368/781 [00:20<00:23, 17.95it/s]
 47%|####7     | 370/781 [00:20<00:22, 17.96it/s]
 48%|####7     | 372/781 [00:20<00:22, 17.90it/s]
 48%|####7     | 374/781 [00:21<00:22, 17.89it/s]
 48%|####8     | 376/781 [00:21<00:22, 17.89it/s]
 48%|####8     | 378/781 [00:21<00:22, 17.89it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.89it/s]
 49%|####8     | 382/781 [00:21<00:22, 17.90it/s]
 49%|####9     | 384/781 [00:21<00:22, 17.95it/s]
 49%|####9     | 386/781 [00:21<00:21, 17.96it/s]
 50%|####9     | 388/781 [00:21<00:21, 17.94it/s]
 50%|####9     | 390/781 [00:21<00:22, 17.74it/s]
 50%|#####     | 392/781 [00:22<00:21, 17.77it/s]
 50%|#####     | 394/781 [00:22<00:21, 17.74it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.78it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.73it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.55it/s]
 51%|#####1    | 402/781 [00:22<00:21, 17.45it/s]
 52%|#####1    | 404/781 [00:22<00:21, 17.46it/s]
 52%|#####1    | 406/781 [00:22<00:21, 17.60it/s]
 52%|#####2    | 408/781 [00:22<00:21, 17.71it/s]
 52%|#####2    | 410/781 [00:23<00:21, 17.61it/s]
 53%|#####2    | 412/781 [00:23<00:20, 17.70it/s]
 53%|#####3    | 414/781 [00:23<00:20, 17.64it/s]
 53%|#####3    | 416/781 [00:23<00:20, 17.64it/s]
 54%|#####3    | 418/781 [00:23<00:20, 17.57it/s]
 54%|#####3    | 420/781 [00:23<00:20, 17.62it/s]
 54%|#####4    | 422/781 [00:23<00:20, 17.65it/s]
 54%|#####4    | 424/781 [00:23<00:20, 17.69it/s]
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100%|##########| 781/781 [00:43<00:00, 18.12it/s]




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Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:17,  1.12s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:17,  1.12s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.09s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.09s/it]
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Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.09s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.11s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
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Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
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Validation Progress:  75%|#######5  | 33/44 [00:35<00:11,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.16s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.16s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.16s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.15s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.15s/it]
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Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:07<00:00,  7.61s/it]
100%|##########| 1/1 [00:07<00:00,  7.61s/it]

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100%|##########| 157/157 [00:08<00:00, 17.94it/s]

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100%|#########9| 779/781 [00:39<00:00, 20.75it/s]
100%|##########| 781/781 [00:39<00:00, 19.69it/s]




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Validation Progress:  55%|#####4    | 24/44 [00:25<00:22,  1.13s/it]
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Validation Progress:  55%|#####4    | 24/44 [00:25<00:22,  1.12s/it]
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Validation Progress:  57%|#####6    | 25/44 [00:26<00:21,  1.13s/it]
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Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.12s/it]
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Validation Progress:  61%|######1   | 27/44 [00:29<00:19,  1.14s/it]
Validation Progress:  61%|######1   | 27/44 [00:29<00:19,  1.14s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:18,  1.13s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:18,  1.13s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.11s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.11s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.13s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.13s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
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Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.10s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
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Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.19s/it]
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Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.19s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
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Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.16s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
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Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
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Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]

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100%|##########| 1/1 [00:08<00:00,  8.43s/it]

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 24%|##3       | 185/781 [00:10<00:33, 18.06it/s]
 24%|##3       | 187/781 [00:10<00:32, 18.17it/s]
 24%|##4       | 189/781 [00:10<00:32, 18.15it/s]
 24%|##4       | 191/781 [00:10<00:32, 18.01it/s]
 25%|##4       | 193/781 [00:10<00:32, 18.05it/s]
 25%|##4       | 195/781 [00:10<00:32, 17.99it/s]
 25%|##5       | 197/781 [00:11<00:32, 17.95it/s]
 25%|##5       | 199/781 [00:11<00:32, 18.03it/s]
 26%|##5       | 201/781 [00:11<00:32, 18.10it/s]
 26%|##5       | 203/781 [00:11<00:31, 18.07it/s]
 26%|##6       | 205/781 [00:11<00:31, 18.05it/s]
 27%|##6       | 207/781 [00:11<00:31, 18.12it/s]
 27%|##6       | 209/781 [00:11<00:31, 18.12it/s]
 27%|##7       | 211/781 [00:11<00:31, 18.17it/s]
 27%|##7       | 213/781 [00:11<00:31, 18.22it/s]
 28%|##7       | 215/781 [00:12<00:30, 18.28it/s]
 28%|##7       | 217/781 [00:12<00:30, 18.22it/s]
 28%|##8       | 219/781 [00:12<00:30, 18.23it/s]
 28%|##8       | 221/781 [00:12<00:30, 18.21it/s]
 29%|##8       | 223/781 [00:12<00:30, 18.04it/s]
 29%|##8       | 225/781 [00:12<00:30, 18.00it/s]
 29%|##9       | 227/781 [00:12<00:30, 17.92it/s]
 29%|##9       | 229/781 [00:12<00:30, 17.91it/s]
 30%|##9       | 231/781 [00:12<00:30, 17.98it/s]
 30%|##9       | 233/781 [00:13<00:30, 18.07it/s]
 30%|###       | 235/781 [00:13<00:30, 17.86it/s]
 30%|###       | 237/781 [00:13<00:30, 17.82it/s]
 31%|###       | 239/781 [00:13<00:30, 17.79it/s]
 31%|###       | 241/781 [00:13<00:30, 17.65it/s]
 31%|###1      | 243/781 [00:13<00:30, 17.69it/s]
 31%|###1      | 245/781 [00:13<00:30, 17.70it/s]
 32%|###1      | 247/781 [00:13<00:30, 17.72it/s]
 32%|###1      | 249/781 [00:13<00:29, 17.84it/s]
 32%|###2      | 251/781 [00:14<00:30, 17.64it/s]
 32%|###2      | 253/781 [00:14<00:29, 17.61it/s]
 33%|###2      | 255/781 [00:14<00:29, 17.55it/s]
 33%|###2      | 257/781 [00:14<00:29, 17.59it/s]
 33%|###3      | 259/781 [00:14<00:29, 17.70it/s]
 33%|###3      | 261/781 [00:14<00:29, 17.80it/s]
 34%|###3      | 263/781 [00:14<00:28, 17.96it/s]
 34%|###3      | 265/781 [00:14<00:28, 17.97it/s]
 34%|###4      | 267/781 [00:14<00:28, 17.98it/s]
 34%|###4      | 269/781 [00:15<00:28, 18.04it/s]
 35%|###4      | 271/781 [00:15<00:28, 18.00it/s]
 35%|###4      | 273/781 [00:15<00:28, 18.07it/s]
 35%|###5      | 275/781 [00:15<00:27, 18.09it/s]
 35%|###5      | 277/781 [00:15<00:27, 18.13it/s]
 36%|###5      | 279/781 [00:15<00:27, 18.14it/s]
 36%|###5      | 281/781 [00:15<00:27, 18.19it/s]
 36%|###6      | 283/781 [00:15<00:27, 18.22it/s]
 36%|###6      | 285/781 [00:15<00:27, 18.24it/s]
 37%|###6      | 287/781 [00:16<00:27, 17.91it/s]
 37%|###7      | 289/781 [00:16<00:27, 17.98it/s]
 37%|###7      | 291/781 [00:16<00:27, 18.07it/s]
 38%|###7      | 293/781 [00:16<00:26, 18.13it/s]
 38%|###7      | 295/781 [00:16<00:26, 18.14it/s]
 38%|###8      | 297/781 [00:16<00:26, 18.16it/s]
 38%|###8      | 299/781 [00:16<00:26, 18.08it/s]
 39%|###8      | 301/781 [00:16<00:26, 18.09it/s]
 39%|###8      | 303/781 [00:16<00:26, 18.09it/s]
 39%|###9      | 305/781 [00:17<00:26, 17.77it/s]
 39%|###9      | 307/781 [00:17<00:26, 17.60it/s]
 40%|###9      | 309/781 [00:17<00:26, 17.55it/s]
 40%|###9      | 311/781 [00:17<00:26, 17.92it/s]
 40%|####      | 313/781 [00:17<00:25, 18.20it/s]
 40%|####      | 315/781 [00:17<00:25, 18.42it/s]
 41%|####      | 317/781 [00:17<00:25, 18.43it/s]
 41%|####      | 319/781 [00:17<00:24, 18.56it/s]
 41%|####1     | 321/781 [00:17<00:25, 18.20it/s]
 41%|####1     | 323/781 [00:18<00:25, 18.12it/s]
 42%|####1     | 325/781 [00:18<00:25, 18.12it/s]
 42%|####1     | 327/781 [00:18<00:25, 17.67it/s]
 42%|####2     | 329/781 [00:18<00:24, 18.26it/s]
 42%|####2     | 331/781 [00:18<00:24, 18.37it/s]
 43%|####2     | 333/781 [00:18<00:24, 18.18it/s]
 43%|####2     | 335/781 [00:18<00:24, 18.17it/s]
 43%|####3     | 337/781 [00:18<00:24, 18.42it/s]
 43%|####3     | 339/781 [00:18<00:24, 18.30it/s]
 44%|####3     | 341/781 [00:19<00:24, 17.93it/s]
 44%|####3     | 343/781 [00:19<00:24, 17.61it/s]
 44%|####4     | 345/781 [00:19<00:24, 17.50it/s]
 44%|####4     | 347/781 [00:19<00:24, 17.61it/s]
 45%|####4     | 349/781 [00:19<00:24, 17.72it/s]
 45%|####4     | 351/781 [00:19<00:24, 17.79it/s]
 45%|####5     | 353/781 [00:19<00:24, 17.80it/s]
 45%|####5     | 355/781 [00:19<00:24, 17.69it/s]
 46%|####5     | 357/781 [00:19<00:23, 17.76it/s]
 46%|####5     | 359/781 [00:20<00:23, 17.88it/s]
 46%|####6     | 361/781 [00:20<00:23, 17.83it/s]
 46%|####6     | 363/781 [00:20<00:23, 17.92it/s]
 47%|####6     | 365/781 [00:20<00:23, 17.76it/s]
 47%|####6     | 367/781 [00:20<00:23, 17.79it/s]
 47%|####7     | 369/781 [00:20<00:23, 17.61it/s]
 48%|####7     | 371/781 [00:20<00:23, 17.72it/s]
 48%|####7     | 373/781 [00:20<00:22, 17.78it/s]
 48%|####8     | 375/781 [00:20<00:22, 17.82it/s]
 48%|####8     | 377/781 [00:21<00:22, 17.92it/s]
 49%|####8     | 379/781 [00:21<00:22, 18.01it/s]
 49%|####8     | 381/781 [00:21<00:22, 18.10it/s]
 49%|####9     | 383/781 [00:21<00:22, 18.06it/s]
 49%|####9     | 385/781 [00:21<00:21, 18.05it/s]
 50%|####9     | 387/781 [00:21<00:21, 18.11it/s]
 50%|####9     | 389/781 [00:21<00:21, 18.10it/s]
 50%|#####     | 391/781 [00:21<00:21, 17.93it/s]
 50%|#####     | 393/781 [00:21<00:21, 18.00it/s]
 51%|#####     | 395/781 [00:22<00:21, 18.00it/s]
 51%|#####     | 397/781 [00:22<00:21, 18.12it/s]
 51%|#####1    | 399/781 [00:22<00:21, 18.15it/s]
 51%|#####1    | 401/781 [00:22<00:20, 18.21it/s]
 52%|#####1    | 403/781 [00:22<00:20, 18.21it/s]
 52%|#####1    | 405/781 [00:22<00:20, 18.25it/s]
 52%|#####2    | 407/781 [00:22<00:20, 18.29it/s]
 52%|#####2    | 409/781 [00:22<00:20, 18.25it/s]
 53%|#####2    | 411/781 [00:22<00:20, 18.21it/s]
 53%|#####2    | 413/781 [00:23<00:20, 17.92it/s]
 53%|#####3    | 415/781 [00:23<00:20, 17.90it/s]
 53%|#####3    | 417/781 [00:23<00:20, 17.85it/s]
 54%|#####3    | 419/781 [00:23<00:20, 17.94it/s]
 54%|#####3    | 421/781 [00:23<00:20, 17.98it/s]
 54%|#####4    | 423/781 [00:23<00:19, 18.05it/s]
 54%|#####4    | 425/781 [00:23<00:19, 18.01it/s]
 55%|#####4    | 427/781 [00:23<00:19, 17.93it/s]
 55%|#####4    | 429/781 [00:23<00:19, 17.99it/s]
 55%|#####5    | 431/781 [00:24<00:19, 17.90it/s]
 55%|#####5    | 433/781 [00:24<00:19, 17.92it/s]
 56%|#####5    | 435/781 [00:24<00:19, 17.93it/s]
 56%|#####5    | 437/781 [00:24<00:19, 17.90it/s]
 56%|#####6    | 439/781 [00:24<00:18, 18.02it/s]
 56%|#####6    | 441/781 [00:24<00:18, 17.98it/s]
 57%|#####6    | 443/781 [00:24<00:18, 17.95it/s]
 57%|#####6    | 445/781 [00:24<00:18, 17.76it/s]
 57%|#####7    | 447/781 [00:24<00:18, 17.86it/s]
 57%|#####7    | 449/781 [00:25<00:18, 17.96it/s]
 58%|#####7    | 451/781 [00:25<00:19, 17.16it/s]
 58%|#####8    | 453/781 [00:25<00:18, 17.30it/s]
 58%|#####8    | 455/781 [00:25<00:18, 17.28it/s]
 59%|#####8    | 457/781 [00:25<00:18, 17.46it/s]
 59%|#####8    | 459/781 [00:25<00:18, 17.63it/s]
 59%|#####9    | 461/781 [00:25<00:17, 17.81it/s]
 59%|#####9    | 463/781 [00:25<00:17, 17.67it/s]
 60%|#####9    | 465/781 [00:25<00:17, 17.85it/s]
 60%|#####9    | 467/781 [00:26<00:17, 17.76it/s]
 60%|######    | 469/781 [00:26<00:17, 17.81it/s]
 60%|######    | 471/781 [00:26<00:17, 17.70it/s]
 61%|######    | 473/781 [00:26<00:17, 17.74it/s]
 61%|######    | 475/781 [00:26<00:17, 17.75it/s]
 61%|######1   | 477/781 [00:26<00:17, 17.79it/s]
 61%|######1   | 479/781 [00:26<00:16, 17.94it/s]
 62%|######1   | 481/781 [00:26<00:16, 17.92it/s]
 62%|######1   | 483/781 [00:26<00:16, 17.94it/s]
 62%|######2   | 485/781 [00:27<00:16, 18.01it/s]
 62%|######2   | 487/781 [00:27<00:16, 18.09it/s]
 63%|######2   | 489/781 [00:27<00:16, 17.61it/s]
 63%|######2   | 491/781 [00:27<00:16, 17.65it/s]
 63%|######3   | 493/781 [00:27<00:16, 17.77it/s]
 63%|######3   | 495/781 [00:27<00:15, 17.90it/s]
 64%|######3   | 497/781 [00:27<00:15, 17.80it/s]
 64%|######3   | 499/781 [00:27<00:15, 18.04it/s]
 64%|######4   | 501/781 [00:27<00:15, 17.99it/s]
 64%|######4   | 503/781 [00:28<00:15, 17.86it/s]
 65%|######4   | 505/781 [00:28<00:15, 17.90it/s]
 65%|######4   | 507/781 [00:28<00:15, 17.83it/s]
 65%|######5   | 509/781 [00:28<00:15, 17.91it/s]
 65%|######5   | 511/781 [00:28<00:15, 17.93it/s]
 66%|######5   | 513/781 [00:28<00:14, 17.94it/s]
 66%|######5   | 515/781 [00:28<00:14, 17.88it/s]
 66%|######6   | 517/781 [00:28<00:14, 18.05it/s]
 66%|######6   | 519/781 [00:28<00:14, 18.49it/s]
 67%|######6   | 522/781 [00:29<00:13, 19.09it/s]
 67%|######7   | 524/781 [00:29<00:13, 18.93it/s]
 67%|######7   | 526/781 [00:29<00:13, 19.09it/s]
 68%|######7   | 528/781 [00:29<00:13, 19.20it/s]
 68%|######7   | 530/781 [00:29<00:13, 19.27it/s]
 68%|######8   | 532/781 [00:29<00:12, 19.46it/s]
 68%|######8   | 534/781 [00:29<00:12, 19.38it/s]
 69%|######8   | 536/781 [00:29<00:12, 19.48it/s]
 69%|######9   | 539/781 [00:29<00:12, 19.86it/s]
 69%|######9   | 542/781 [00:30<00:11, 20.08it/s]
 70%|######9   | 545/781 [00:30<00:11, 20.21it/s]
 70%|#######   | 548/781 [00:30<00:11, 20.21it/s]
 71%|#######   | 551/781 [00:30<00:11, 20.29it/s]
 71%|#######   | 554/781 [00:30<00:11, 20.32it/s]
 71%|#######1  | 557/781 [00:30<00:11, 20.17it/s]
 72%|#######1  | 560/781 [00:31<00:10, 20.09it/s]
 72%|#######2  | 563/781 [00:31<00:10, 20.02it/s]
 72%|#######2  | 566/781 [00:31<00:10, 20.10it/s]
 73%|#######2  | 569/781 [00:31<00:10, 20.22it/s]
 73%|#######3  | 572/781 [00:31<00:10, 20.37it/s]
 74%|#######3  | 575/781 [00:31<00:10, 20.51it/s]
 74%|#######4  | 578/781 [00:31<00:09, 20.46it/s]
 74%|#######4  | 581/781 [00:32<00:09, 20.35it/s]
 75%|#######4  | 584/781 [00:32<00:09, 20.45it/s]
 75%|#######5  | 587/781 [00:32<00:09, 20.50it/s]
 76%|#######5  | 590/781 [00:32<00:09, 20.56it/s]
 76%|#######5  | 593/781 [00:32<00:09, 20.11it/s]
 76%|#######6  | 596/781 [00:32<00:09, 20.24it/s]
 77%|#######6  | 599/781 [00:32<00:09, 20.07it/s]
 77%|#######7  | 602/781 [00:33<00:08, 20.02it/s]
 77%|#######7  | 605/781 [00:33<00:08, 19.99it/s]
 78%|#######7  | 608/781 [00:33<00:08, 19.97it/s]
 78%|#######8  | 610/781 [00:33<00:08, 19.85it/s]
 78%|#######8  | 613/781 [00:33<00:08, 19.98it/s]
 79%|#######8  | 616/781 [00:33<00:08, 20.13it/s]
 79%|#######9  | 619/781 [00:33<00:07, 20.28it/s]
 80%|#######9  | 622/781 [00:34<00:07, 20.17it/s]
 80%|########  | 625/781 [00:34<00:07, 20.31it/s]
 80%|########  | 628/781 [00:34<00:07, 20.35it/s]
 81%|########  | 631/781 [00:34<00:07, 20.43it/s]
 81%|########1 | 634/781 [00:34<00:07, 20.47it/s]
 82%|########1 | 637/781 [00:34<00:07, 20.49it/s]
 82%|########1 | 640/781 [00:34<00:06, 20.40it/s]
 82%|########2 | 643/781 [00:35<00:06, 20.25it/s]
 83%|########2 | 646/781 [00:35<00:06, 20.33it/s]
 83%|########3 | 649/781 [00:35<00:06, 20.21it/s]
 83%|########3 | 652/781 [00:35<00:06, 20.16it/s]
 84%|########3 | 655/781 [00:35<00:06, 19.91it/s]
 84%|########4 | 657/781 [00:35<00:06, 19.92it/s]
 84%|########4 | 659/781 [00:35<00:06, 19.81it/s]
 85%|########4 | 661/781 [00:36<00:06, 19.61it/s]
 85%|########5 | 664/781 [00:36<00:05, 19.88it/s]
 85%|########5 | 667/781 [00:36<00:05, 20.08it/s]
 86%|########5 | 670/781 [00:36<00:05, 20.17it/s]
 86%|########6 | 673/781 [00:36<00:05, 20.30it/s]
 87%|########6 | 676/781 [00:36<00:05, 20.41it/s]
 87%|########6 | 679/781 [00:36<00:05, 20.31it/s]
 87%|########7 | 682/781 [00:37<00:04, 20.34it/s]
 88%|########7 | 685/781 [00:37<00:04, 20.36it/s]
 88%|########8 | 688/781 [00:37<00:04, 20.17it/s]
 88%|########8 | 691/781 [00:37<00:04, 20.14it/s]
 89%|########8 | 694/781 [00:37<00:04, 20.26it/s]
 89%|########9 | 697/781 [00:37<00:04, 20.16it/s]
 90%|########9 | 700/781 [00:37<00:04, 20.08it/s]
 90%|######### | 703/781 [00:38<00:03, 20.05it/s]
 90%|######### | 706/781 [00:38<00:03, 19.66it/s]
 91%|######### | 708/781 [00:38<00:03, 19.33it/s]
 91%|#########1| 711/781 [00:38<00:03, 19.68it/s]
 91%|#########1| 714/781 [00:38<00:03, 19.80it/s]
 92%|#########1| 717/781 [00:38<00:03, 20.03it/s]
 92%|#########2| 720/781 [00:38<00:03, 20.02it/s]
 92%|#########2| 722/781 [00:39<00:03, 19.65it/s]
 93%|#########2| 724/781 [00:39<00:02, 19.71it/s]
 93%|#########3| 727/781 [00:39<00:02, 19.90it/s]
 93%|#########3| 730/781 [00:39<00:02, 20.09it/s]
 94%|#########3| 733/781 [00:39<00:02, 20.28it/s]
 94%|#########4| 736/781 [00:39<00:02, 20.37it/s]
 95%|#########4| 739/781 [00:39<00:02, 20.33it/s]
 95%|#########5| 742/781 [00:40<00:01, 20.30it/s]
 95%|#########5| 745/781 [00:40<00:01, 19.99it/s]
 96%|#########5| 747/781 [00:40<00:01, 19.60it/s]
 96%|#########6| 750/781 [00:40<00:01, 19.92it/s]
 96%|#########6| 753/781 [00:40<00:01, 20.06it/s]
 97%|#########6| 756/781 [00:40<00:01, 19.93it/s]
 97%|#########7| 758/781 [00:40<00:01, 19.69it/s]
 97%|#########7| 761/781 [00:41<00:01, 19.64it/s]
 98%|#########7| 763/781 [00:41<00:00, 19.65it/s]
 98%|#########7| 765/781 [00:41<00:00, 19.63it/s]
 98%|#########8| 768/781 [00:41<00:00, 19.91it/s]
 99%|#########8| 770/781 [00:41<00:00, 19.83it/s]
 99%|#########8| 772/781 [00:41<00:00, 19.85it/s]
 99%|#########9| 775/781 [00:41<00:00, 20.10it/s]
100%|#########9| 778/781 [00:41<00:00, 20.25it/s]
100%|##########| 781/781 [00:42<00:00, 20.40it/s]
100%|##########| 781/781 [00:42<00:00, 18.59it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.05it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.00it/s]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.01s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.01s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.03s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.00it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.00it/s]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.00s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.00s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.03s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:37,  1.01it/s]
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Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
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  5%|4         | 38/781 [00:02<00:41, 17.88it/s]
  5%|5         | 40/781 [00:02<00:41, 17.88it/s]
  5%|5         | 42/781 [00:02<00:41, 18.00it/s]
  6%|5         | 44/781 [00:02<00:40, 18.01it/s]
  6%|5         | 46/781 [00:02<00:40, 18.01it/s]
  6%|6         | 48/781 [00:02<00:40, 17.92it/s]
  6%|6         | 50/781 [00:02<00:40, 18.03it/s]
  7%|6         | 52/781 [00:02<00:40, 18.07it/s]
  7%|6         | 54/781 [00:03<00:40, 17.98it/s]
  7%|7         | 56/781 [00:03<00:40, 17.88it/s]
  7%|7         | 58/781 [00:03<00:40, 17.64it/s]
  8%|7         | 60/781 [00:03<00:40, 17.73it/s]
  8%|7         | 62/781 [00:03<00:40, 17.78it/s]
  8%|8         | 64/781 [00:03<00:40, 17.52it/s]
  8%|8         | 66/781 [00:03<00:40, 17.77it/s]
  9%|8         | 68/781 [00:03<00:40, 17.81it/s]
  9%|8         | 70/781 [00:03<00:39, 18.09it/s]
  9%|9         | 72/781 [00:04<00:38, 18.44it/s]
  9%|9         | 74/781 [00:04<00:37, 18.66it/s]
 10%|9         | 76/781 [00:04<00:37, 18.84it/s]
 10%|9         | 78/781 [00:04<00:37, 18.96it/s]
 10%|#         | 80/781 [00:04<00:38, 18.38it/s]
 10%|#         | 82/781 [00:04<00:37, 18.57it/s]
 11%|#         | 84/781 [00:04<00:37, 18.80it/s]
 11%|#1        | 86/781 [00:04<00:36, 18.85it/s]
 11%|#1        | 88/781 [00:04<00:36, 18.92it/s]
 12%|#1        | 90/781 [00:04<00:36, 18.88it/s]
 12%|#1        | 92/781 [00:05<00:36, 19.04it/s]
 12%|#2        | 94/781 [00:05<00:36, 19.03it/s]
 12%|#2        | 96/781 [00:05<00:35, 19.14it/s]
 13%|#2        | 98/781 [00:05<00:35, 19.26it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.17it/s]
 13%|#3        | 102/781 [00:05<00:35, 19.11it/s]
 13%|#3        | 104/781 [00:05<00:35, 19.13it/s]
 14%|#3        | 106/781 [00:05<00:35, 19.19it/s]
 14%|#3        | 108/781 [00:05<00:34, 19.26it/s]
 14%|#4        | 110/781 [00:06<00:34, 19.31it/s]
 14%|#4        | 112/781 [00:06<00:34, 19.24it/s]
 15%|#4        | 114/781 [00:06<00:34, 19.17it/s]
 15%|#4        | 116/781 [00:06<00:34, 19.19it/s]
 15%|#5        | 118/781 [00:06<00:34, 19.12it/s]
 15%|#5        | 120/781 [00:06<00:34, 19.20it/s]
 16%|#5        | 122/781 [00:06<00:34, 19.26it/s]
 16%|#5        | 124/781 [00:06<00:34, 19.24it/s]
 16%|#6        | 126/781 [00:06<00:34, 18.79it/s]
 16%|#6        | 128/781 [00:06<00:34, 18.86it/s]
 17%|#6        | 130/781 [00:07<00:34, 18.93it/s]
 17%|#6        | 132/781 [00:07<00:34, 18.77it/s]
 17%|#7        | 134/781 [00:07<00:34, 18.77it/s]
 17%|#7        | 136/781 [00:07<00:34, 18.67it/s]
 18%|#7        | 138/781 [00:07<00:34, 18.66it/s]
 18%|#7        | 140/781 [00:07<00:34, 18.76it/s]
 18%|#8        | 142/781 [00:07<00:33, 18.92it/s]
 18%|#8        | 144/781 [00:07<00:33, 19.01it/s]
 19%|#8        | 146/781 [00:07<00:33, 18.92it/s]
 19%|#8        | 148/781 [00:08<00:33, 19.01it/s]
 19%|#9        | 150/781 [00:08<00:33, 18.76it/s]
 19%|#9        | 152/781 [00:08<00:33, 18.82it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.83it/s]
 20%|#9        | 156/781 [00:08<00:32, 18.97it/s]
 20%|##        | 158/781 [00:08<00:32, 19.03it/s]
 20%|##        | 160/781 [00:08<00:32, 18.98it/s]
 21%|##        | 162/781 [00:08<00:32, 19.06it/s]
 21%|##        | 164/781 [00:08<00:32, 18.85it/s]
 21%|##1       | 166/781 [00:08<00:32, 18.84it/s]
 22%|##1       | 168/781 [00:09<00:33, 18.54it/s]
 22%|##1       | 170/781 [00:09<00:32, 18.55it/s]
 22%|##2       | 172/781 [00:09<00:32, 18.62it/s]
 22%|##2       | 174/781 [00:09<00:32, 18.80it/s]
 23%|##2       | 176/781 [00:09<00:32, 18.83it/s]
 23%|##2       | 178/781 [00:09<00:32, 18.82it/s]
 23%|##3       | 180/781 [00:09<00:32, 18.75it/s]
 23%|##3       | 182/781 [00:09<00:32, 18.63it/s]
 24%|##3       | 184/781 [00:09<00:32, 18.64it/s]
 24%|##3       | 186/781 [00:10<00:32, 18.56it/s]
 24%|##4       | 188/781 [00:10<00:31, 18.61it/s]
 24%|##4       | 190/781 [00:10<00:31, 18.71it/s]
 25%|##4       | 192/781 [00:10<00:31, 18.79it/s]
 25%|##4       | 194/781 [00:10<00:31, 18.70it/s]
 25%|##5       | 196/781 [00:10<00:31, 18.69it/s]
 25%|##5       | 198/781 [00:10<00:31, 18.64it/s]
 26%|##5       | 200/781 [00:10<00:31, 18.67it/s]
 26%|##5       | 202/781 [00:10<00:30, 18.85it/s]
 26%|##6       | 204/781 [00:11<00:30, 18.72it/s]
 26%|##6       | 206/781 [00:11<00:30, 18.66it/s]
 27%|##6       | 208/781 [00:11<00:30, 18.81it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.85it/s]
 27%|##7       | 212/781 [00:11<00:29, 19.01it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.85it/s]
 28%|##7       | 216/781 [00:11<00:29, 19.01it/s]
 28%|##7       | 218/781 [00:11<00:29, 19.11it/s]
 28%|##8       | 220/781 [00:11<00:29, 19.17it/s]
 28%|##8       | 222/781 [00:11<00:29, 19.21it/s]
 29%|##8       | 224/781 [00:12<00:29, 19.14it/s]
 29%|##8       | 226/781 [00:12<00:29, 19.13it/s]
 29%|##9       | 228/781 [00:12<00:29, 19.06it/s]
 29%|##9       | 230/781 [00:12<00:28, 19.11it/s]
 30%|##9       | 232/781 [00:12<00:28, 19.17it/s]
 30%|##9       | 234/781 [00:12<00:28, 19.21it/s]
 30%|###       | 236/781 [00:12<00:28, 19.16it/s]
 30%|###       | 238/781 [00:12<00:28, 19.23it/s]
 31%|###       | 240/781 [00:12<00:28, 19.23it/s]
 31%|###       | 242/781 [00:12<00:28, 19.15it/s]
 31%|###1      | 244/781 [00:13<00:28, 19.12it/s]
 31%|###1      | 246/781 [00:13<00:28, 19.05it/s]
 32%|###1      | 248/781 [00:13<00:28, 18.84it/s]
 32%|###2      | 250/781 [00:13<00:28, 18.93it/s]
 32%|###2      | 252/781 [00:13<00:28, 18.78it/s]
 33%|###2      | 254/781 [00:13<00:27, 18.88it/s]
 33%|###2      | 256/781 [00:13<00:27, 18.94it/s]
 33%|###3      | 258/781 [00:13<00:27, 18.94it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.03it/s]
 34%|###3      | 262/781 [00:14<00:27, 19.09it/s]
 34%|###3      | 264/781 [00:14<00:27, 18.91it/s]
 34%|###4      | 266/781 [00:14<00:27, 18.81it/s]
 34%|###4      | 268/781 [00:14<00:27, 18.90it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.02it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.08it/s]
 35%|###5      | 274/781 [00:14<00:26, 19.15it/s]
 35%|###5      | 276/781 [00:14<00:26, 19.02it/s]
 36%|###5      | 278/781 [00:14<00:26, 18.99it/s]
 36%|###5      | 280/781 [00:14<00:26, 19.04it/s]
 36%|###6      | 282/781 [00:15<00:26, 19.03it/s]
 36%|###6      | 284/781 [00:15<00:26, 18.83it/s]
 37%|###6      | 286/781 [00:15<00:26, 18.89it/s]
 37%|###6      | 288/781 [00:15<00:26, 18.83it/s]
 37%|###7      | 290/781 [00:15<00:25, 18.97it/s]
 37%|###7      | 292/781 [00:15<00:26, 18.74it/s]
 38%|###7      | 294/781 [00:15<00:26, 18.73it/s]
 38%|###7      | 296/781 [00:15<00:25, 18.77it/s]
 38%|###8      | 298/781 [00:15<00:25, 18.76it/s]
 38%|###8      | 300/781 [00:16<00:25, 18.97it/s]
 39%|###8      | 302/781 [00:16<00:25, 18.71it/s]
 39%|###8      | 304/781 [00:16<00:25, 18.83it/s]
 39%|###9      | 306/781 [00:16<00:25, 18.96it/s]
 39%|###9      | 308/781 [00:16<00:24, 19.04it/s]
 40%|###9      | 310/781 [00:16<00:24, 19.10it/s]
 40%|###9      | 312/781 [00:16<00:24, 19.10it/s]
 40%|####      | 314/781 [00:16<00:24, 18.92it/s]
 40%|####      | 316/781 [00:16<00:24, 18.72it/s]
 41%|####      | 318/781 [00:17<00:24, 18.84it/s]
 41%|####      | 320/781 [00:17<00:24, 18.99it/s]
 41%|####1     | 322/781 [00:17<00:24, 19.08it/s]
 41%|####1     | 324/781 [00:17<00:23, 19.16it/s]
 42%|####1     | 326/781 [00:17<00:23, 19.22it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.20it/s]
 42%|####2     | 330/781 [00:17<00:23, 19.13it/s]
 43%|####2     | 332/781 [00:17<00:23, 19.23it/s]
 43%|####2     | 334/781 [00:17<00:23, 19.20it/s]
 43%|####3     | 336/781 [00:17<00:23, 19.22it/s]
 43%|####3     | 338/781 [00:18<00:23, 19.22it/s]
 44%|####3     | 340/781 [00:18<00:23, 19.14it/s]
 44%|####3     | 342/781 [00:18<00:23, 19.04it/s]
 44%|####4     | 344/781 [00:18<00:22, 19.08it/s]
 44%|####4     | 346/781 [00:18<00:22, 19.18it/s]
 45%|####4     | 348/781 [00:18<00:22, 19.16it/s]
 45%|####4     | 350/781 [00:18<00:22, 19.19it/s]
 45%|####5     | 352/781 [00:18<00:22, 19.04it/s]
 45%|####5     | 354/781 [00:18<00:22, 18.85it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.78it/s]
 46%|####5     | 358/781 [00:19<00:22, 18.64it/s]
 46%|####6     | 360/781 [00:19<00:23, 18.23it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.37it/s]
 47%|####6     | 364/781 [00:19<00:22, 18.60it/s]
 47%|####6     | 366/781 [00:19<00:22, 18.66it/s]
 47%|####7     | 368/781 [00:19<00:22, 18.68it/s]
 47%|####7     | 370/781 [00:19<00:22, 18.39it/s]
 48%|####7     | 372/781 [00:19<00:22, 18.53it/s]
 48%|####7     | 374/781 [00:19<00:21, 18.73it/s]
 48%|####8     | 376/781 [00:20<00:21, 18.51it/s]
 48%|####8     | 378/781 [00:20<00:21, 18.37it/s]
 49%|####8     | 380/781 [00:20<00:22, 18.05it/s]
 49%|####8     | 382/781 [00:20<00:21, 18.44it/s]
 49%|####9     | 384/781 [00:20<00:21, 18.60it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.75it/s]
 50%|####9     | 388/781 [00:20<00:20, 18.84it/s]
 50%|####9     | 390/781 [00:20<00:20, 18.95it/s]
 50%|#####     | 392/781 [00:20<00:20, 19.01it/s]
 50%|#####     | 394/781 [00:21<00:20, 18.78it/s]
 51%|#####     | 396/781 [00:21<00:20, 18.74it/s]
 51%|#####     | 398/781 [00:21<00:20, 18.84it/s]
 51%|#####1    | 400/781 [00:21<00:20, 18.84it/s]
 51%|#####1    | 402/781 [00:21<00:20, 18.86it/s]
 52%|#####1    | 404/781 [00:21<00:19, 19.02it/s]
 52%|#####1    | 406/781 [00:21<00:19, 19.16it/s]
 52%|#####2    | 408/781 [00:21<00:19, 19.34it/s]
 52%|#####2    | 410/781 [00:21<00:19, 19.45it/s]
 53%|#####2    | 412/781 [00:21<00:18, 19.57it/s]
 53%|#####3    | 414/781 [00:22<00:18, 19.66it/s]
 53%|#####3    | 416/781 [00:22<00:18, 19.60it/s]
 54%|#####3    | 418/781 [00:22<00:18, 19.54it/s]
 54%|#####3    | 420/781 [00:22<00:18, 19.55it/s]
 54%|#####4    | 422/781 [00:22<00:18, 19.28it/s]
 54%|#####4    | 424/781 [00:22<00:18, 19.22it/s]
 55%|#####4    | 426/781 [00:22<00:18, 19.15it/s]
 55%|#####4    | 428/781 [00:22<00:18, 19.33it/s]
 55%|#####5    | 430/781 [00:22<00:18, 19.23it/s]
 55%|#####5    | 432/781 [00:23<00:18, 19.18it/s]
 56%|#####5    | 434/781 [00:23<00:18, 19.25it/s]
 56%|#####5    | 436/781 [00:23<00:18, 19.12it/s]
 56%|#####6    | 438/781 [00:23<00:33, 10.38it/s]
 56%|#####6    | 440/781 [00:23<00:28, 12.07it/s]
 57%|#####6    | 442/781 [00:23<00:24, 13.60it/s]
 57%|#####6    | 444/781 [00:23<00:22, 14.92it/s]
 57%|#####7    | 446/781 [00:24<00:20, 16.09it/s]
 57%|#####7    | 448/781 [00:24<00:19, 16.79it/s]
 58%|#####7    | 450/781 [00:24<00:19, 17.32it/s]
 58%|#####7    | 452/781 [00:24<00:18, 17.94it/s]
 58%|#####8    | 454/781 [00:24<00:17, 18.43it/s]
 58%|#####8    | 456/781 [00:24<00:17, 18.80it/s]
 59%|#####8    | 458/781 [00:24<00:16, 19.00it/s]
 59%|#####8    | 460/781 [00:24<00:16, 19.18it/s]
 59%|#####9    | 462/781 [00:24<00:16, 19.39it/s]
 59%|#####9    | 464/781 [00:24<00:16, 19.55it/s]
 60%|#####9    | 466/781 [00:25<00:16, 19.52it/s]
 60%|######    | 469/781 [00:25<00:15, 19.70it/s]
 60%|######    | 472/781 [00:25<00:15, 19.80it/s]
 61%|######    | 474/781 [00:25<00:15, 19.81it/s]
 61%|######    | 476/781 [00:25<00:15, 19.80it/s]
 61%|######1   | 478/781 [00:25<00:15, 19.78it/s]
 61%|######1   | 480/781 [00:25<00:15, 19.81it/s]
 62%|######1   | 482/781 [00:25<00:15, 19.85it/s]
 62%|######1   | 484/781 [00:25<00:14, 19.80it/s]
 62%|######2   | 486/781 [00:26<00:14, 19.77it/s]
 62%|######2   | 488/781 [00:26<00:14, 19.60it/s]
 63%|######2   | 490/781 [00:26<00:14, 19.50it/s]
 63%|######2   | 492/781 [00:26<00:14, 19.29it/s]
 63%|######3   | 494/781 [00:26<00:14, 19.22it/s]
 64%|######3   | 496/781 [00:26<00:14, 19.26it/s]
 64%|######3   | 498/781 [00:26<00:14, 19.19it/s]
 64%|######4   | 500/781 [00:26<00:14, 19.31it/s]
 64%|######4   | 502/781 [00:26<00:14, 19.40it/s]
 65%|######4   | 504/781 [00:27<00:14, 19.46it/s]
 65%|######4   | 506/781 [00:27<00:14, 19.49it/s]
 65%|######5   | 508/781 [00:27<00:14, 19.49it/s]
 65%|######5   | 510/781 [00:27<00:13, 19.52it/s]
 66%|######5   | 512/781 [00:27<00:13, 19.45it/s]
 66%|######5   | 514/781 [00:27<00:13, 19.45it/s]
 66%|######6   | 516/781 [00:27<00:13, 19.52it/s]
 66%|######6   | 518/781 [00:27<00:13, 19.44it/s]
 67%|######6   | 520/781 [00:27<00:13, 19.26it/s]
 67%|######6   | 522/781 [00:27<00:13, 19.36it/s]
 67%|######7   | 525/781 [00:28<00:13, 19.61it/s]
 67%|######7   | 527/781 [00:28<00:12, 19.62it/s]
 68%|######7   | 529/781 [00:28<00:12, 19.65it/s]
 68%|######7   | 531/781 [00:28<00:12, 19.72it/s]
 68%|######8   | 533/781 [00:28<00:12, 19.79it/s]
 69%|######8   | 535/781 [00:28<00:12, 19.77it/s]
 69%|######8   | 537/781 [00:28<00:12, 19.79it/s]
 69%|######9   | 539/781 [00:28<00:12, 19.72it/s]
 69%|######9   | 541/781 [00:28<00:12, 19.76it/s]
 70%|######9   | 543/781 [00:28<00:12, 19.46it/s]
 70%|######9   | 545/781 [00:29<00:12, 19.35it/s]
 70%|#######   | 547/781 [00:29<00:12, 19.15it/s]
 70%|#######   | 549/781 [00:29<00:12, 19.10it/s]
 71%|#######   | 551/781 [00:29<00:11, 19.17it/s]
 71%|#######   | 553/781 [00:29<00:11, 19.07it/s]
 71%|#######1  | 555/781 [00:29<00:11, 19.12it/s]
 71%|#######1  | 557/781 [00:29<00:11, 19.22it/s]
 72%|#######1  | 559/781 [00:29<00:11, 19.26it/s]
 72%|#######1  | 561/781 [00:29<00:11, 18.99it/s]
 72%|#######2  | 563/781 [00:30<00:11, 18.85it/s]
 72%|#######2  | 565/781 [00:30<00:11, 18.75it/s]
 73%|#######2  | 567/781 [00:30<00:11, 18.58it/s]
 73%|#######2  | 569/781 [00:30<00:11, 18.69it/s]
 73%|#######3  | 571/781 [00:30<00:11, 18.37it/s]
 73%|#######3  | 573/781 [00:30<00:11, 18.57it/s]
 74%|#######3  | 575/781 [00:30<00:11, 18.39it/s]
 74%|#######3  | 577/781 [00:30<00:10, 18.63it/s]
 74%|#######4  | 579/781 [00:30<00:10, 18.79it/s]
 74%|#######4  | 581/781 [00:31<00:10, 18.89it/s]
 75%|#######4  | 583/781 [00:31<00:10, 19.01it/s]
 75%|#######4  | 585/781 [00:31<00:10, 19.14it/s]
 75%|#######5  | 587/781 [00:31<00:10, 18.97it/s]
 75%|#######5  | 589/781 [00:31<00:10, 18.82it/s]
 76%|#######5  | 591/781 [00:31<00:10, 18.68it/s]
 76%|#######5  | 593/781 [00:31<00:10, 18.70it/s]
 76%|#######6  | 595/781 [00:31<00:09, 18.70it/s]
 76%|#######6  | 597/781 [00:31<00:09, 18.84it/s]
 77%|#######6  | 599/781 [00:31<00:09, 19.00it/s]
 77%|#######6  | 601/781 [00:32<00:09, 19.02it/s]
 77%|#######7  | 603/781 [00:32<00:09, 18.95it/s]
 77%|#######7  | 605/781 [00:32<00:09, 18.60it/s]
 78%|#######7  | 607/781 [00:32<00:09, 18.58it/s]
 78%|#######7  | 609/781 [00:32<00:09, 18.61it/s]
 78%|#######8  | 611/781 [00:32<00:09, 18.75it/s]
 78%|#######8  | 613/781 [00:32<00:08, 18.89it/s]
 79%|#######8  | 615/781 [00:32<00:08, 18.92it/s]
 79%|#######9  | 617/781 [00:32<00:08, 19.02it/s]
 79%|#######9  | 619/781 [00:33<00:08, 18.74it/s]
 80%|#######9  | 621/781 [00:33<00:08, 18.58it/s]
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Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:09<00:00,  9.56s/it]
100%|##########| 1/1 [00:09<00:00,  9.56s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:10, 14.56it/s]
  3%|2         | 4/157 [00:00<00:10, 14.30it/s]
  4%|3         | 6/157 [00:00<00:10, 14.13it/s]
  5%|5         | 8/157 [00:00<00:09, 15.11it/s]
  6%|6         | 10/157 [00:00<00:09, 15.74it/s]
  8%|7         | 12/157 [00:00<00:08, 16.21it/s]
  9%|8         | 14/157 [00:00<00:08, 16.49it/s]
 10%|#         | 16/157 [00:01<00:08, 16.64it/s]
 11%|#1        | 18/157 [00:01<00:08, 16.68it/s]
 13%|#2        | 20/157 [00:01<00:08, 16.48it/s]
 14%|#4        | 22/157 [00:01<00:08, 16.61it/s]
 15%|#5        | 24/157 [00:01<00:07, 16.73it/s]
 17%|#6        | 26/157 [00:01<00:07, 16.72it/s]
 18%|#7        | 28/157 [00:01<00:07, 16.54it/s]
 19%|#9        | 30/157 [00:01<00:07, 16.62it/s]
 20%|##        | 32/157 [00:01<00:07, 16.78it/s]
 22%|##1       | 34/157 [00:02<00:07, 16.81it/s]
 23%|##2       | 36/157 [00:02<00:07, 16.71it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.72it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.57it/s]
 27%|##6       | 42/157 [00:02<00:06, 16.75it/s]
 28%|##8       | 44/157 [00:02<00:06, 16.77it/s]
 29%|##9       | 46/157 [00:02<00:06, 16.91it/s]
 31%|###       | 48/157 [00:02<00:06, 16.87it/s]
 32%|###1      | 50/157 [00:03<00:06, 17.00it/s]
 33%|###3      | 52/157 [00:03<00:06, 17.10it/s]
 34%|###4      | 54/157 [00:03<00:06, 17.07it/s]
 36%|###5      | 56/157 [00:03<00:05, 17.06it/s]
 37%|###6      | 58/157 [00:03<00:05, 17.15it/s]
 38%|###8      | 60/157 [00:03<00:05, 17.15it/s]
 39%|###9      | 62/157 [00:03<00:05, 17.15it/s]
 41%|####      | 64/157 [00:03<00:05, 17.20it/s]
 42%|####2     | 66/157 [00:03<00:05, 17.21it/s]
 43%|####3     | 68/157 [00:04<00:05, 17.21it/s]
 45%|####4     | 70/157 [00:04<00:05, 17.09it/s]
 46%|####5     | 72/157 [00:04<00:04, 17.11it/s]
 47%|####7     | 74/157 [00:04<00:04, 17.11it/s]
 48%|####8     | 76/157 [00:04<00:04, 16.94it/s]
 50%|####9     | 78/157 [00:04<00:04, 16.97it/s]
 51%|#####     | 80/157 [00:04<00:04, 16.99it/s]
 52%|#####2    | 82/157 [00:04<00:04, 17.03it/s]
 54%|#####3    | 84/157 [00:05<00:04, 17.04it/s]
 55%|#####4    | 86/157 [00:05<00:04, 17.03it/s]
 56%|#####6    | 88/157 [00:05<00:04, 16.71it/s]
 57%|#####7    | 90/157 [00:05<00:04, 16.48it/s]
 59%|#####8    | 92/157 [00:05<00:03, 16.47it/s]
 60%|#####9    | 94/157 [00:05<00:03, 16.73it/s]
 61%|######1   | 96/157 [00:05<00:03, 16.64it/s]
 62%|######2   | 98/157 [00:05<00:03, 16.30it/s]
 64%|######3   | 100/157 [00:06<00:03, 16.02it/s]
 65%|######4   | 102/157 [00:06<00:03, 15.92it/s]
 66%|######6   | 104/157 [00:06<00:03, 16.05it/s]
 68%|######7   | 106/157 [00:06<00:03, 16.03it/s]
 69%|######8   | 108/157 [00:06<00:03, 16.19it/s]
 70%|#######   | 110/157 [00:06<00:02, 16.26it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.31it/s]
 73%|#######2  | 114/157 [00:06<00:02, 16.27it/s]
 74%|#######3  | 116/157 [00:06<00:02, 16.33it/s]
 75%|#######5  | 118/157 [00:07<00:02, 16.35it/s]
 76%|#######6  | 120/157 [00:07<00:02, 16.42it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.42it/s]
 79%|#######8  | 124/157 [00:07<00:02, 16.10it/s]
 80%|########  | 126/157 [00:07<00:01, 16.25it/s]
 82%|########1 | 128/157 [00:07<00:01, 16.18it/s]
 83%|########2 | 130/157 [00:07<00:01, 15.97it/s]
 84%|########4 | 132/157 [00:07<00:01, 15.96it/s]
 85%|########5 | 134/157 [00:08<00:01, 16.13it/s]
 87%|########6 | 136/157 [00:08<00:01, 16.15it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.48it/s]
 89%|########9 | 140/157 [00:08<00:01, 16.19it/s]
 90%|######### | 142/157 [00:08<00:00, 16.36it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.54it/s]
 93%|#########2| 146/157 [00:08<00:00, 16.67it/s]
 94%|#########4| 148/157 [00:08<00:00, 16.75it/s]
 96%|#########5| 150/157 [00:09<00:00, 16.64it/s]
 97%|#########6| 152/157 [00:09<00:00, 16.64it/s]
 98%|#########8| 154/157 [00:09<00:00, 16.77it/s]
 99%|#########9| 156/157 [00:09<00:00, 16.83it/s]
100%|##########| 157/157 [00:09<00:00, 16.61it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:44, 17.47it/s]
  1%|          | 4/781 [00:00<00:42, 18.22it/s]
  1%|          | 6/781 [00:00<00:41, 18.57it/s]
  1%|1         | 8/781 [00:00<00:41, 18.63it/s]
  1%|1         | 10/781 [00:00<00:41, 18.79it/s]
  2%|1         | 12/781 [00:00<00:40, 18.85it/s]
  2%|1         | 14/781 [00:00<00:41, 18.62it/s]
  2%|2         | 16/781 [00:00<00:40, 18.69it/s]
  2%|2         | 18/781 [00:00<00:41, 18.56it/s]
  3%|2         | 20/781 [00:01<00:40, 18.76it/s]
  3%|2         | 22/781 [00:01<00:40, 18.70it/s]
  3%|3         | 24/781 [00:01<00:39, 18.99it/s]
  3%|3         | 26/781 [00:01<00:39, 18.99it/s]
  4%|3         | 28/781 [00:01<00:39, 19.13it/s]
  4%|3         | 30/781 [00:01<00:39, 18.98it/s]
  4%|4         | 32/781 [00:01<00:39, 19.16it/s]
  4%|4         | 34/781 [00:01<00:39, 18.97it/s]
  5%|4         | 36/781 [00:01<00:38, 19.21it/s]
  5%|4         | 38/781 [00:02<00:38, 19.30it/s]
  5%|5         | 40/781 [00:02<00:38, 19.28it/s]
  5%|5         | 42/781 [00:02<00:38, 19.44it/s]
  6%|5         | 44/781 [00:02<00:37, 19.56it/s]
  6%|5         | 46/781 [00:02<00:37, 19.57it/s]
  6%|6         | 48/781 [00:02<00:37, 19.42it/s]
  6%|6         | 50/781 [00:02<00:37, 19.53it/s]
  7%|6         | 52/781 [00:02<00:37, 19.64it/s]
  7%|6         | 54/781 [00:02<00:37, 19.38it/s]
  7%|7         | 56/781 [00:02<00:37, 19.47it/s]
  7%|7         | 58/781 [00:03<00:37, 19.53it/s]
  8%|7         | 60/781 [00:03<00:37, 19.46it/s]
  8%|7         | 62/781 [00:03<00:36, 19.52it/s]
  8%|8         | 64/781 [00:03<00:36, 19.55it/s]
  8%|8         | 66/781 [00:03<00:36, 19.65it/s]
  9%|8         | 68/781 [00:03<00:37, 19.26it/s]
  9%|8         | 70/781 [00:03<00:37, 19.01it/s]
  9%|9         | 72/781 [00:03<00:36, 19.17it/s]
  9%|9         | 74/781 [00:03<00:36, 19.31it/s]
 10%|9         | 76/781 [00:03<00:36, 19.43it/s]
 10%|9         | 78/781 [00:04<00:35, 19.54it/s]
 10%|#         | 80/781 [00:04<00:35, 19.49it/s]
 10%|#         | 82/781 [00:04<00:35, 19.46it/s]
 11%|#         | 84/781 [00:04<00:35, 19.39it/s]
 11%|#1        | 86/781 [00:04<00:35, 19.33it/s]
 11%|#1        | 88/781 [00:04<00:35, 19.37it/s]
 12%|#1        | 90/781 [00:04<00:35, 19.51it/s]
 12%|#1        | 92/781 [00:04<00:35, 19.64it/s]
 12%|#2        | 94/781 [00:04<00:35, 19.52it/s]
 12%|#2        | 96/781 [00:04<00:35, 19.46it/s]
 13%|#2        | 98/781 [00:05<00:35, 19.48it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.41it/s]
 13%|#3        | 102/781 [00:05<00:34, 19.45it/s]
 13%|#3        | 104/781 [00:05<00:35, 19.29it/s]
 14%|#3        | 106/781 [00:05<00:34, 19.30it/s]
 14%|#3        | 108/781 [00:05<00:34, 19.36it/s]
 14%|#4        | 110/781 [00:05<00:34, 19.51it/s]
 14%|#4        | 112/781 [00:05<00:34, 19.60it/s]
 15%|#4        | 114/781 [00:05<00:33, 19.64it/s]
 15%|#4        | 116/781 [00:06<00:34, 19.53it/s]
 15%|#5        | 118/781 [00:06<00:33, 19.55it/s]
 15%|#5        | 120/781 [00:06<00:34, 19.32it/s]
 16%|#5        | 122/781 [00:06<00:34, 19.18it/s]
 16%|#5        | 124/781 [00:06<00:34, 19.26it/s]
 16%|#6        | 126/781 [00:06<00:34, 19.16it/s]
 16%|#6        | 128/781 [00:06<00:33, 19.21it/s]
 17%|#6        | 130/781 [00:06<00:33, 19.35it/s]
 17%|#6        | 132/781 [00:06<00:33, 19.38it/s]
 17%|#7        | 134/781 [00:06<00:33, 19.36it/s]
 17%|#7        | 136/781 [00:07<00:33, 19.41it/s]
 18%|#7        | 138/781 [00:07<00:33, 18.92it/s]
 18%|#7        | 140/781 [00:07<00:34, 18.79it/s]
 18%|#8        | 142/781 [00:07<00:33, 18.80it/s]
 18%|#8        | 144/781 [00:07<00:33, 18.96it/s]
 19%|#8        | 146/781 [00:07<00:33, 18.68it/s]
 19%|#8        | 148/781 [00:07<00:33, 18.63it/s]
 19%|#9        | 150/781 [00:07<00:34, 18.43it/s]
 19%|#9        | 152/781 [00:07<00:34, 18.47it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.68it/s]
 20%|#9        | 156/781 [00:08<00:33, 18.60it/s]
 20%|##        | 158/781 [00:08<00:33, 18.74it/s]
 20%|##        | 160/781 [00:08<00:33, 18.47it/s]
 21%|##        | 162/781 [00:08<00:33, 18.65it/s]
 21%|##        | 164/781 [00:08<00:32, 18.94it/s]
 21%|##1       | 166/781 [00:08<00:32, 19.11it/s]
 22%|##1       | 168/781 [00:08<00:31, 19.30it/s]
 22%|##1       | 170/781 [00:08<00:31, 19.46it/s]
 22%|##2       | 172/781 [00:08<00:31, 19.55it/s]
 22%|##2       | 174/781 [00:09<00:31, 19.53it/s]
 23%|##2       | 176/781 [00:09<00:30, 19.62it/s]
 23%|##2       | 178/781 [00:09<00:31, 19.24it/s]
 23%|##3       | 180/781 [00:09<00:31, 19.36it/s]
 23%|##3       | 182/781 [00:09<00:30, 19.37it/s]
 24%|##3       | 185/781 [00:09<00:30, 19.57it/s]
 24%|##3       | 187/781 [00:09<00:30, 19.58it/s]
 24%|##4       | 189/781 [00:09<00:30, 19.57it/s]
 24%|##4       | 191/781 [00:09<00:30, 19.48it/s]
 25%|##4       | 193/781 [00:10<00:30, 19.56it/s]
 25%|##5       | 196/781 [00:10<00:29, 19.67it/s]
 25%|##5       | 198/781 [00:10<00:29, 19.66it/s]
 26%|##5       | 200/781 [00:10<00:29, 19.74it/s]
 26%|##5       | 202/781 [00:10<00:29, 19.75it/s]
 26%|##6       | 204/781 [00:10<00:29, 19.74it/s]
 26%|##6       | 206/781 [00:10<00:29, 19.73it/s]
 27%|##6       | 208/781 [00:10<00:29, 19.72it/s]
 27%|##6       | 210/781 [00:10<00:28, 19.78it/s]
 27%|##7       | 212/781 [00:11<00:28, 19.77it/s]
 27%|##7       | 214/781 [00:11<00:28, 19.75it/s]
 28%|##7       | 216/781 [00:11<00:28, 19.57it/s]
 28%|##7       | 218/781 [00:11<00:28, 19.58it/s]
 28%|##8       | 220/781 [00:11<00:28, 19.48it/s]
 28%|##8       | 222/781 [00:11<00:28, 19.28it/s]
 29%|##8       | 224/781 [00:11<00:28, 19.31it/s]
 29%|##8       | 226/781 [00:11<00:29, 19.12it/s]
 29%|##9       | 228/781 [00:11<00:28, 19.28it/s]
 29%|##9       | 230/781 [00:11<00:29, 18.75it/s]
 30%|##9       | 232/781 [00:12<00:29, 18.46it/s]
 30%|##9       | 234/781 [00:12<00:29, 18.53it/s]
 30%|###       | 236/781 [00:12<00:28, 18.79it/s]
 30%|###       | 238/781 [00:12<00:28, 18.93it/s]
 31%|###       | 240/781 [00:12<00:28, 19.10it/s]
 31%|###       | 242/781 [00:12<00:28, 19.24it/s]
 31%|###1      | 244/781 [00:12<00:27, 19.39it/s]
 31%|###1      | 246/781 [00:12<00:27, 19.55it/s]
 32%|###1      | 248/781 [00:12<00:27, 19.51it/s]
 32%|###2      | 250/781 [00:12<00:27, 19.38it/s]
 32%|###2      | 252/781 [00:13<00:27, 19.43it/s]
 33%|###2      | 254/781 [00:13<00:27, 18.91it/s]
 33%|###2      | 256/781 [00:13<00:28, 18.59it/s]
 33%|###3      | 258/781 [00:13<00:28, 18.21it/s]
 33%|###3      | 260/781 [00:13<00:28, 18.58it/s]
 34%|###3      | 262/781 [00:13<00:27, 18.89it/s]
 34%|###3      | 264/781 [00:13<00:27, 18.67it/s]
 34%|###4      | 266/781 [00:13<00:27, 18.98it/s]
 34%|###4      | 268/781 [00:13<00:26, 19.15it/s]
 35%|###4      | 270/781 [00:14<00:26, 18.99it/s]
 35%|###4      | 272/781 [00:14<00:26, 19.10it/s]
 35%|###5      | 274/781 [00:14<00:27, 18.62it/s]
 35%|###5      | 276/781 [00:14<00:26, 18.71it/s]
 36%|###5      | 278/781 [00:14<00:26, 18.78it/s]
 36%|###5      | 280/781 [00:14<00:26, 19.05it/s]
 36%|###6      | 282/781 [00:14<00:26, 19.14it/s]
 36%|###6      | 284/781 [00:14<00:25, 19.30it/s]
 37%|###6      | 286/781 [00:14<00:25, 19.27it/s]
 37%|###6      | 288/781 [00:14<00:25, 19.48it/s]
 37%|###7      | 290/781 [00:15<00:25, 19.40it/s]
 37%|###7      | 292/781 [00:15<00:25, 19.25it/s]
 38%|###7      | 294/781 [00:15<00:25, 19.29it/s]
 38%|###8      | 297/781 [00:15<00:24, 19.59it/s]
 38%|###8      | 299/781 [00:15<00:24, 19.65it/s]
 39%|###8      | 301/781 [00:15<00:24, 19.71it/s]
 39%|###8      | 303/781 [00:15<00:24, 19.65it/s]
 39%|###9      | 305/781 [00:15<00:24, 19.43it/s]
 39%|###9      | 307/781 [00:15<00:24, 19.41it/s]
 40%|###9      | 309/781 [00:16<00:24, 19.21it/s]
 40%|###9      | 311/781 [00:16<00:24, 19.31it/s]
 40%|####      | 313/781 [00:16<00:24, 19.25it/s]
 40%|####      | 315/781 [00:16<00:24, 19.15it/s]
 41%|####      | 317/781 [00:16<00:24, 18.84it/s]
 41%|####      | 319/781 [00:16<00:24, 18.81it/s]
 41%|####1     | 321/781 [00:16<00:24, 18.76it/s]
 41%|####1     | 323/781 [00:16<00:24, 18.73it/s]
 42%|####1     | 325/781 [00:16<00:24, 18.61it/s]
 42%|####1     | 327/781 [00:17<00:24, 18.49it/s]
 42%|####2     | 329/781 [00:17<00:24, 18.57it/s]
 42%|####2     | 331/781 [00:17<00:24, 18.75it/s]
 43%|####2     | 333/781 [00:17<00:23, 18.95it/s]
 43%|####2     | 335/781 [00:17<00:23, 19.13it/s]
 43%|####3     | 337/781 [00:17<00:23, 19.28it/s]
 43%|####3     | 339/781 [00:17<00:22, 19.39it/s]
 44%|####3     | 341/781 [00:17<00:22, 19.30it/s]
 44%|####3     | 343/781 [00:17<00:22, 19.33it/s]
 44%|####4     | 345/781 [00:17<00:22, 19.38it/s]
 44%|####4     | 347/781 [00:18<00:22, 19.21it/s]
 45%|####4     | 349/781 [00:18<00:22, 19.37it/s]
 45%|####4     | 351/781 [00:18<00:22, 19.31it/s]
 45%|####5     | 353/781 [00:18<00:22, 19.23it/s]
 45%|####5     | 355/781 [00:18<00:22, 19.23it/s]
 46%|####5     | 357/781 [00:18<00:21, 19.33it/s]
 46%|####5     | 359/781 [00:18<00:22, 19.16it/s]
 46%|####6     | 361/781 [00:18<00:21, 19.28it/s]
 46%|####6     | 363/781 [00:18<00:21, 19.34it/s]
 47%|####6     | 365/781 [00:19<00:21, 19.49it/s]
 47%|####6     | 367/781 [00:19<00:21, 19.33it/s]
 47%|####7     | 369/781 [00:19<00:21, 18.85it/s]
 48%|####7     | 371/781 [00:19<00:21, 18.80it/s]
 48%|####7     | 373/781 [00:19<00:21, 18.74it/s]
 48%|####8     | 375/781 [00:19<00:21, 18.97it/s]
 48%|####8     | 377/781 [00:19<00:21, 19.14it/s]
 49%|####8     | 379/781 [00:19<00:21, 19.05it/s]
 49%|####8     | 381/781 [00:19<00:21, 18.99it/s]
 49%|####9     | 384/781 [00:20<00:20, 19.40it/s]
 49%|####9     | 386/781 [00:20<00:20, 19.48it/s]
 50%|####9     | 388/781 [00:20<00:20, 19.25it/s]
 50%|####9     | 390/781 [00:20<00:20, 19.35it/s]
 50%|#####     | 392/781 [00:20<00:20, 19.40it/s]
 50%|#####     | 394/781 [00:20<00:19, 19.48it/s]
 51%|#####     | 396/781 [00:20<00:19, 19.46it/s]
 51%|#####     | 398/781 [00:20<00:19, 19.30it/s]
 51%|#####1    | 401/781 [00:20<00:19, 19.56it/s]
 52%|#####1    | 403/781 [00:20<00:19, 19.56it/s]
 52%|#####1    | 405/781 [00:21<00:19, 19.56it/s]
 52%|#####2    | 407/781 [00:21<00:19, 19.68it/s]
 52%|#####2    | 409/781 [00:21<00:19, 19.09it/s]
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100%|#########9| 780/781 [00:40<00:00, 19.19it/s]
100%|##########| 781/781 [00:40<00:00, 19.07it/s]




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Validation Progress:  50%|#####     | 22/44 [00:23<00:24,  1.11s/it]
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Validation Progress:  52%|#####2    | 23/44 [00:24<00:24,  1.17s/it]
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Validation Progress:  55%|#####4    | 24/44 [00:25<00:22,  1.14s/it]
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Validation Progress:  57%|#####6    | 25/44 [00:26<00:21,  1.14s/it]
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Validation Progress:  57%|#####6    | 25/44 [00:26<00:21,  1.15s/it]
Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.14s/it]
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Validation Progress:  61%|######1   | 27/44 [00:29<00:19,  1.14s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:17,  1.12s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:17,  1.12s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
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Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.10s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
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Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
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Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.19s/it]
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Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.19s/it]
Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.19s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
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Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
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Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]

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100%|##########| 1/1 [00:10<00:00, 10.64s/it]
100%|##########| 1/1 [00:10<00:00, 10.64s/it]

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100%|##########| 157/157 [00:11<00:00, 14.21it/s]

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 24%|##4       | 188/781 [00:10<00:32, 18.11it/s]
 24%|##4       | 190/781 [00:10<00:32, 18.20it/s]
 25%|##4       | 192/781 [00:10<00:32, 18.20it/s]
 25%|##4       | 194/781 [00:10<00:32, 18.26it/s]
 25%|##5       | 196/781 [00:10<00:31, 18.29it/s]
 25%|##5       | 198/781 [00:10<00:32, 18.08it/s]
 26%|##5       | 200/781 [00:11<00:32, 18.15it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.91it/s]
 26%|##6       | 204/781 [00:11<00:32, 17.80it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.94it/s]
 27%|##6       | 208/781 [00:11<00:32, 17.87it/s]
 27%|##6       | 210/781 [00:11<00:31, 17.98it/s]
 27%|##7       | 212/781 [00:11<00:31, 18.07it/s]
 27%|##7       | 214/781 [00:11<00:31, 18.12it/s]
 28%|##7       | 216/781 [00:11<00:31, 18.16it/s]
 28%|##7       | 218/781 [00:12<00:31, 18.12it/s]
 28%|##8       | 220/781 [00:12<00:30, 18.11it/s]
 28%|##8       | 222/781 [00:12<00:31, 17.90it/s]
 29%|##8       | 224/781 [00:12<00:30, 17.99it/s]
 29%|##8       | 226/781 [00:12<00:30, 17.99it/s]
 29%|##9       | 228/781 [00:12<00:30, 18.00it/s]
 29%|##9       | 230/781 [00:12<00:30, 18.01it/s]
 30%|##9       | 232/781 [00:12<00:30, 18.11it/s]
 30%|##9       | 234/781 [00:12<00:30, 18.16it/s]
 30%|###       | 236/781 [00:13<00:29, 18.21it/s]
 30%|###       | 238/781 [00:13<00:29, 18.20it/s]
 31%|###       | 240/781 [00:13<00:29, 18.19it/s]
 31%|###       | 242/781 [00:13<00:29, 18.18it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.03it/s]
 31%|###1      | 246/781 [00:13<00:29, 17.96it/s]
 32%|###1      | 248/781 [00:13<00:29, 17.88it/s]
 32%|###2      | 250/781 [00:13<00:29, 17.93it/s]
 32%|###2      | 252/781 [00:13<00:29, 18.04it/s]
 33%|###2      | 254/781 [00:14<00:29, 18.06it/s]
 33%|###2      | 256/781 [00:14<00:29, 18.06it/s]
 33%|###3      | 258/781 [00:14<00:28, 18.07it/s]
 33%|###3      | 260/781 [00:14<00:28, 18.09it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.14it/s]
 34%|###3      | 264/781 [00:14<00:29, 17.74it/s]
 34%|###4      | 266/781 [00:14<00:28, 17.90it/s]
 34%|###4      | 268/781 [00:14<00:28, 17.93it/s]
 35%|###4      | 270/781 [00:14<00:28, 18.04it/s]
 35%|###4      | 272/781 [00:15<00:28, 18.10it/s]
 35%|###5      | 274/781 [00:15<00:27, 18.12it/s]
 35%|###5      | 276/781 [00:15<00:28, 18.01it/s]
 36%|###5      | 278/781 [00:15<00:27, 18.03it/s]
 36%|###5      | 280/781 [00:15<00:27, 18.04it/s]
 36%|###6      | 282/781 [00:15<00:27, 18.11it/s]
 36%|###6      | 284/781 [00:15<00:27, 18.09it/s]
 37%|###6      | 286/781 [00:15<00:27, 18.10it/s]
 37%|###6      | 288/781 [00:15<00:27, 18.16it/s]
 37%|###7      | 290/781 [00:16<00:27, 18.15it/s]
 37%|###7      | 292/781 [00:16<00:26, 18.12it/s]
 38%|###7      | 294/781 [00:16<00:26, 18.13it/s]
 38%|###7      | 296/781 [00:16<00:26, 18.04it/s]
 38%|###8      | 298/781 [00:16<00:26, 18.00it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.77it/s]
 39%|###8      | 302/781 [00:16<00:26, 17.75it/s]
 39%|###8      | 304/781 [00:16<00:26, 17.88it/s]
 39%|###9      | 306/781 [00:16<00:26, 18.02it/s]
 39%|###9      | 308/781 [00:17<00:26, 18.11it/s]
 40%|###9      | 310/781 [00:17<00:26, 18.11it/s]
 40%|###9      | 312/781 [00:17<00:25, 18.17it/s]
 40%|####      | 314/781 [00:17<00:26, 17.96it/s]
 40%|####      | 316/781 [00:17<00:26, 17.81it/s]
 41%|####      | 318/781 [00:17<00:25, 17.81it/s]
 41%|####      | 320/781 [00:17<00:25, 17.88it/s]
 41%|####1     | 322/781 [00:17<00:25, 17.99it/s]
 41%|####1     | 324/781 [00:17<00:25, 17.73it/s]
 42%|####1     | 326/781 [00:18<00:25, 17.63it/s]
 42%|####1     | 328/781 [00:18<00:25, 17.63it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.59it/s]
 43%|####2     | 332/781 [00:18<00:25, 17.64it/s]
 43%|####2     | 334/781 [00:18<00:25, 17.79it/s]
 43%|####3     | 336/781 [00:18<00:24, 17.90it/s]
 43%|####3     | 338/781 [00:18<00:24, 17.96it/s]
 44%|####3     | 340/781 [00:18<00:24, 17.88it/s]
 44%|####3     | 342/781 [00:18<00:24, 17.90it/s]
 44%|####4     | 344/781 [00:19<00:24, 17.73it/s]
 44%|####4     | 346/781 [00:19<00:24, 17.87it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.90it/s]
 45%|####4     | 350/781 [00:19<00:23, 17.99it/s]
 45%|####5     | 352/781 [00:19<00:23, 17.92it/s]
 45%|####5     | 354/781 [00:19<00:23, 17.99it/s]
 46%|####5     | 356/781 [00:19<00:23, 18.02it/s]
 46%|####5     | 358/781 [00:19<00:23, 18.10it/s]
 46%|####6     | 360/781 [00:19<00:23, 18.01it/s]
 46%|####6     | 362/781 [00:20<00:23, 18.03it/s]
 47%|####6     | 364/781 [00:20<00:23, 18.06it/s]
 47%|####6     | 366/781 [00:20<00:22, 18.12it/s]
 47%|####7     | 368/781 [00:20<00:22, 18.12it/s]
 47%|####7     | 370/781 [00:20<00:22, 17.97it/s]
 48%|####7     | 372/781 [00:20<00:22, 18.03it/s]
 48%|####7     | 374/781 [00:20<00:22, 17.80it/s]
 48%|####8     | 376/781 [00:20<00:22, 17.83it/s]
 48%|####8     | 378/781 [00:20<00:22, 17.94it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.99it/s]
 49%|####8     | 382/781 [00:21<00:22, 17.99it/s]
 49%|####9     | 384/781 [00:21<00:22, 18.01it/s]
 49%|####9     | 386/781 [00:21<00:21, 18.10it/s]
 50%|####9     | 388/781 [00:21<00:21, 18.04it/s]
 50%|####9     | 390/781 [00:21<00:22, 17.69it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.69it/s]
 50%|#####     | 394/781 [00:21<00:21, 17.73it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.76it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.75it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.68it/s]
 51%|#####1    | 402/781 [00:22<00:21, 17.75it/s]
 52%|#####1    | 404/781 [00:22<00:21, 17.89it/s]
 52%|#####1    | 406/781 [00:22<00:20, 17.95it/s]
 52%|#####2    | 408/781 [00:22<00:20, 17.81it/s]
 52%|#####2    | 410/781 [00:22<00:20, 17.91it/s]
 53%|#####2    | 412/781 [00:22<00:21, 17.49it/s]
 53%|#####3    | 414/781 [00:23<00:20, 17.74it/s]
 53%|#####3    | 416/781 [00:23<00:20, 17.85it/s]
 54%|#####3    | 418/781 [00:23<00:20, 17.89it/s]
 54%|#####3    | 420/781 [00:23<00:20, 17.91it/s]
 54%|#####4    | 422/781 [00:23<00:20, 17.82it/s]
 54%|#####4    | 424/781 [00:23<00:20, 17.60it/s]
 55%|#####4    | 426/781 [00:23<00:19, 17.77it/s]
 55%|#####4    | 428/781 [00:23<00:19, 17.88it/s]
 55%|#####5    | 430/781 [00:23<00:19, 17.79it/s]
 55%|#####5    | 432/781 [00:24<00:19, 17.79it/s]
 56%|#####5    | 434/781 [00:24<00:19, 17.87it/s]
 56%|#####5    | 436/781 [00:24<00:19, 18.01it/s]
 56%|#####6    | 438/781 [00:24<00:19, 17.80it/s]
 56%|#####6    | 440/781 [00:24<00:19, 17.95it/s]
 57%|#####6    | 442/781 [00:24<00:18, 18.04it/s]
 57%|#####6    | 444/781 [00:24<00:18, 18.13it/s]
 57%|#####7    | 446/781 [00:24<00:18, 18.08it/s]
 57%|#####7    | 448/781 [00:24<00:18, 18.13it/s]
 58%|#####7    | 450/781 [00:25<00:18, 18.10it/s]
 58%|#####7    | 452/781 [00:25<00:18, 18.07it/s]
 58%|#####8    | 454/781 [00:25<00:18, 18.08it/s]
 58%|#####8    | 456/781 [00:25<00:18, 18.05it/s]
 59%|#####8    | 458/781 [00:25<00:17, 18.00it/s]
 59%|#####8    | 460/781 [00:25<00:17, 17.98it/s]
 59%|#####9    | 462/781 [00:25<00:17, 17.88it/s]
 59%|#####9    | 464/781 [00:25<00:17, 17.68it/s]
 60%|#####9    | 466/781 [00:25<00:17, 17.60it/s]
 60%|#####9    | 468/781 [00:26<00:17, 17.40it/s]
 60%|######    | 470/781 [00:26<00:17, 17.44it/s]
 60%|######    | 472/781 [00:26<00:17, 17.45it/s]
 61%|######    | 474/781 [00:26<00:17, 17.57it/s]
 61%|######    | 476/781 [00:26<00:17, 17.76it/s]
 61%|######1   | 478/781 [00:26<00:17, 17.76it/s]
 61%|######1   | 480/781 [00:26<00:16, 17.81it/s]
 62%|######1   | 482/781 [00:26<00:16, 17.94it/s]
 62%|######1   | 484/781 [00:26<00:16, 17.90it/s]
 62%|######2   | 486/781 [00:27<00:16, 17.92it/s]
 62%|######2   | 488/781 [00:27<00:16, 17.95it/s]
 63%|######2   | 490/781 [00:27<00:16, 17.85it/s]
 63%|######2   | 492/781 [00:27<00:16, 17.88it/s]
 63%|######3   | 494/781 [00:27<00:15, 18.00it/s]
 64%|######3   | 496/781 [00:27<00:15, 18.08it/s]
 64%|######3   | 498/781 [00:27<00:15, 18.11it/s]
 64%|######4   | 500/781 [00:27<00:15, 18.17it/s]
 64%|######4   | 502/781 [00:27<00:15, 18.21it/s]
 65%|######4   | 504/781 [00:28<00:15, 18.18it/s]
 65%|######4   | 506/781 [00:28<00:15, 18.15it/s]
 65%|######5   | 508/781 [00:28<00:15, 18.19it/s]
 65%|######5   | 510/781 [00:28<00:14, 18.23it/s]
 66%|######5   | 512/781 [00:28<00:14, 18.10it/s]
 66%|######5   | 514/781 [00:28<00:14, 18.02it/s]
 66%|######6   | 516/781 [00:28<00:14, 18.08it/s]
 66%|######6   | 518/781 [00:28<00:14, 18.10it/s]
 67%|######6   | 520/781 [00:28<00:14, 17.96it/s]
 67%|######6   | 522/781 [00:29<00:14, 17.73it/s]
 67%|######7   | 524/781 [00:29<00:14, 17.79it/s]
 67%|######7   | 526/781 [00:29<00:14, 17.83it/s]
 68%|######7   | 528/781 [00:29<00:14, 17.84it/s]
 68%|######7   | 530/781 [00:29<00:14, 17.70it/s]
 68%|######8   | 532/781 [00:29<00:14, 17.70it/s]
 68%|######8   | 534/781 [00:29<00:13, 17.83it/s]
 69%|######8   | 536/781 [00:29<00:13, 17.82it/s]
 69%|######8   | 538/781 [00:29<00:13, 17.73it/s]
 69%|######9   | 540/781 [00:30<00:13, 17.54it/s]
 69%|######9   | 542/781 [00:30<00:13, 17.75it/s]
 70%|######9   | 544/781 [00:30<00:13, 17.85it/s]
 70%|######9   | 546/781 [00:30<00:13, 17.80it/s]
 70%|#######   | 548/781 [00:30<00:13, 17.67it/s]
 70%|#######   | 550/781 [00:30<00:13, 17.39it/s]
 71%|#######   | 552/781 [00:30<00:13, 17.33it/s]
 71%|#######   | 554/781 [00:30<00:13, 17.43it/s]
 71%|#######1  | 556/781 [00:30<00:12, 17.52it/s]
 71%|#######1  | 558/781 [00:31<00:12, 17.54it/s]
 72%|#######1  | 560/781 [00:31<00:12, 17.66it/s]
 72%|#######1  | 562/781 [00:31<00:12, 17.75it/s]
 72%|#######2  | 564/781 [00:31<00:12, 17.77it/s]
 72%|#######2  | 566/781 [00:31<00:12, 17.79it/s]
 73%|#######2  | 568/781 [00:31<00:11, 17.78it/s]
 73%|#######2  | 570/781 [00:31<00:11, 17.71it/s]
 73%|#######3  | 572/781 [00:31<00:11, 17.56it/s]
 73%|#######3  | 574/781 [00:31<00:11, 17.75it/s]
 74%|#######3  | 576/781 [00:32<00:11, 17.84it/s]
 74%|#######4  | 578/781 [00:32<00:11, 17.94it/s]
 74%|#######4  | 580/781 [00:32<00:11, 17.84it/s]
 75%|#######4  | 582/781 [00:32<00:11, 18.00it/s]
 75%|#######4  | 584/781 [00:32<00:10, 17.93it/s]
 75%|#######5  | 586/781 [00:32<00:10, 17.97it/s]
 75%|#######5  | 588/781 [00:32<00:10, 17.97it/s]
 76%|#######5  | 590/781 [00:32<00:10, 18.03it/s]
 76%|#######5  | 592/781 [00:32<00:10, 18.04it/s]
 76%|#######6  | 594/781 [00:33<00:10, 18.02it/s]
 76%|#######6  | 596/781 [00:33<00:10, 17.98it/s]
 77%|#######6  | 598/781 [00:33<00:10, 17.90it/s]
 77%|#######6  | 600/781 [00:33<00:10, 17.92it/s]
 77%|#######7  | 602/781 [00:33<00:09, 17.93it/s]
 77%|#######7  | 604/781 [00:33<00:09, 17.96it/s]
 78%|#######7  | 606/781 [00:33<00:09, 18.05it/s]
 78%|#######7  | 608/781 [00:33<00:09, 17.98it/s]
 78%|#######8  | 610/781 [00:33<00:09, 17.92it/s]
 78%|#######8  | 612/781 [00:34<00:09, 17.96it/s]
 79%|#######8  | 614/781 [00:34<00:09, 18.06it/s]
 79%|#######8  | 616/781 [00:34<00:09, 17.84it/s]
 79%|#######9  | 618/781 [00:34<00:09, 17.83it/s]
 79%|#######9  | 620/781 [00:34<00:08, 18.07it/s]
 80%|#######9  | 622/781 [00:34<00:08, 18.00it/s]
 80%|#######9  | 624/781 [00:34<00:08, 17.97it/s]
 80%|########  | 626/781 [00:34<00:08, 18.43it/s]
 80%|########  | 628/781 [00:34<00:08, 18.83it/s]
 81%|########  | 630/781 [00:35<00:07, 19.10it/s]
 81%|########1 | 633/781 [00:35<00:07, 19.57it/s]
 81%|########1 | 636/781 [00:35<00:07, 19.94it/s]
 82%|########1 | 639/781 [00:35<00:07, 20.08it/s]
 82%|########2 | 641/781 [00:35<00:06, 20.04it/s]
 82%|########2 | 644/781 [00:35<00:06, 20.18it/s]
 83%|########2 | 647/781 [00:35<00:06, 20.38it/s]
 83%|########3 | 650/781 [00:36<00:06, 20.31it/s]
 84%|########3 | 653/781 [00:36<00:06, 20.40it/s]
 84%|########3 | 656/781 [00:36<00:06, 20.46it/s]
 84%|########4 | 659/781 [00:36<00:05, 20.57it/s]
 85%|########4 | 662/781 [00:36<00:05, 20.55it/s]
 85%|########5 | 665/781 [00:36<00:05, 20.23it/s]
 86%|########5 | 668/781 [00:36<00:05, 20.35it/s]
 86%|########5 | 671/781 [00:37<00:05, 20.28it/s]
 86%|########6 | 674/781 [00:37<00:05, 20.38it/s]
 87%|########6 | 677/781 [00:37<00:05, 20.45it/s]
 87%|########7 | 680/781 [00:37<00:04, 20.55it/s]
 87%|########7 | 683/781 [00:37<00:04, 20.49it/s]
 88%|########7 | 686/781 [00:37<00:04, 20.42it/s]
 88%|########8 | 689/781 [00:37<00:04, 20.46it/s]
 89%|########8 | 692/781 [00:38<00:04, 20.48it/s]
 89%|########8 | 695/781 [00:38<00:04, 20.26it/s]
 89%|########9 | 698/781 [00:38<00:04, 20.33it/s]
 90%|########9 | 701/781 [00:38<00:03, 20.33it/s]
 90%|######### | 704/781 [00:38<00:03, 20.31it/s]
 91%|######### | 707/781 [00:38<00:03, 20.43it/s]
 91%|######### | 710/781 [00:38<00:03, 20.29it/s]
 91%|#########1| 713/781 [00:39<00:03, 20.25it/s]
 92%|#########1| 716/781 [00:39<00:03, 19.35it/s]
 92%|#########1| 718/781 [00:39<00:03, 18.94it/s]
 92%|#########2| 720/781 [00:39<00:03, 18.50it/s]
 92%|#########2| 722/781 [00:39<00:03, 18.12it/s]
 93%|#########2| 724/781 [00:39<00:03, 17.88it/s]
 93%|#########2| 726/781 [00:39<00:03, 17.72it/s]
 93%|#########3| 728/781 [00:39<00:02, 18.23it/s]
 93%|#########3| 730/781 [00:40<00:02, 18.04it/s]
 94%|#########3| 732/781 [00:40<00:02, 18.40it/s]
 94%|#########4| 735/781 [00:40<00:02, 19.03it/s]
 94%|#########4| 737/781 [00:40<00:02, 19.17it/s]
 95%|#########4| 740/781 [00:40<00:02, 19.30it/s]
 95%|#########5| 742/781 [00:40<00:02, 19.02it/s]
 95%|#########5| 745/781 [00:40<00:01, 19.43it/s]
 96%|#########5| 748/781 [00:41<00:01, 19.81it/s]
 96%|#########6| 750/781 [00:41<00:01, 19.76it/s]
 96%|#########6| 753/781 [00:41<00:01, 19.94it/s]
 97%|#########6| 756/781 [00:41<00:01, 20.05it/s]
 97%|#########7| 759/781 [00:41<00:01, 20.10it/s]
 98%|#########7| 762/781 [00:41<00:00, 19.60it/s]
 98%|#########7| 764/781 [00:41<00:00, 19.57it/s]
 98%|#########8| 766/781 [00:41<00:00, 19.34it/s]
 98%|#########8| 768/781 [00:42<00:00, 19.48it/s]
 99%|#########8| 771/781 [00:42<00:00, 19.74it/s]
 99%|#########9| 774/781 [00:42<00:00, 20.00it/s]
 99%|#########9| 777/781 [00:42<00:00, 20.10it/s]
100%|#########9| 780/781 [00:42<00:00, 20.28it/s]
100%|##########| 781/781 [00:42<00:00, 18.30it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.05it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.02it/s]
Validation Progress:   2%|2         | 1/44 [00:01<00:43,  1.01s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.01s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:42,  1.02s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.03s/it]
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  2%|1         | 13/781 [00:00<00:39, 19.56it/s]
  2%|1         | 15/781 [00:00<00:39, 19.53it/s]
  2%|2         | 17/781 [00:00<00:39, 19.56it/s]
  2%|2         | 19/781 [00:00<00:38, 19.66it/s]
  3%|2         | 21/781 [00:01<00:39, 19.27it/s]
  3%|2         | 23/781 [00:01<00:38, 19.44it/s]
  3%|3         | 26/781 [00:01<00:38, 19.78it/s]
  4%|3         | 29/781 [00:01<00:37, 19.98it/s]
  4%|4         | 32/781 [00:01<00:37, 20.11it/s]
  4%|4         | 35/781 [00:01<00:37, 20.15it/s]
  5%|4         | 38/781 [00:01<00:37, 20.03it/s]
  5%|5         | 41/781 [00:02<00:36, 20.03it/s]
  6%|5         | 44/781 [00:02<00:36, 20.12it/s]
  6%|6         | 47/781 [00:02<00:36, 20.08it/s]
  6%|6         | 50/781 [00:02<00:36, 20.15it/s]
  7%|6         | 53/781 [00:02<00:36, 19.82it/s]
  7%|7         | 55/781 [00:02<00:36, 19.74it/s]
  7%|7         | 57/781 [00:02<00:37, 19.20it/s]
  8%|7         | 59/781 [00:03<00:38, 18.72it/s]
  8%|7         | 61/781 [00:03<00:38, 18.48it/s]
  8%|8         | 63/781 [00:03<00:39, 18.17it/s]
  8%|8         | 65/781 [00:03<00:39, 18.04it/s]
  9%|8         | 67/781 [00:03<00:39, 17.96it/s]
  9%|8         | 69/781 [00:03<00:39, 17.94it/s]
  9%|9         | 71/781 [00:03<00:39, 18.00it/s]
  9%|9         | 73/781 [00:03<00:39, 17.96it/s]
 10%|9         | 75/781 [00:03<00:39, 17.98it/s]
 10%|9         | 77/781 [00:04<00:39, 18.01it/s]
 10%|#         | 79/781 [00:04<00:39, 17.77it/s]
 10%|#         | 81/781 [00:04<00:39, 17.67it/s]
 11%|#         | 83/781 [00:04<00:39, 17.71it/s]
 11%|#         | 85/781 [00:04<00:39, 17.63it/s]
 11%|#1        | 87/781 [00:04<00:39, 17.72it/s]
 11%|#1        | 89/781 [00:04<00:38, 17.79it/s]
 12%|#1        | 91/781 [00:04<00:37, 18.23it/s]
 12%|#1        | 93/781 [00:04<00:37, 18.50it/s]
 12%|#2        | 95/781 [00:05<00:36, 18.65it/s]
 12%|#2        | 97/781 [00:05<00:36, 18.83it/s]
 13%|#2        | 99/781 [00:05<00:35, 18.97it/s]
 13%|#2        | 101/781 [00:05<00:35, 19.06it/s]
 13%|#3        | 103/781 [00:05<00:35, 19.14it/s]
 14%|#3        | 106/781 [00:05<00:34, 19.60it/s]
 14%|#3        | 108/781 [00:05<00:34, 19.50it/s]
 14%|#4        | 110/781 [00:05<00:34, 19.58it/s]
 14%|#4        | 113/781 [00:05<00:33, 19.80it/s]
 15%|#4        | 116/781 [00:06<00:33, 19.90it/s]
 15%|#5        | 118/781 [00:06<00:33, 19.87it/s]
 15%|#5        | 121/781 [00:06<00:33, 19.94it/s]
 16%|#5        | 123/781 [00:06<00:33, 19.88it/s]
 16%|#6        | 125/781 [00:06<00:32, 19.89it/s]
 16%|#6        | 128/781 [00:06<00:32, 19.98it/s]
 17%|#6        | 131/781 [00:06<00:32, 19.91it/s]
 17%|#7        | 134/781 [00:06<00:32, 20.13it/s]
 18%|#7        | 137/781 [00:07<00:31, 20.27it/s]
 18%|#7        | 140/781 [00:07<00:31, 20.18it/s]
 18%|#8        | 143/781 [00:07<00:31, 20.30it/s]
 19%|#8        | 146/781 [00:07<00:31, 20.36it/s]
 19%|#9        | 149/781 [00:07<00:30, 20.43it/s]
 19%|#9        | 152/781 [00:07<00:30, 20.44it/s]
 20%|#9        | 155/781 [00:08<00:30, 20.30it/s]
 20%|##        | 158/781 [00:08<00:31, 19.98it/s]
 21%|##        | 161/781 [00:08<00:31, 19.96it/s]
 21%|##        | 163/781 [00:08<00:31, 19.90it/s]
 21%|##1       | 166/781 [00:08<00:30, 20.15it/s]
 22%|##1       | 169/781 [00:08<00:30, 20.28it/s]
 22%|##2       | 172/781 [00:08<00:29, 20.42it/s]
 22%|##2       | 175/781 [00:09<00:29, 20.39it/s]
 23%|##2       | 178/781 [00:09<00:29, 20.40it/s]
 23%|##3       | 181/781 [00:09<00:29, 20.45it/s]
 24%|##3       | 184/781 [00:09<00:29, 20.55it/s]
 24%|##3       | 187/781 [00:09<00:29, 20.24it/s]
 24%|##4       | 190/781 [00:09<00:29, 20.36it/s]
 25%|##4       | 193/781 [00:09<00:28, 20.42it/s]
 25%|##5       | 196/781 [00:10<00:28, 20.44it/s]
 25%|##5       | 199/781 [00:10<00:28, 20.31it/s]
 26%|##5       | 202/781 [00:10<00:28, 20.24it/s]
 26%|##6       | 205/781 [00:10<00:28, 20.20it/s]
 27%|##6       | 208/781 [00:10<00:28, 20.20it/s]
 27%|##7       | 211/781 [00:10<00:28, 20.24it/s]
 27%|##7       | 214/781 [00:10<00:27, 20.27it/s]
 28%|##7       | 217/781 [00:11<00:27, 20.33it/s]
 28%|##8       | 220/781 [00:11<00:27, 20.37it/s]
 29%|##8       | 223/781 [00:11<00:27, 20.38it/s]
 29%|##8       | 226/781 [00:11<00:27, 20.22it/s]
 29%|##9       | 229/781 [00:11<00:27, 20.30it/s]
 30%|##9       | 232/781 [00:11<00:26, 20.36it/s]
 30%|###       | 235/781 [00:11<00:27, 20.08it/s]
 30%|###       | 238/781 [00:12<00:26, 20.22it/s]
 31%|###       | 241/781 [00:12<00:26, 20.20it/s]
 31%|###1      | 244/781 [00:12<00:26, 19.91it/s]
 32%|###1      | 247/781 [00:12<00:26, 20.03it/s]
 32%|###2      | 250/781 [00:12<00:26, 20.22it/s]
 32%|###2      | 253/781 [00:12<00:25, 20.33it/s]
 33%|###2      | 256/781 [00:13<00:25, 20.27it/s]
 33%|###3      | 259/781 [00:13<00:25, 20.27it/s]
 34%|###3      | 262/781 [00:13<00:25, 20.37it/s]
 34%|###3      | 265/781 [00:13<00:25, 20.23it/s]
 34%|###4      | 268/781 [00:13<00:25, 20.20it/s]
 35%|###4      | 271/781 [00:13<00:25, 20.10it/s]
 35%|###5      | 274/781 [00:13<00:25, 19.98it/s]
 35%|###5      | 276/781 [00:14<00:25, 19.84it/s]
 36%|###5      | 279/781 [00:14<00:25, 19.81it/s]
 36%|###5      | 281/781 [00:14<00:25, 19.78it/s]
 36%|###6      | 284/781 [00:14<00:24, 20.07it/s]
 37%|###6      | 287/781 [00:14<00:24, 20.16it/s]
 37%|###7      | 290/781 [00:14<00:24, 20.00it/s]
 38%|###7      | 293/781 [00:14<00:24, 20.11it/s]
 38%|###7      | 296/781 [00:14<00:24, 20.12it/s]
 38%|###8      | 299/781 [00:15<00:24, 19.68it/s]
 39%|###8      | 302/781 [00:15<00:24, 19.84it/s]
 39%|###9      | 305/781 [00:15<00:23, 20.03it/s]
 39%|###9      | 308/781 [00:15<00:23, 20.07it/s]
 40%|###9      | 311/781 [00:15<00:23, 19.85it/s]
 40%|####      | 313/781 [00:15<00:24, 19.34it/s]
 40%|####      | 315/781 [00:15<00:23, 19.46it/s]
 41%|####      | 317/781 [00:16<00:24, 18.98it/s]
 41%|####      | 319/781 [00:16<00:24, 19.20it/s]
 41%|####1     | 321/781 [00:16<00:24, 19.01it/s]
 41%|####1     | 323/781 [00:16<00:23, 19.23it/s]
 42%|####1     | 325/781 [00:16<00:24, 18.60it/s]
 42%|####1     | 327/781 [00:16<00:24, 18.90it/s]
 42%|####2     | 329/781 [00:16<00:23, 19.15it/s]
 42%|####2     | 331/781 [00:16<00:23, 19.38it/s]
 43%|####2     | 334/781 [00:16<00:22, 19.78it/s]
 43%|####3     | 336/781 [00:17<00:22, 19.59it/s]
 43%|####3     | 338/781 [00:17<00:22, 19.63it/s]
 44%|####3     | 340/781 [00:17<00:22, 19.72it/s]
 44%|####3     | 342/781 [00:17<00:22, 19.78it/s]
 44%|####4     | 345/781 [00:17<00:21, 20.08it/s]
 45%|####4     | 348/781 [00:17<00:21, 20.24it/s]
 45%|####4     | 351/781 [00:17<00:21, 20.37it/s]
 45%|####5     | 354/781 [00:17<00:20, 20.43it/s]
 46%|####5     | 357/781 [00:18<00:20, 20.48it/s]
 46%|####6     | 360/781 [00:18<00:20, 20.34it/s]
 46%|####6     | 363/781 [00:18<00:20, 20.28it/s]
 47%|####6     | 366/781 [00:18<00:20, 20.20it/s]
 47%|####7     | 369/781 [00:18<00:20, 20.21it/s]
 48%|####7     | 372/781 [00:18<00:20, 20.33it/s]
 48%|####8     | 375/781 [00:18<00:20, 20.28it/s]
 48%|####8     | 378/781 [00:19<00:19, 20.28it/s]
 49%|####8     | 381/781 [00:19<00:19, 20.27it/s]
 49%|####9     | 384/781 [00:19<00:19, 20.27it/s]
 50%|####9     | 387/781 [00:19<00:19, 20.13it/s]
 50%|####9     | 390/781 [00:19<00:19, 20.25it/s]
 50%|#####     | 393/781 [00:19<00:19, 20.39it/s]
 51%|#####     | 396/781 [00:20<00:18, 20.42it/s]
 51%|#####1    | 399/781 [00:20<00:18, 20.27it/s]
 51%|#####1    | 402/781 [00:20<00:18, 20.30it/s]
 52%|#####1    | 405/781 [00:20<00:18, 20.33it/s]
 52%|#####2    | 408/781 [00:20<00:18, 20.27it/s]
 53%|#####2    | 411/781 [00:20<00:18, 20.17it/s]
 53%|#####3    | 414/781 [00:20<00:18, 20.25it/s]
 53%|#####3    | 417/781 [00:21<00:17, 20.39it/s]
 54%|#####3    | 420/781 [00:21<00:17, 20.31it/s]
 54%|#####4    | 423/781 [00:21<00:17, 20.30it/s]
 55%|#####4    | 426/781 [00:21<00:17, 20.30it/s]
 55%|#####4    | 429/781 [00:21<00:26, 13.14it/s]
 55%|#####5    | 432/781 [00:22<00:23, 14.73it/s]
 56%|#####5    | 435/781 [00:22<00:21, 16.00it/s]
 56%|#####5    | 437/781 [00:22<00:20, 16.74it/s]
 56%|#####6    | 440/781 [00:22<00:19, 17.76it/s]
 57%|#####6    | 443/781 [00:22<00:18, 18.56it/s]
 57%|#####7    | 446/781 [00:22<00:17, 19.14it/s]
 57%|#####7    | 449/781 [00:22<00:17, 19.41it/s]
 58%|#####7    | 452/781 [00:23<00:16, 19.71it/s]
 58%|#####8    | 455/781 [00:23<00:16, 19.92it/s]
 59%|#####8    | 458/781 [00:23<00:16, 20.06it/s]
 59%|#####9    | 461/781 [00:23<00:15, 20.08it/s]
 59%|#####9    | 464/781 [00:23<00:16, 19.58it/s]
 60%|#####9    | 466/781 [00:23<00:16, 19.46it/s]
 60%|#####9    | 468/781 [00:23<00:16, 19.31it/s]
 60%|######    | 470/781 [00:23<00:16, 18.44it/s]
 60%|######    | 472/781 [00:24<00:16, 18.41it/s]
 61%|######    | 474/781 [00:24<00:16, 18.59it/s]
 61%|######    | 476/781 [00:24<00:16, 18.80it/s]
 61%|######1   | 478/781 [00:24<00:15, 19.01it/s]
 61%|######1   | 480/781 [00:24<00:15, 19.02it/s]
 62%|######1   | 482/781 [00:24<00:15, 19.14it/s]
 62%|######1   | 484/781 [00:24<00:15, 18.91it/s]
 62%|######2   | 486/781 [00:24<00:15, 18.58it/s]
 62%|######2   | 488/781 [00:24<00:15, 18.32it/s]
 63%|######2   | 490/781 [00:25<00:15, 18.27it/s]
 63%|######2   | 492/781 [00:25<00:15, 18.22it/s]
 63%|######3   | 494/781 [00:25<00:15, 18.21it/s]
 64%|######3   | 496/781 [00:25<00:15, 18.12it/s]
 64%|######3   | 498/781 [00:25<00:15, 18.06it/s]
 64%|######4   | 500/781 [00:25<00:15, 18.05it/s]
 64%|######4   | 502/781 [00:25<00:15, 18.13it/s]
 65%|######4   | 504/781 [00:25<00:15, 18.16it/s]
 65%|######4   | 506/781 [00:25<00:15, 18.14it/s]
 65%|######5   | 508/781 [00:26<00:15, 18.16it/s]
 65%|######5   | 510/781 [00:26<00:14, 18.18it/s]
 66%|######5   | 512/781 [00:26<00:14, 18.06it/s]
 66%|######5   | 514/781 [00:26<00:14, 18.05it/s]
 66%|######6   | 516/781 [00:26<00:14, 18.14it/s]
 66%|######6   | 518/781 [00:26<00:14, 18.19it/s]
 67%|######6   | 520/781 [00:26<00:14, 18.22it/s]
 67%|######6   | 522/781 [00:26<00:14, 18.16it/s]
 67%|######7   | 524/781 [00:26<00:14, 18.18it/s]
 67%|######7   | 526/781 [00:27<00:14, 18.14it/s]
 68%|######7   | 528/781 [00:27<00:13, 18.12it/s]
 68%|######7   | 530/781 [00:27<00:14, 17.89it/s]
 68%|######8   | 532/781 [00:27<00:13, 17.85it/s]
 68%|######8   | 534/781 [00:27<00:13, 17.83it/s]
 69%|######8   | 536/781 [00:27<00:13, 17.97it/s]
 69%|######8   | 538/781 [00:27<00:13, 18.03it/s]
 69%|######9   | 540/781 [00:27<00:13, 18.12it/s]
 69%|######9   | 542/781 [00:27<00:13, 18.19it/s]
 70%|######9   | 544/781 [00:28<00:12, 18.25it/s]
 70%|######9   | 546/781 [00:28<00:12, 18.27it/s]
 70%|#######   | 548/781 [00:28<00:12, 18.23it/s]
 70%|#######   | 550/781 [00:28<00:12, 18.21it/s]
 71%|#######   | 552/781 [00:28<00:12, 17.69it/s]
 71%|#######   | 554/781 [00:28<00:13, 17.31it/s]
 71%|#######1  | 556/781 [00:28<00:12, 17.46it/s]
 71%|#######1  | 558/781 [00:28<00:12, 17.65it/s]
 72%|#######1  | 560/781 [00:28<00:12, 17.82it/s]
 72%|#######1  | 562/781 [00:29<00:12, 17.88it/s]
 72%|#######2  | 564/781 [00:29<00:12, 17.95it/s]
 72%|#######2  | 566/781 [00:29<00:11, 17.99it/s]
 73%|#######2  | 568/781 [00:29<00:11, 18.03it/s]
 73%|#######2  | 570/781 [00:29<00:11, 17.84it/s]
 73%|#######3  | 572/781 [00:29<00:11, 17.94it/s]
 73%|#######3  | 574/781 [00:29<00:11, 18.02it/s]
 74%|#######3  | 576/781 [00:29<00:11, 18.05it/s]
 74%|#######4  | 578/781 [00:29<00:11, 17.92it/s]
 74%|#######4  | 580/781 [00:30<00:11, 17.88it/s]
 75%|#######4  | 582/781 [00:30<00:11, 17.86it/s]
 75%|#######4  | 584/781 [00:30<00:11, 17.76it/s]
 75%|#######5  | 586/781 [00:30<00:10, 17.74it/s]
 75%|#######5  | 588/781 [00:30<00:10, 17.70it/s]
 76%|#######5  | 590/781 [00:30<00:10, 17.99it/s]
 76%|#######5  | 592/781 [00:30<00:10, 17.82it/s]
 76%|#######6  | 594/781 [00:30<00:10, 17.74it/s]
 76%|#######6  | 596/781 [00:30<00:10, 17.75it/s]
 77%|#######6  | 598/781 [00:31<00:10, 17.89it/s]
 77%|#######6  | 600/781 [00:31<00:10, 17.94it/s]
 77%|#######7  | 602/781 [00:31<00:09, 17.96it/s]
 77%|#######7  | 604/781 [00:31<00:09, 17.86it/s]
 78%|#######7  | 606/781 [00:31<00:09, 17.88it/s]
 78%|#######7  | 608/781 [00:31<00:09, 17.85it/s]
 78%|#######8  | 610/781 [00:31<00:09, 18.01it/s]
 78%|#######8  | 612/781 [00:31<00:09, 18.11it/s]
 79%|#######8  | 614/781 [00:31<00:09, 18.02it/s]
 79%|#######8  | 616/781 [00:32<00:09, 18.11it/s]
 79%|#######9  | 618/781 [00:32<00:08, 18.14it/s]
 79%|#######9  | 620/781 [00:32<00:08, 18.17it/s]
 80%|#######9  | 622/781 [00:32<00:08, 18.13it/s]
 80%|#######9  | 624/781 [00:32<00:08, 18.01it/s]
 80%|########  | 626/781 [00:32<00:08, 18.01it/s]
 80%|########  | 628/781 [00:32<00:08, 18.02it/s]
 81%|########  | 630/781 [00:32<00:08, 18.08it/s]
 81%|########  | 632/781 [00:32<00:08, 18.05it/s]
 81%|########1 | 634/781 [00:33<00:08, 17.96it/s]
 81%|########1 | 636/781 [00:33<00:08, 18.05it/s]
 82%|########1 | 638/781 [00:33<00:07, 18.06it/s]
 82%|########1 | 640/781 [00:33<00:07, 18.05it/s]
 82%|########2 | 642/781 [00:33<00:07, 17.92it/s]
 82%|########2 | 644/781 [00:33<00:07, 17.86it/s]
 83%|########2 | 646/781 [00:33<00:07, 17.92it/s]
 83%|########2 | 648/781 [00:33<00:07, 17.75it/s]
 83%|########3 | 650/781 [00:33<00:07, 17.80it/s]
 83%|########3 | 652/781 [00:34<00:07, 17.48it/s]
 84%|########3 | 654/781 [00:34<00:07, 17.53it/s]
 84%|########3 | 656/781 [00:34<00:07, 17.68it/s]
 84%|########4 | 658/781 [00:34<00:06, 17.73it/s]
 85%|########4 | 660/781 [00:34<00:06, 17.78it/s]
 85%|########4 | 662/781 [00:34<00:06, 17.90it/s]
 85%|########5 | 664/781 [00:34<00:06, 17.84it/s]
 85%|########5 | 666/781 [00:34<00:06, 17.75it/s]
 86%|########5 | 668/781 [00:34<00:06, 17.72it/s]
 86%|########5 | 670/781 [00:35<00:06, 17.59it/s]
 86%|########6 | 672/781 [00:35<00:06, 17.62it/s]
 86%|########6 | 674/781 [00:35<00:06, 17.61it/s]
 87%|########6 | 676/781 [00:35<00:05, 17.75it/s]
 87%|########6 | 678/781 [00:35<00:05, 17.76it/s]
 87%|########7 | 680/781 [00:35<00:05, 17.66it/s]
 87%|########7 | 682/781 [00:35<00:05, 17.68it/s]
 88%|########7 | 684/781 [00:35<00:05, 17.71it/s]
 88%|########7 | 686/781 [00:35<00:05, 17.63it/s]
 88%|########8 | 688/781 [00:36<00:05, 17.73it/s]
 88%|########8 | 690/781 [00:36<00:05, 17.86it/s]
 89%|########8 | 692/781 [00:36<00:04, 17.95it/s]
 89%|########8 | 694/781 [00:36<00:04, 18.02it/s]
 89%|########9 | 696/781 [00:36<00:04, 18.08it/s]
 89%|########9 | 698/781 [00:36<00:04, 18.09it/s]
 90%|########9 | 700/781 [00:36<00:04, 18.09it/s]
 90%|########9 | 702/781 [00:36<00:04, 18.13it/s]
 90%|######### | 704/781 [00:36<00:04, 18.11it/s]
 90%|######### | 706/781 [00:37<00:04, 18.14it/s]
 91%|######### | 708/781 [00:37<00:04, 18.15it/s]
 91%|######### | 710/781 [00:37<00:03, 17.81it/s]
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100%|##########| 781/781 [00:41<00:00, 18.91it/s]




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 45%|####4     | 70/157 [00:04<00:05, 16.53it/s]
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 47%|####7     | 74/157 [00:04<00:05, 16.35it/s]
 48%|####8     | 76/157 [00:04<00:04, 16.31it/s]
 50%|####9     | 78/157 [00:04<00:04, 16.49it/s]
 51%|#####     | 80/157 [00:04<00:04, 16.56it/s]
 52%|#####2    | 82/157 [00:04<00:04, 16.71it/s]
 54%|#####3    | 84/157 [00:05<00:04, 16.69it/s]
 55%|#####4    | 86/157 [00:05<00:04, 16.75it/s]
 56%|#####6    | 88/157 [00:05<00:04, 16.58it/s]
 57%|#####7    | 90/157 [00:05<00:04, 16.71it/s]
 59%|#####8    | 92/157 [00:05<00:03, 16.78it/s]
 60%|#####9    | 94/157 [00:05<00:03, 16.83it/s]
 61%|######1   | 96/157 [00:05<00:03, 16.88it/s]
 62%|######2   | 98/157 [00:05<00:03, 16.89it/s]
 64%|######3   | 100/157 [00:06<00:03, 16.90it/s]
 65%|######4   | 102/157 [00:06<00:03, 16.86it/s]
 66%|######6   | 104/157 [00:06<00:03, 16.93it/s]
 68%|######7   | 106/157 [00:06<00:03, 16.72it/s]
 69%|######8   | 108/157 [00:06<00:02, 16.57it/s]
 70%|#######   | 110/157 [00:06<00:02, 16.71it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.76it/s]
 73%|#######2  | 114/157 [00:06<00:02, 16.71it/s]
 74%|#######3  | 116/157 [00:07<00:02, 16.69it/s]
 75%|#######5  | 118/157 [00:07<00:02, 16.65it/s]
 76%|#######6  | 120/157 [00:07<00:02, 16.63it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.72it/s]
 79%|#######8  | 124/157 [00:07<00:01, 16.79it/s]
 80%|########  | 126/157 [00:07<00:01, 16.88it/s]
 82%|########1 | 128/157 [00:07<00:01, 16.97it/s]
 83%|########2 | 130/157 [00:07<00:01, 16.98it/s]
 84%|########4 | 132/157 [00:07<00:01, 16.99it/s]
 85%|########5 | 134/157 [00:08<00:01, 17.03it/s]
 87%|########6 | 136/157 [00:08<00:01, 17.05it/s]
 88%|########7 | 138/157 [00:08<00:01, 17.05it/s]
 89%|########9 | 140/157 [00:08<00:00, 17.05it/s]
 90%|######### | 142/157 [00:08<00:00, 16.96it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.87it/s]
 93%|#########2| 146/157 [00:08<00:00, 16.88it/s]
 94%|#########4| 148/157 [00:08<00:00, 16.94it/s]
 96%|#########5| 150/157 [00:09<00:00, 16.79it/s]
 97%|#########6| 152/157 [00:09<00:00, 16.91it/s]
 98%|#########8| 154/157 [00:09<00:00, 16.84it/s]
 99%|#########9| 156/157 [00:09<00:00, 16.90it/s]
100%|##########| 157/157 [00:09<00:00, 16.68it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:44, 17.54it/s]
  1%|          | 4/781 [00:00<00:47, 16.36it/s]
  1%|          | 6/781 [00:00<00:44, 17.30it/s]
  1%|1         | 8/781 [00:00<00:43, 17.73it/s]
  1%|1         | 10/781 [00:00<00:42, 18.05it/s]
  2%|1         | 12/781 [00:00<00:42, 18.15it/s]
  2%|1         | 14/781 [00:00<00:41, 18.36it/s]
  2%|2         | 16/781 [00:00<00:41, 18.57it/s]
  2%|2         | 18/781 [00:00<00:41, 18.59it/s]
  3%|2         | 20/781 [00:01<00:41, 18.45it/s]
  3%|2         | 22/781 [00:01<00:40, 18.54it/s]
  3%|3         | 24/781 [00:01<00:41, 18.41it/s]
  3%|3         | 26/781 [00:01<00:40, 18.50it/s]
  4%|3         | 28/781 [00:01<00:40, 18.69it/s]
  4%|3         | 30/781 [00:01<00:40, 18.64it/s]
  4%|4         | 32/781 [00:01<00:40, 18.33it/s]
  4%|4         | 34/781 [00:01<00:40, 18.62it/s]
  5%|4         | 36/781 [00:01<00:39, 18.74it/s]
  5%|4         | 38/781 [00:02<00:39, 18.81it/s]
  5%|5         | 40/781 [00:02<00:40, 18.25it/s]
  5%|5         | 42/781 [00:02<00:39, 18.58it/s]
  6%|5         | 44/781 [00:02<00:38, 18.96it/s]
  6%|5         | 46/781 [00:02<00:38, 19.23it/s]
  6%|6         | 48/781 [00:02<00:37, 19.31it/s]
  6%|6         | 50/781 [00:02<00:37, 19.29it/s]
  7%|6         | 52/781 [00:02<00:37, 19.36it/s]
  7%|6         | 54/781 [00:02<00:37, 19.47it/s]
  7%|7         | 56/781 [00:03<00:37, 19.40it/s]
  7%|7         | 58/781 [00:03<00:37, 19.34it/s]
  8%|7         | 60/781 [00:03<00:37, 19.26it/s]
  8%|7         | 62/781 [00:03<00:37, 19.12it/s]
  8%|8         | 64/781 [00:03<00:37, 18.88it/s]
  8%|8         | 66/781 [00:03<00:37, 18.95it/s]
  9%|8         | 68/781 [00:03<00:37, 18.94it/s]
  9%|8         | 70/781 [00:03<00:38, 18.63it/s]
  9%|9         | 72/781 [00:03<00:38, 18.64it/s]
  9%|9         | 74/781 [00:03<00:37, 18.76it/s]
 10%|9         | 76/781 [00:04<00:37, 18.70it/s]
 10%|9         | 78/781 [00:04<00:37, 18.87it/s]
 10%|#         | 80/781 [00:04<00:37, 18.85it/s]
 10%|#         | 82/781 [00:04<00:37, 18.82it/s]
 11%|#         | 84/781 [00:04<00:36, 19.05it/s]
 11%|#1        | 87/781 [00:04<00:35, 19.40it/s]
 11%|#1        | 89/781 [00:04<00:35, 19.32it/s]
 12%|#1        | 91/781 [00:04<00:35, 19.19it/s]
 12%|#1        | 93/781 [00:04<00:35, 19.40it/s]
 12%|#2        | 95/781 [00:05<00:35, 19.51it/s]
 12%|#2        | 97/781 [00:05<00:35, 19.44it/s]
 13%|#2        | 99/781 [00:05<00:34, 19.57it/s]
 13%|#2        | 101/781 [00:05<00:34, 19.64it/s]
 13%|#3        | 103/781 [00:05<00:34, 19.56it/s]
 13%|#3        | 105/781 [00:05<00:34, 19.61it/s]
 14%|#3        | 107/781 [00:05<00:34, 19.58it/s]
 14%|#3        | 109/781 [00:05<00:34, 19.60it/s]
 14%|#4        | 111/781 [00:05<00:34, 19.64it/s]
 14%|#4        | 113/781 [00:05<00:34, 19.59it/s]
 15%|#4        | 115/781 [00:06<00:33, 19.68it/s]
 15%|#4        | 117/781 [00:06<00:33, 19.75it/s]
 15%|#5        | 119/781 [00:06<00:33, 19.76it/s]
 15%|#5        | 121/781 [00:06<00:33, 19.77it/s]
 16%|#5        | 123/781 [00:06<00:33, 19.61it/s]
 16%|#6        | 125/781 [00:06<00:33, 19.70it/s]
 16%|#6        | 127/781 [00:06<00:33, 19.74it/s]
 17%|#6        | 129/781 [00:06<00:33, 19.76it/s]
 17%|#6        | 131/781 [00:06<00:33, 19.66it/s]
 17%|#7        | 133/781 [00:06<00:32, 19.68it/s]
 17%|#7        | 135/781 [00:07<00:32, 19.68it/s]
 18%|#7        | 137/781 [00:07<00:32, 19.75it/s]
 18%|#7        | 139/781 [00:07<00:32, 19.73it/s]
 18%|#8        | 141/781 [00:07<00:32, 19.47it/s]
 18%|#8        | 143/781 [00:07<00:32, 19.52it/s]
 19%|#8        | 145/781 [00:07<00:32, 19.54it/s]
 19%|#8        | 147/781 [00:07<00:32, 19.61it/s]
 19%|#9        | 149/781 [00:07<00:32, 19.63it/s]
 19%|#9        | 151/781 [00:07<00:32, 19.52it/s]
 20%|#9        | 153/781 [00:08<00:32, 19.41it/s]
 20%|#9        | 155/781 [00:08<00:32, 19.39it/s]
 20%|##        | 157/781 [00:08<00:32, 19.36it/s]
 20%|##        | 159/781 [00:08<00:31, 19.49it/s]
 21%|##        | 161/781 [00:08<00:31, 19.49it/s]
 21%|##        | 163/781 [00:08<00:32, 19.29it/s]
 21%|##1       | 165/781 [00:08<00:31, 19.46it/s]
 21%|##1       | 167/781 [00:08<00:31, 19.56it/s]
 22%|##1       | 169/781 [00:08<00:31, 19.63it/s]
 22%|##1       | 171/781 [00:08<00:31, 19.32it/s]
 22%|##2       | 173/781 [00:09<00:31, 19.37it/s]
 22%|##2       | 175/781 [00:09<00:31, 19.01it/s]
 23%|##2       | 177/781 [00:09<00:31, 19.16it/s]
 23%|##2       | 179/781 [00:09<00:31, 19.37it/s]
 23%|##3       | 181/781 [00:09<00:30, 19.40it/s]
 23%|##3       | 183/781 [00:09<00:30, 19.49it/s]
 24%|##3       | 185/781 [00:09<00:30, 19.57it/s]
 24%|##3       | 187/781 [00:09<00:30, 19.63it/s]
 24%|##4       | 189/781 [00:09<00:30, 19.68it/s]
 24%|##4       | 191/781 [00:09<00:29, 19.74it/s]
 25%|##4       | 193/781 [00:10<00:29, 19.77it/s]
 25%|##4       | 195/781 [00:10<00:29, 19.63it/s]
 25%|##5       | 197/781 [00:10<00:29, 19.69it/s]
 25%|##5       | 199/781 [00:10<00:29, 19.56it/s]
 26%|##5       | 201/781 [00:10<00:29, 19.36it/s]
 26%|##5       | 203/781 [00:10<00:29, 19.54it/s]
 26%|##6       | 205/781 [00:10<00:29, 19.49it/s]
 27%|##6       | 207/781 [00:10<00:29, 19.55it/s]
 27%|##6       | 209/781 [00:10<00:29, 19.61it/s]
 27%|##7       | 211/781 [00:10<00:29, 19.33it/s]
 27%|##7       | 213/781 [00:11<00:29, 19.24it/s]
 28%|##7       | 215/781 [00:11<00:29, 19.30it/s]
 28%|##7       | 217/781 [00:11<00:29, 19.29it/s]
 28%|##8       | 219/781 [00:11<00:28, 19.42it/s]
 28%|##8       | 221/781 [00:11<00:28, 19.45it/s]
 29%|##8       | 223/781 [00:11<00:29, 19.13it/s]
 29%|##8       | 225/781 [00:11<00:29, 19.05it/s]
 29%|##9       | 227/781 [00:11<00:29, 19.02it/s]
 29%|##9       | 229/781 [00:11<00:28, 19.29it/s]
 30%|##9       | 231/781 [00:12<00:28, 19.44it/s]
 30%|##9       | 233/781 [00:12<00:28, 19.55it/s]
 30%|###       | 236/781 [00:12<00:27, 19.70it/s]
 30%|###       | 238/781 [00:12<00:27, 19.46it/s]
 31%|###       | 240/781 [00:12<00:28, 19.27it/s]
 31%|###       | 242/781 [00:12<00:28, 19.18it/s]
 31%|###1      | 244/781 [00:12<00:28, 19.08it/s]
 31%|###1      | 246/781 [00:12<00:27, 19.18it/s]
 32%|###1      | 248/781 [00:12<00:27, 19.32it/s]
 32%|###2      | 250/781 [00:13<00:27, 19.38it/s]
 32%|###2      | 252/781 [00:13<00:27, 19.48it/s]
 33%|###2      | 254/781 [00:13<00:27, 19.04it/s]
 33%|###2      | 256/781 [00:13<00:27, 19.21it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.34it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.27it/s]
 34%|###3      | 263/781 [00:13<00:26, 19.60it/s]
 34%|###3      | 265/781 [00:13<00:26, 19.46it/s]
 34%|###4      | 268/781 [00:13<00:26, 19.71it/s]
 35%|###4      | 271/781 [00:14<00:25, 19.80it/s]
 35%|###4      | 273/781 [00:14<00:25, 19.82it/s]
 35%|###5      | 275/781 [00:14<00:25, 19.79it/s]
 35%|###5      | 277/781 [00:14<00:25, 19.83it/s]
 36%|###5      | 279/781 [00:14<00:25, 19.82it/s]
 36%|###5      | 281/781 [00:14<00:25, 19.87it/s]
 36%|###6      | 283/781 [00:14<00:25, 19.85it/s]
 36%|###6      | 285/781 [00:14<00:24, 19.88it/s]
 37%|###6      | 287/781 [00:14<00:24, 19.91it/s]
 37%|###7      | 289/781 [00:14<00:24, 19.82it/s]
 37%|###7      | 291/781 [00:15<00:24, 19.76it/s]
 38%|###7      | 293/781 [00:15<00:24, 19.69it/s]
 38%|###7      | 295/781 [00:15<00:24, 19.60it/s]
 38%|###8      | 297/781 [00:15<00:25, 19.30it/s]
 38%|###8      | 299/781 [00:15<00:24, 19.50it/s]
 39%|###8      | 302/781 [00:15<00:24, 19.66it/s]
 39%|###8      | 304/781 [00:15<00:24, 19.45it/s]
 39%|###9      | 306/781 [00:15<00:24, 19.50it/s]
 39%|###9      | 308/781 [00:15<00:24, 19.60it/s]
 40%|###9      | 311/781 [00:16<00:23, 19.75it/s]
 40%|####      | 313/781 [00:16<00:23, 19.77it/s]
 40%|####      | 315/781 [00:16<00:23, 19.80it/s]
 41%|####      | 317/781 [00:16<00:23, 19.83it/s]
 41%|####      | 319/781 [00:16<00:23, 19.83it/s]
 41%|####1     | 321/781 [00:16<00:23, 19.64it/s]
 41%|####1     | 323/781 [00:16<00:23, 19.69it/s]
 42%|####1     | 325/781 [00:16<00:23, 19.54it/s]
 42%|####1     | 327/781 [00:16<00:23, 19.48it/s]
 42%|####2     | 329/781 [00:17<00:23, 19.60it/s]
 42%|####2     | 331/781 [00:17<00:23, 19.53it/s]
 43%|####2     | 333/781 [00:17<00:22, 19.58it/s]
 43%|####2     | 335/781 [00:17<00:23, 19.27it/s]
 43%|####3     | 337/781 [00:17<00:23, 19.27it/s]
 43%|####3     | 339/781 [00:17<00:22, 19.34it/s]
 44%|####3     | 341/781 [00:17<00:22, 19.33it/s]
 44%|####3     | 343/781 [00:17<00:22, 19.49it/s]
 44%|####4     | 345/781 [00:17<00:22, 19.63it/s]
 44%|####4     | 347/781 [00:17<00:22, 19.61it/s]
 45%|####4     | 349/781 [00:18<00:22, 19.57it/s]
 45%|####5     | 352/781 [00:18<00:21, 19.74it/s]
 45%|####5     | 354/781 [00:18<00:21, 19.72it/s]
 46%|####5     | 356/781 [00:18<00:21, 19.64it/s]
 46%|####5     | 358/781 [00:18<00:21, 19.42it/s]
 46%|####6     | 360/781 [00:18<00:21, 19.47it/s]
 46%|####6     | 362/781 [00:18<00:21, 19.62it/s]
 47%|####6     | 364/781 [00:18<00:21, 19.72it/s]
 47%|####6     | 366/781 [00:18<00:21, 19.40it/s]
 47%|####7     | 368/781 [00:19<00:21, 19.48it/s]
 47%|####7     | 370/781 [00:19<00:20, 19.62it/s]
 48%|####7     | 372/781 [00:19<00:20, 19.71it/s]
 48%|####7     | 374/781 [00:19<00:20, 19.73it/s]
 48%|####8     | 376/781 [00:19<00:20, 19.77it/s]
 48%|####8     | 378/781 [00:19<00:20, 19.80it/s]
 49%|####8     | 380/781 [00:19<00:20, 19.81it/s]
 49%|####8     | 382/781 [00:19<00:20, 19.63it/s]
 49%|####9     | 384/781 [00:19<00:20, 19.61it/s]
 49%|####9     | 386/781 [00:19<00:20, 19.73it/s]
 50%|####9     | 388/781 [00:20<00:20, 19.51it/s]
 50%|####9     | 390/781 [00:20<00:20, 19.46it/s]
 50%|#####     | 392/781 [00:20<00:20, 19.29it/s]
 50%|#####     | 394/781 [00:20<00:20, 19.00it/s]
 51%|#####     | 396/781 [00:20<00:20, 18.75it/s]
 51%|#####     | 398/781 [00:20<00:20, 18.45it/s]
 51%|#####1    | 400/781 [00:20<00:20, 18.50it/s]
 51%|#####1    | 402/781 [00:20<00:20, 18.74it/s]
 52%|#####1    | 404/781 [00:20<00:20, 18.74it/s]
 52%|#####1    | 406/781 [00:21<00:20, 18.53it/s]
 52%|#####2    | 408/781 [00:21<00:20, 18.64it/s]
 52%|#####2    | 410/781 [00:21<00:20, 18.49it/s]
 53%|#####2    | 412/781 [00:21<00:20, 18.44it/s]
 53%|#####3    | 414/781 [00:21<00:19, 18.66it/s]
 53%|#####3    | 416/781 [00:21<00:19, 18.81it/s]
 54%|#####3    | 418/781 [00:21<00:19, 18.84it/s]
 54%|#####3    | 420/781 [00:21<00:19, 18.31it/s]
 54%|#####4    | 422/781 [00:21<00:19, 18.30it/s]
 54%|#####4    | 424/781 [00:21<00:19, 18.32it/s]
 55%|#####4    | 426/781 [00:22<00:19, 18.32it/s]
 55%|#####4    | 428/781 [00:22<00:19, 18.30it/s]
 55%|#####5    | 430/781 [00:22<00:19, 18.07it/s]
 55%|#####5    | 432/781 [00:22<00:19, 18.09it/s]
 56%|#####5    | 434/781 [00:22<00:19, 18.12it/s]
 56%|#####5    | 436/781 [00:22<00:18, 18.22it/s]
 56%|#####6    | 438/781 [00:22<00:18, 18.38it/s]
 56%|#####6    | 440/781 [00:22<00:18, 18.49it/s]
 57%|#####6    | 442/781 [00:22<00:18, 18.60it/s]
 57%|#####6    | 444/781 [00:23<00:18, 18.54it/s]
 57%|#####7    | 446/781 [00:23<00:17, 18.73it/s]
 57%|#####7    | 448/781 [00:23<00:17, 18.79it/s]
 58%|#####7    | 450/781 [00:23<00:17, 18.80it/s]
 58%|#####7    | 452/781 [00:23<00:17, 18.73it/s]
 58%|#####8    | 454/781 [00:23<00:17, 18.76it/s]
 58%|#####8    | 456/781 [00:23<00:17, 18.75it/s]
 59%|#####8    | 458/781 [00:23<00:17, 18.87it/s]
 59%|#####8    | 460/781 [00:23<00:16, 19.04it/s]
 59%|#####9    | 462/781 [00:24<00:16, 19.12it/s]
 59%|#####9    | 464/781 [00:24<00:16, 19.01it/s]
 60%|#####9    | 466/781 [00:24<00:16, 18.98it/s]
 60%|#####9    | 468/781 [00:24<00:16, 19.02it/s]
 60%|######    | 470/781 [00:24<00:16, 19.14it/s]
 60%|######    | 472/781 [00:24<00:16, 19.10it/s]
 61%|######    | 474/781 [00:24<00:16, 18.92it/s]
 61%|######    | 476/781 [00:24<00:16, 18.56it/s]
 61%|######1   | 478/781 [00:24<00:16, 18.73it/s]
 61%|######1   | 480/781 [00:24<00:15, 18.94it/s]
 62%|######1   | 482/781 [00:25<00:15, 19.11it/s]
 62%|######1   | 484/781 [00:25<00:15, 19.21it/s]
 62%|######2   | 486/781 [00:25<00:15, 19.28it/s]
 62%|######2   | 488/781 [00:25<00:15, 19.32it/s]
 63%|######2   | 490/781 [00:25<00:15, 19.15it/s]
 63%|######2   | 492/781 [00:25<00:15, 19.09it/s]
 63%|######3   | 494/781 [00:25<00:15, 18.95it/s]
 64%|######3   | 496/781 [00:25<00:14, 19.08it/s]
 64%|######3   | 498/781 [00:25<00:14, 19.16it/s]
 64%|######4   | 500/781 [00:26<00:14, 19.20it/s]
 64%|######4   | 502/781 [00:26<00:14, 19.08it/s]
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100%|##########| 781/781 [00:40<00:00, 19.29it/s]




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Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.18s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.22s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.22s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.22s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.22s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.22s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.22s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.18s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00it/s]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:12<00:00, 12.62s/it]
100%|##########| 1/1 [00:12<00:00, 12.62s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:11, 13.64it/s]
  3%|2         | 4/157 [00:00<00:10, 15.26it/s]
  4%|3         | 6/157 [00:00<00:09, 16.33it/s]
  5%|5         | 8/157 [00:00<00:08, 16.93it/s]
  6%|6         | 10/157 [00:00<00:08, 17.15it/s]
  8%|7         | 12/157 [00:00<00:08, 17.13it/s]
  9%|8         | 14/157 [00:00<00:08, 17.26it/s]
 10%|#         | 16/157 [00:00<00:08, 17.50it/s]
 11%|#1        | 18/157 [00:01<00:07, 17.42it/s]
 13%|#2        | 20/157 [00:01<00:07, 17.65it/s]
 14%|#4        | 22/157 [00:01<00:07, 17.77it/s]
 15%|#5        | 24/157 [00:01<00:07, 17.81it/s]
 17%|#6        | 26/157 [00:01<00:07, 17.84it/s]
 18%|#7        | 28/157 [00:01<00:07, 17.26it/s]
 19%|#9        | 30/157 [00:01<00:07, 17.16it/s]
 20%|##        | 32/157 [00:01<00:07, 16.63it/s]
 22%|##1       | 34/157 [00:02<00:07, 16.45it/s]
 23%|##2       | 36/157 [00:02<00:07, 16.30it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.01it/s]
 25%|##5       | 40/157 [00:02<00:07, 15.86it/s]
 27%|##6       | 42/157 [00:02<00:07, 15.59it/s]
 28%|##8       | 44/157 [00:02<00:07, 15.29it/s]
 29%|##9       | 46/157 [00:02<00:07, 15.26it/s]
 31%|###       | 48/157 [00:02<00:07, 15.41it/s]
 32%|###1      | 50/157 [00:03<00:06, 15.53it/s]
 33%|###3      | 52/157 [00:03<00:06, 15.65it/s]
 34%|###4      | 54/157 [00:03<00:06, 15.61it/s]
 36%|###5      | 56/157 [00:03<00:06, 15.55it/s]
 37%|###6      | 58/157 [00:03<00:06, 15.59it/s]
 38%|###8      | 60/157 [00:03<00:06, 15.62it/s]
 39%|###9      | 62/157 [00:03<00:06, 15.55it/s]
 41%|####      | 64/157 [00:03<00:05, 15.58it/s]
 42%|####2     | 66/157 [00:04<00:05, 15.68it/s]
 43%|####3     | 68/157 [00:04<00:05, 15.70it/s]
 45%|####4     | 70/157 [00:04<00:05, 15.71it/s]
 46%|####5     | 72/157 [00:04<00:05, 15.76it/s]
 47%|####7     | 74/157 [00:04<00:05, 15.81it/s]
 48%|####8     | 76/157 [00:04<00:05, 15.58it/s]
 50%|####9     | 78/157 [00:04<00:05, 15.61it/s]
 51%|#####     | 80/157 [00:04<00:04, 15.52it/s]
 52%|#####2    | 82/157 [00:05<00:04, 15.59it/s]
 54%|#####3    | 84/157 [00:05<00:04, 15.70it/s]
 55%|#####4    | 86/157 [00:05<00:08,  8.54it/s]
 56%|#####6    | 88/157 [00:05<00:06,  9.94it/s]
 57%|#####7    | 90/157 [00:05<00:05, 11.25it/s]
 59%|#####8    | 92/157 [00:06<00:05, 12.37it/s]
 60%|#####9    | 94/157 [00:06<00:04, 13.28it/s]
 61%|######1   | 96/157 [00:06<00:04, 14.00it/s]
 62%|######2   | 98/157 [00:06<00:04, 14.69it/s]
 64%|######3   | 100/157 [00:06<00:03, 14.81it/s]
 65%|######4   | 102/157 [00:06<00:03, 15.05it/s]
 66%|######6   | 104/157 [00:06<00:03, 15.28it/s]
 68%|######7   | 106/157 [00:06<00:03, 15.39it/s]
 69%|######8   | 108/157 [00:07<00:03, 15.54it/s]
 70%|#######   | 110/157 [00:07<00:02, 15.74it/s]
 71%|#######1  | 112/157 [00:07<00:02, 15.80it/s]
 73%|#######2  | 114/157 [00:07<00:02, 15.81it/s]
 74%|#######3  | 116/157 [00:07<00:02, 15.86it/s]
 75%|#######5  | 118/157 [00:07<00:02, 15.81it/s]
 76%|#######6  | 120/157 [00:07<00:02, 15.82it/s]
 78%|#######7  | 122/157 [00:07<00:02, 15.83it/s]
 79%|#######8  | 124/157 [00:08<00:02, 15.79it/s]
 80%|########  | 126/157 [00:08<00:01, 15.88it/s]
 82%|########1 | 128/157 [00:08<00:01, 15.87it/s]
 83%|########2 | 130/157 [00:08<00:01, 15.92it/s]
 84%|########4 | 132/157 [00:08<00:01, 15.62it/s]
 85%|########5 | 134/157 [00:08<00:01, 15.69it/s]
 87%|########6 | 136/157 [00:08<00:01, 15.79it/s]
 88%|########7 | 138/157 [00:08<00:01, 15.84it/s]
 89%|########9 | 140/157 [00:09<00:01, 15.83it/s]
 90%|######### | 142/157 [00:09<00:00, 15.97it/s]
 92%|#########1| 144/157 [00:09<00:00, 16.08it/s]
 93%|#########2| 146/157 [00:09<00:00, 15.97it/s]
 94%|#########4| 148/157 [00:09<00:00, 16.04it/s]
 96%|#########5| 150/157 [00:09<00:00, 16.10it/s]
 97%|#########6| 152/157 [00:09<00:00, 16.07it/s]
 98%|#########8| 154/157 [00:09<00:00, 16.00it/s]
 99%|#########9| 156/157 [00:10<00:00, 15.96it/s]
100%|##########| 157/157 [00:10<00:00, 15.51it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:45, 17.10it/s]
  1%|          | 4/781 [00:00<00:44, 17.38it/s]
  1%|          | 6/781 [00:00<00:43, 17.69it/s]
  1%|1         | 8/781 [00:00<00:43, 17.71it/s]
  1%|1         | 10/781 [00:00<00:43, 17.57it/s]
  2%|1         | 12/781 [00:00<00:43, 17.71it/s]
  2%|1         | 14/781 [00:00<00:43, 17.74it/s]
  2%|2         | 16/781 [00:00<00:42, 17.84it/s]
  2%|2         | 18/781 [00:01<00:42, 17.88it/s]
  3%|2         | 20/781 [00:01<00:42, 17.85it/s]
  3%|2         | 22/781 [00:01<00:42, 17.92it/s]
  3%|3         | 24/781 [00:01<00:42, 17.83it/s]
  3%|3         | 26/781 [00:01<00:42, 17.78it/s]
  4%|3         | 28/781 [00:01<00:42, 17.72it/s]
  4%|3         | 30/781 [00:01<00:42, 17.84it/s]
  4%|4         | 32/781 [00:01<00:42, 17.72it/s]
  4%|4         | 34/781 [00:01<00:42, 17.57it/s]
  5%|4         | 36/781 [00:02<00:42, 17.45it/s]
  5%|4         | 38/781 [00:02<00:42, 17.57it/s]
  5%|5         | 40/781 [00:02<00:41, 17.69it/s]
  5%|5         | 42/781 [00:02<00:41, 17.65it/s]
  6%|5         | 44/781 [00:02<00:41, 17.79it/s]
  6%|5         | 46/781 [00:02<00:41, 17.80it/s]
  6%|6         | 48/781 [00:02<00:41, 17.80it/s]
  6%|6         | 50/781 [00:02<00:41, 17.80it/s]
  7%|6         | 52/781 [00:02<00:40, 17.86it/s]
  7%|6         | 54/781 [00:03<00:41, 17.63it/s]
  7%|7         | 56/781 [00:03<00:40, 17.70it/s]
  7%|7         | 58/781 [00:03<00:40, 17.73it/s]
  8%|7         | 60/781 [00:03<00:40, 17.81it/s]
  8%|7         | 62/781 [00:03<00:40, 17.69it/s]
  8%|8         | 64/781 [00:03<00:40, 17.73it/s]
  8%|8         | 66/781 [00:03<00:40, 17.63it/s]
  9%|8         | 68/781 [00:03<00:40, 17.63it/s]
  9%|8         | 70/781 [00:03<00:40, 17.60it/s]
  9%|9         | 72/781 [00:04<00:40, 17.65it/s]
  9%|9         | 74/781 [00:04<00:39, 17.69it/s]
 10%|9         | 76/781 [00:04<00:39, 17.82it/s]
 10%|9         | 78/781 [00:04<00:39, 17.93it/s]
 10%|#         | 80/781 [00:04<00:39, 17.94it/s]
 10%|#         | 82/781 [00:04<00:39, 17.89it/s]
 11%|#         | 84/781 [00:04<00:38, 18.00it/s]
 11%|#1        | 86/781 [00:04<00:38, 18.06it/s]
 11%|#1        | 88/781 [00:04<00:38, 18.11it/s]
 12%|#1        | 90/781 [00:05<00:38, 18.14it/s]
 12%|#1        | 92/781 [00:05<00:38, 18.01it/s]
 12%|#2        | 94/781 [00:05<00:38, 18.06it/s]
 12%|#2        | 96/781 [00:05<00:38, 18.02it/s]
 13%|#2        | 98/781 [00:05<00:38, 17.95it/s]
 13%|#2        | 100/781 [00:05<00:38, 17.82it/s]
 13%|#3        | 102/781 [00:05<00:38, 17.64it/s]
 13%|#3        | 104/781 [00:05<00:38, 17.67it/s]
 14%|#3        | 106/781 [00:05<00:38, 17.51it/s]
 14%|#3        | 108/781 [00:06<00:38, 17.48it/s]
 14%|#4        | 110/781 [00:06<00:38, 17.42it/s]
 14%|#4        | 112/781 [00:06<00:37, 17.62it/s]
 15%|#4        | 114/781 [00:06<00:37, 17.71it/s]
 15%|#4        | 116/781 [00:06<00:37, 17.80it/s]
 15%|#5        | 118/781 [00:06<00:37, 17.85it/s]
 15%|#5        | 120/781 [00:06<00:37, 17.56it/s]
 16%|#5        | 122/781 [00:06<00:37, 17.74it/s]
 16%|#5        | 124/781 [00:06<00:36, 17.91it/s]
 16%|#6        | 126/781 [00:07<00:36, 17.92it/s]
 16%|#6        | 128/781 [00:07<00:36, 18.03it/s]
 17%|#6        | 130/781 [00:07<00:36, 18.07it/s]
 17%|#6        | 132/781 [00:07<00:35, 18.16it/s]
 17%|#7        | 134/781 [00:07<00:35, 18.16it/s]
 17%|#7        | 136/781 [00:07<00:35, 18.14it/s]
 18%|#7        | 138/781 [00:07<00:35, 17.91it/s]
 18%|#7        | 140/781 [00:07<00:36, 17.73it/s]
 18%|#8        | 142/781 [00:07<00:36, 17.64it/s]
 18%|#8        | 144/781 [00:08<00:35, 17.79it/s]
 19%|#8        | 146/781 [00:08<00:35, 17.92it/s]
 19%|#8        | 148/781 [00:08<00:35, 17.80it/s]
 19%|#9        | 150/781 [00:08<00:35, 17.72it/s]
 19%|#9        | 152/781 [00:08<00:35, 17.71it/s]
 20%|#9        | 154/781 [00:08<00:35, 17.57it/s]
 20%|#9        | 156/781 [00:08<00:35, 17.74it/s]
 20%|##        | 158/781 [00:08<00:35, 17.71it/s]
 20%|##        | 160/781 [00:08<00:34, 17.86it/s]
 21%|##        | 162/781 [00:09<00:34, 17.97it/s]
 21%|##        | 164/781 [00:09<00:34, 18.06it/s]
 21%|##1       | 166/781 [00:09<00:33, 18.12it/s]
 22%|##1       | 168/781 [00:09<00:33, 18.16it/s]
 22%|##1       | 170/781 [00:09<00:33, 18.19it/s]
 22%|##2       | 172/781 [00:09<00:33, 18.06it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.97it/s]
 23%|##2       | 176/781 [00:09<00:33, 17.99it/s]
 23%|##2       | 178/781 [00:09<00:33, 18.06it/s]
 23%|##3       | 180/781 [00:10<00:33, 17.99it/s]
 23%|##3       | 182/781 [00:10<00:33, 18.07it/s]
 24%|##3       | 184/781 [00:10<00:33, 18.07it/s]
 24%|##3       | 186/781 [00:10<00:32, 18.10it/s]
 24%|##4       | 188/781 [00:10<00:32, 18.14it/s]
 24%|##4       | 190/781 [00:10<00:32, 18.19it/s]
 25%|##4       | 192/781 [00:10<00:32, 18.11it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.87it/s]
 25%|##5       | 196/781 [00:10<00:32, 17.94it/s]
 25%|##5       | 198/781 [00:11<00:32, 17.94it/s]
 26%|##5       | 200/781 [00:11<00:32, 17.95it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.91it/s]
 26%|##6       | 204/781 [00:11<00:32, 18.00it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.91it/s]
 27%|##6       | 208/781 [00:11<00:32, 17.82it/s]
 27%|##6       | 210/781 [00:11<00:31, 17.87it/s]
 27%|##7       | 212/781 [00:11<00:32, 17.78it/s]
 27%|##7       | 214/781 [00:11<00:31, 17.93it/s]
 28%|##7       | 216/781 [00:12<00:32, 17.63it/s]
 28%|##7       | 218/781 [00:12<00:32, 17.52it/s]
 28%|##8       | 220/781 [00:12<00:31, 17.70it/s]
 28%|##8       | 222/781 [00:12<00:31, 17.85it/s]
 29%|##8       | 224/781 [00:12<00:31, 17.90it/s]
 29%|##8       | 226/781 [00:12<00:30, 18.00it/s]
 29%|##9       | 228/781 [00:12<00:30, 17.95it/s]
 29%|##9       | 230/781 [00:12<00:30, 17.84it/s]
 30%|##9       | 232/781 [00:13<00:30, 17.95it/s]
 30%|##9       | 234/781 [00:13<00:30, 17.77it/s]
 30%|###       | 236/781 [00:13<00:30, 17.93it/s]
 30%|###       | 238/781 [00:13<00:30, 17.87it/s]
 31%|###       | 240/781 [00:13<00:30, 17.95it/s]
 31%|###       | 242/781 [00:13<00:29, 17.99it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.11it/s]
 31%|###1      | 246/781 [00:13<00:29, 18.17it/s]
 32%|###1      | 248/781 [00:13<00:29, 18.09it/s]
 32%|###2      | 250/781 [00:14<00:29, 17.86it/s]
 32%|###2      | 252/781 [00:14<00:29, 17.76it/s]
 33%|###2      | 254/781 [00:14<00:29, 17.77it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.63it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.76it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.69it/s]
 34%|###3      | 262/781 [00:14<00:29, 17.84it/s]
 34%|###3      | 264/781 [00:14<00:28, 17.89it/s]
 34%|###4      | 266/781 [00:14<00:28, 17.90it/s]
 34%|###4      | 268/781 [00:15<00:28, 17.74it/s]
 35%|###4      | 270/781 [00:15<00:28, 17.86it/s]
 35%|###4      | 272/781 [00:15<00:28, 18.02it/s]
 35%|###5      | 274/781 [00:15<00:28, 18.08it/s]
 35%|###5      | 276/781 [00:15<00:27, 18.11it/s]
 36%|###5      | 278/781 [00:15<00:27, 18.06it/s]
 36%|###5      | 280/781 [00:15<00:27, 18.10it/s]
 36%|###6      | 282/781 [00:15<00:28, 17.28it/s]
 36%|###6      | 284/781 [00:15<00:28, 17.48it/s]
 37%|###6      | 286/781 [00:16<00:28, 17.49it/s]
 37%|###6      | 288/781 [00:16<00:27, 17.68it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.67it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.69it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.81it/s]
 38%|###7      | 296/781 [00:16<00:27, 17.86it/s]
 38%|###8      | 298/781 [00:16<00:27, 17.47it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.55it/s]
 39%|###8      | 302/781 [00:16<00:27, 17.68it/s]
 39%|###8      | 304/781 [00:17<00:27, 17.61it/s]
 39%|###9      | 306/781 [00:17<00:27, 17.52it/s]
 39%|###9      | 308/781 [00:17<00:27, 17.46it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.64it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.83it/s]
 40%|####      | 314/781 [00:17<00:25, 17.99it/s]
 40%|####      | 316/781 [00:17<00:25, 18.06it/s]
 41%|####      | 318/781 [00:17<00:25, 17.99it/s]
 41%|####      | 320/781 [00:17<00:25, 18.01it/s]
 41%|####1     | 322/781 [00:18<00:25, 17.94it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.89it/s]
 42%|####1     | 326/781 [00:18<00:25, 18.05it/s]
 42%|####1     | 328/781 [00:18<00:25, 18.11it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.97it/s]
 43%|####2     | 332/781 [00:18<00:25, 17.95it/s]
 43%|####2     | 334/781 [00:18<00:24, 17.98it/s]
 43%|####3     | 336/781 [00:18<00:24, 18.03it/s]
 43%|####3     | 338/781 [00:18<00:24, 18.09it/s]
 44%|####3     | 340/781 [00:19<00:24, 17.92it/s]
 44%|####3     | 342/781 [00:19<00:24, 17.96it/s]
 44%|####4     | 344/781 [00:19<00:24, 18.05it/s]
 44%|####4     | 346/781 [00:19<00:24, 18.11it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.95it/s]
 45%|####4     | 350/781 [00:19<00:23, 18.01it/s]
 45%|####5     | 352/781 [00:19<00:23, 18.10it/s]
 45%|####5     | 354/781 [00:19<00:23, 18.20it/s]
 46%|####5     | 356/781 [00:19<00:23, 18.25it/s]
 46%|####5     | 358/781 [00:20<00:23, 18.17it/s]
 46%|####6     | 360/781 [00:20<00:23, 18.18it/s]
 46%|####6     | 362/781 [00:20<00:22, 18.22it/s]
 47%|####6     | 364/781 [00:20<00:22, 18.24it/s]
 47%|####6     | 366/781 [00:20<00:22, 18.08it/s]
 47%|####7     | 368/781 [00:20<00:22, 18.07it/s]
 47%|####7     | 370/781 [00:20<00:22, 18.12it/s]
 48%|####7     | 372/781 [00:20<00:22, 18.18it/s]
 48%|####7     | 374/781 [00:20<00:22, 17.95it/s]
 48%|####8     | 376/781 [00:21<00:22, 17.99it/s]
 48%|####8     | 378/781 [00:21<00:22, 18.07it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.99it/s]
 49%|####8     | 382/781 [00:21<00:22, 17.81it/s]
 49%|####9     | 384/781 [00:21<00:22, 17.82it/s]
 49%|####9     | 386/781 [00:21<00:22, 17.59it/s]
 50%|####9     | 388/781 [00:21<00:22, 17.75it/s]
 50%|####9     | 390/781 [00:21<00:21, 17.86it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.93it/s]
 50%|#####     | 394/781 [00:22<00:21, 17.99it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.71it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.88it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.76it/s]
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 52%|#####2    | 408/781 [00:22<00:21, 17.73it/s]
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 53%|#####2    | 412/781 [00:23<00:20, 17.89it/s]
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 55%|#####4    | 426/781 [00:23<00:20, 17.67it/s]
 55%|#####4    | 428/781 [00:23<00:19, 17.83it/s]
 55%|#####5    | 430/781 [00:24<00:19, 17.92it/s]
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 56%|#####5    | 434/781 [00:24<00:19, 18.08it/s]
 56%|#####5    | 436/781 [00:24<00:19, 18.11it/s]
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 57%|#####7    | 446/781 [00:24<00:18, 18.22it/s]
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 58%|#####7    | 450/781 [00:25<00:18, 18.27it/s]
 58%|#####7    | 452/781 [00:25<00:18, 18.27it/s]
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 60%|#####9    | 466/781 [00:26<00:17, 18.23it/s]
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 60%|######    | 470/781 [00:26<00:17, 18.12it/s]
 60%|######    | 472/781 [00:26<00:17, 18.13it/s]
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 70%|######9   | 546/781 [00:30<00:12, 18.10it/s]
 70%|#######   | 548/781 [00:30<00:12, 18.04it/s]
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 71%|#######   | 552/781 [00:30<00:12, 17.82it/s]
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 71%|#######1  | 556/781 [00:31<00:12, 17.82it/s]
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 72%|#######1  | 560/781 [00:31<00:12, 17.87it/s]
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 73%|#######2  | 568/781 [00:31<00:12, 17.54it/s]
 73%|#######2  | 570/781 [00:31<00:12, 17.54it/s]
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 74%|#######4  | 580/781 [00:32<00:11, 17.70it/s]
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 76%|#######5  | 590/781 [00:32<00:10, 17.55it/s]
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 77%|#######6  | 600/781 [00:33<00:10, 17.89it/s]
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 78%|#######8  | 610/781 [00:34<00:09, 18.04it/s]
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 79%|#######8  | 614/781 [00:34<00:09, 17.97it/s]
 79%|#######8  | 616/781 [00:34<00:09, 17.95it/s]
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 80%|#######9  | 622/781 [00:34<00:08, 17.67it/s]
 80%|#######9  | 624/781 [00:34<00:08, 17.66it/s]
 80%|########  | 626/781 [00:34<00:08, 17.78it/s]
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 83%|########3 | 650/781 [00:36<00:07, 18.03it/s]
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 85%|########4 | 660/781 [00:36<00:06, 17.97it/s]
 85%|########4 | 662/781 [00:37<00:06, 17.73it/s]
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 85%|########5 | 666/781 [00:37<00:06, 17.90it/s]
 86%|########5 | 668/781 [00:37<00:06, 18.01it/s]
 86%|########5 | 670/781 [00:37<00:06, 18.05it/s]
 86%|########6 | 672/781 [00:37<00:06, 18.06it/s]
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 87%|########7 | 680/781 [00:38<00:05, 17.76it/s]
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 90%|########9 | 699/781 [00:39<00:04, 19.08it/s]
 90%|########9 | 701/781 [00:39<00:04, 19.16it/s]
 90%|######### | 703/781 [00:39<00:04, 19.33it/s]
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 91%|######### | 707/781 [00:39<00:03, 19.61it/s]
 91%|######### | 709/781 [00:39<00:03, 19.64it/s]
 91%|#########1| 712/781 [00:39<00:03, 19.88it/s]
 92%|#########1| 715/781 [00:39<00:03, 20.09it/s]
 92%|#########1| 718/781 [00:39<00:03, 20.20it/s]
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 93%|#########3| 727/781 [00:40<00:02, 20.19it/s]
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 94%|#########3| 733/781 [00:40<00:02, 20.30it/s]
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 96%|#########6| 750/781 [00:41<00:01, 19.12it/s]
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100%|#########9| 778/781 [00:43<00:00, 18.21it/s]
100%|#########9| 780/781 [00:43<00:00, 17.92it/s]
100%|##########| 781/781 [00:43<00:00, 18.03it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
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Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.04it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.04it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.01it/s]
Validation Progress:   2%|2         | 1/44 [00:01<00:43,  1.00s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:44,  1.05s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:44,  1.06s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.00s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.01s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.02s/it]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.01it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.01it/s]
Validation Progress:   9%|9         | 4/44 [00:03<00:39,  1.01it/s]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.00s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.03s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.03s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:38,  1.00s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:38,  1.00s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:38,  1.00s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:38,  1.01s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.02s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.02s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.02s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:38,  1.05s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:37,  1.03s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.02s/it]
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 10%|#         | 80/781 [00:04<00:39, 17.81it/s]
 10%|#         | 82/781 [00:04<00:39, 17.85it/s]
 11%|#         | 84/781 [00:04<00:38, 17.98it/s]
 11%|#1        | 86/781 [00:04<00:38, 17.98it/s]
 11%|#1        | 88/781 [00:04<00:38, 18.08it/s]
 12%|#1        | 90/781 [00:05<00:38, 17.88it/s]
 12%|#1        | 92/781 [00:05<00:38, 17.83it/s]
 12%|#2        | 94/781 [00:05<00:38, 18.06it/s]
 12%|#2        | 96/781 [00:05<00:38, 17.84it/s]
 13%|#2        | 98/781 [00:05<00:38, 17.88it/s]
 13%|#2        | 100/781 [00:05<00:37, 18.12it/s]
 13%|#3        | 102/781 [00:05<00:37, 18.11it/s]
 13%|#3        | 104/781 [00:05<00:37, 18.21it/s]
 14%|#3        | 106/781 [00:05<00:37, 17.83it/s]
 14%|#3        | 108/781 [00:06<00:37, 17.80it/s]
 14%|#4        | 110/781 [00:06<00:37, 17.78it/s]
 14%|#4        | 112/781 [00:06<00:37, 17.93it/s]
 15%|#4        | 114/781 [00:06<00:37, 17.87it/s]
 15%|#4        | 116/781 [00:06<00:37, 17.88it/s]
 15%|#5        | 118/781 [00:06<00:37, 17.91it/s]
 15%|#5        | 120/781 [00:06<00:36, 17.94it/s]
 16%|#5        | 122/781 [00:06<00:36, 17.91it/s]
 16%|#5        | 124/781 [00:06<00:36, 17.96it/s]
 16%|#6        | 126/781 [00:07<00:36, 17.99it/s]
 16%|#6        | 128/781 [00:07<00:36, 18.05it/s]
 17%|#6        | 130/781 [00:07<00:36, 18.08it/s]
 17%|#6        | 132/781 [00:07<00:35, 18.10it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.96it/s]
 17%|#7        | 136/781 [00:07<00:35, 18.01it/s]
 18%|#7        | 138/781 [00:07<00:35, 18.05it/s]
 18%|#7        | 140/781 [00:07<00:35, 18.08it/s]
 18%|#8        | 142/781 [00:07<00:35, 18.12it/s]
 18%|#8        | 144/781 [00:08<00:35, 18.09it/s]
 19%|#8        | 146/781 [00:08<00:35, 17.82it/s]
 19%|#8        | 148/781 [00:08<00:35, 17.97it/s]
 19%|#9        | 150/781 [00:08<00:35, 18.01it/s]
 19%|#9        | 152/781 [00:08<00:35, 17.91it/s]
 20%|#9        | 154/781 [00:08<00:35, 17.72it/s]
 20%|#9        | 156/781 [00:08<00:35, 17.65it/s]
 20%|##        | 158/781 [00:08<00:35, 17.67it/s]
 20%|##        | 160/781 [00:08<00:35, 17.60it/s]
 21%|##        | 162/781 [00:09<00:35, 17.52it/s]
 21%|##        | 164/781 [00:09<00:34, 17.66it/s]
 21%|##1       | 166/781 [00:09<00:34, 17.72it/s]
 22%|##1       | 168/781 [00:09<00:34, 17.60it/s]
 22%|##1       | 170/781 [00:09<00:34, 17.52it/s]
 22%|##2       | 172/781 [00:09<00:34, 17.62it/s]
 22%|##2       | 174/781 [00:09<00:34, 17.61it/s]
 23%|##2       | 176/781 [00:09<00:34, 17.52it/s]
 23%|##2       | 178/781 [00:09<00:34, 17.49it/s]
 23%|##3       | 180/781 [00:10<00:34, 17.44it/s]
 23%|##3       | 182/781 [00:10<00:34, 17.47it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.61it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.64it/s]
 24%|##4       | 188/781 [00:10<00:33, 17.78it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.85it/s]
 25%|##4       | 192/781 [00:10<00:32, 17.96it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.95it/s]
 25%|##5       | 196/781 [00:10<00:32, 18.04it/s]
 25%|##5       | 198/781 [00:11<00:32, 18.04it/s]
 26%|##5       | 200/781 [00:11<00:32, 18.04it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.92it/s]
 26%|##6       | 204/781 [00:11<00:32, 17.91it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.80it/s]
 27%|##6       | 208/781 [00:11<00:32, 17.80it/s]
 27%|##6       | 210/781 [00:11<00:32, 17.75it/s]
 27%|##7       | 212/781 [00:11<00:31, 17.81it/s]
 27%|##7       | 214/781 [00:12<00:31, 17.75it/s]
 28%|##7       | 216/781 [00:12<00:31, 17.83it/s]
 28%|##7       | 218/781 [00:12<00:32, 17.48it/s]
 28%|##8       | 220/781 [00:12<00:31, 17.69it/s]
 28%|##8       | 222/781 [00:12<00:31, 17.56it/s]
 29%|##8       | 224/781 [00:12<00:31, 17.64it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.79it/s]
 29%|##9       | 228/781 [00:12<00:31, 17.82it/s]
 29%|##9       | 230/781 [00:12<00:30, 17.95it/s]
 30%|##9       | 232/781 [00:13<00:30, 17.83it/s]
 30%|##9       | 234/781 [00:13<00:30, 17.77it/s]
 30%|###       | 236/781 [00:13<00:30, 17.76it/s]
 30%|###       | 238/781 [00:13<00:30, 17.73it/s]
 31%|###       | 240/781 [00:13<00:30, 17.62it/s]
 31%|###       | 242/781 [00:13<00:30, 17.67it/s]
 31%|###1      | 244/781 [00:13<00:30, 17.69it/s]
 31%|###1      | 246/781 [00:13<00:30, 17.69it/s]
 32%|###1      | 248/781 [00:13<00:30, 17.68it/s]
 32%|###2      | 250/781 [00:14<00:29, 17.72it/s]
 32%|###2      | 252/781 [00:14<00:29, 17.87it/s]
 33%|###2      | 254/781 [00:14<00:29, 17.96it/s]
 33%|###2      | 256/781 [00:14<00:29, 18.01it/s]
 33%|###3      | 258/781 [00:14<00:29, 18.02it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.87it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.01it/s]
 34%|###3      | 264/781 [00:14<00:28, 18.01it/s]
 34%|###4      | 266/781 [00:14<00:28, 18.06it/s]
 34%|###4      | 268/781 [00:15<00:28, 18.14it/s]
 35%|###4      | 270/781 [00:15<00:28, 17.70it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.78it/s]
 35%|###5      | 274/781 [00:15<00:29, 17.36it/s]
 35%|###5      | 276/781 [00:15<00:28, 17.64it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.68it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.76it/s]
 36%|###6      | 282/781 [00:15<00:27, 17.83it/s]
 36%|###6      | 284/781 [00:15<00:27, 18.05it/s]
 37%|###6      | 286/781 [00:16<00:27, 18.31it/s]
 37%|###6      | 288/781 [00:16<00:26, 18.53it/s]
 37%|###7      | 290/781 [00:16<00:26, 18.59it/s]
 37%|###7      | 292/781 [00:16<00:26, 18.51it/s]
 38%|###7      | 294/781 [00:16<00:25, 18.79it/s]
 38%|###7      | 296/781 [00:16<00:25, 19.03it/s]
 38%|###8      | 298/781 [00:16<00:25, 19.23it/s]
 38%|###8      | 300/781 [00:16<00:24, 19.41it/s]
 39%|###8      | 303/781 [00:16<00:24, 19.76it/s]
 39%|###9      | 306/781 [00:17<00:23, 19.99it/s]
 40%|###9      | 309/781 [00:17<00:23, 20.08it/s]
 40%|###9      | 312/781 [00:17<00:23, 20.26it/s]
 40%|####      | 315/781 [00:17<00:23, 19.94it/s]
 41%|####      | 318/781 [00:17<00:22, 20.14it/s]
 41%|####1     | 321/781 [00:17<00:22, 20.23it/s]
 41%|####1     | 324/781 [00:17<00:22, 20.27it/s]
 42%|####1     | 327/781 [00:18<00:22, 20.11it/s]
 42%|####2     | 330/781 [00:18<00:22, 19.94it/s]
 43%|####2     | 332/781 [00:18<00:22, 19.77it/s]
 43%|####2     | 335/781 [00:18<00:22, 19.97it/s]
 43%|####3     | 338/781 [00:18<00:22, 20.11it/s]
 44%|####3     | 341/781 [00:18<00:21, 20.04it/s]
 44%|####4     | 344/781 [00:18<00:21, 20.00it/s]
 44%|####4     | 347/781 [00:19<00:21, 20.15it/s]
 45%|####4     | 350/781 [00:19<00:21, 20.22it/s]
 45%|####5     | 353/781 [00:19<00:21, 20.01it/s]
 46%|####5     | 356/781 [00:19<00:21, 19.79it/s]
 46%|####5     | 358/781 [00:19<00:21, 19.60it/s]
 46%|####6     | 360/781 [00:19<00:21, 19.48it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.98it/s]
 47%|####6     | 364/781 [00:19<00:22, 18.55it/s]
 47%|####6     | 366/781 [00:20<00:22, 18.51it/s]
 47%|####7     | 368/781 [00:20<00:22, 18.76it/s]
 47%|####7     | 370/781 [00:20<00:21, 19.05it/s]
 48%|####7     | 373/781 [00:20<00:20, 19.48it/s]
 48%|####8     | 375/781 [00:20<00:21, 19.26it/s]
 48%|####8     | 377/781 [00:20<00:21, 18.88it/s]
 49%|####8     | 379/781 [00:20<00:21, 18.43it/s]
 49%|####8     | 381/781 [00:20<00:21, 18.37it/s]
 49%|####9     | 383/781 [00:21<00:21, 18.13it/s]
 49%|####9     | 385/781 [00:21<00:22, 17.86it/s]
 50%|####9     | 387/781 [00:21<00:22, 17.77it/s]
 50%|####9     | 389/781 [00:21<00:22, 17.66it/s]
 50%|#####     | 391/781 [00:21<00:22, 17.62it/s]
 50%|#####     | 393/781 [00:21<00:21, 17.69it/s]
 51%|#####     | 395/781 [00:21<00:21, 17.74it/s]
 51%|#####     | 397/781 [00:21<00:21, 17.77it/s]
 51%|#####1    | 399/781 [00:21<00:21, 17.73it/s]
 51%|#####1    | 401/781 [00:22<00:21, 17.75it/s]
 52%|#####1    | 403/781 [00:22<00:21, 17.70it/s]
 52%|#####1    | 405/781 [00:22<00:21, 17.56it/s]
 52%|#####2    | 407/781 [00:22<00:21, 17.73it/s]
 52%|#####2    | 409/781 [00:22<00:20, 17.73it/s]
 53%|#####2    | 411/781 [00:22<00:20, 17.71it/s]
 53%|#####2    | 413/781 [00:22<00:20, 17.76it/s]
 53%|#####3    | 415/781 [00:22<00:20, 17.77it/s]
 53%|#####3    | 417/781 [00:22<00:20, 17.80it/s]
 54%|#####3    | 419/781 [00:23<00:20, 17.95it/s]
 54%|#####3    | 421/781 [00:23<00:20, 17.37it/s]
 54%|#####4    | 423/781 [00:23<00:20, 17.47it/s]
 54%|#####4    | 425/781 [00:23<00:20, 17.70it/s]
 55%|#####4    | 427/781 [00:23<00:19, 17.86it/s]
 55%|#####4    | 429/781 [00:23<00:19, 18.01it/s]
 55%|#####5    | 431/781 [00:23<00:19, 18.11it/s]
 55%|#####5    | 433/781 [00:23<00:19, 17.93it/s]
 56%|#####5    | 435/781 [00:23<00:19, 17.79it/s]
 56%|#####5    | 437/781 [00:24<00:19, 17.68it/s]
 56%|#####6    | 439/781 [00:24<00:19, 17.69it/s]
 56%|#####6    | 441/781 [00:24<00:19, 17.76it/s]
 57%|#####6    | 443/781 [00:24<00:18, 17.86it/s]
 57%|#####6    | 445/781 [00:24<00:18, 17.93it/s]
 57%|#####7    | 447/781 [00:24<00:18, 18.02it/s]
 57%|#####7    | 449/781 [00:24<00:18, 18.10it/s]
 58%|#####7    | 451/781 [00:24<00:18, 18.17it/s]
 58%|#####8    | 453/781 [00:24<00:18, 18.16it/s]
 58%|#####8    | 455/781 [00:25<00:18, 18.06it/s]
 59%|#####8    | 457/781 [00:25<00:17, 18.04it/s]
 59%|#####8    | 459/781 [00:25<00:17, 18.13it/s]
 59%|#####9    | 461/781 [00:25<00:17, 18.15it/s]
 59%|#####9    | 463/781 [00:25<00:17, 18.20it/s]
 60%|#####9    | 465/781 [00:25<00:17, 18.26it/s]
 60%|#####9    | 467/781 [00:25<00:17, 18.31it/s]
 60%|######    | 469/781 [00:25<00:17, 18.09it/s]
 60%|######    | 471/781 [00:25<00:17, 18.03it/s]
 61%|######    | 473/781 [00:26<00:17, 18.04it/s]
 61%|######    | 475/781 [00:26<00:16, 18.09it/s]
 61%|######1   | 477/781 [00:26<00:16, 18.57it/s]
 61%|######1   | 479/781 [00:26<00:16, 18.26it/s]
 62%|######1   | 481/781 [00:26<00:16, 18.13it/s]
 62%|######1   | 483/781 [00:26<00:16, 18.04it/s]
 62%|######2   | 485/781 [00:26<00:16, 17.99it/s]
 62%|######2   | 487/781 [00:26<00:16, 17.94it/s]
 63%|######2   | 489/781 [00:26<00:16, 17.93it/s]
 63%|######2   | 491/781 [00:27<00:16, 18.03it/s]
 63%|######3   | 493/781 [00:27<00:16, 17.84it/s]
 63%|######3   | 495/781 [00:27<00:16, 17.70it/s]
 64%|######3   | 497/781 [00:27<00:16, 17.51it/s]
 64%|######3   | 499/781 [00:27<00:15, 17.96it/s]
 64%|######4   | 501/781 [00:27<00:15, 18.10it/s]
 64%|######4   | 503/781 [00:27<00:15, 17.95it/s]
 65%|######4   | 505/781 [00:27<00:14, 18.47it/s]
 65%|######4   | 507/781 [00:27<00:14, 18.87it/s]
 65%|######5   | 509/781 [00:28<00:14, 18.49it/s]
 65%|######5   | 511/781 [00:28<00:14, 18.40it/s]
 66%|######5   | 513/781 [00:28<00:14, 18.48it/s]
 66%|######5   | 515/781 [00:28<00:14, 18.69it/s]
 66%|######6   | 517/781 [00:28<00:13, 18.87it/s]
 66%|######6   | 519/781 [00:28<00:13, 18.85it/s]
 67%|######6   | 521/781 [00:28<00:13, 18.79it/s]
 67%|######6   | 523/781 [00:28<00:14, 18.14it/s]
 67%|######7   | 525/781 [00:28<00:14, 17.95it/s]
 67%|######7   | 527/781 [00:29<00:14, 17.88it/s]
 68%|######7   | 529/781 [00:29<00:14, 17.74it/s]
 68%|######7   | 531/781 [00:29<00:14, 17.49it/s]
 68%|######8   | 533/781 [00:29<00:14, 17.54it/s]
 69%|######8   | 535/781 [00:29<00:14, 17.44it/s]
 69%|######8   | 537/781 [00:29<00:14, 17.35it/s]
 69%|######9   | 539/781 [00:29<00:13, 17.30it/s]
 69%|######9   | 541/781 [00:29<00:13, 17.46it/s]
 70%|######9   | 543/781 [00:29<00:13, 17.59it/s]
 70%|######9   | 545/781 [00:30<00:13, 17.60it/s]
 70%|#######   | 547/781 [00:30<00:13, 17.69it/s]
 70%|#######   | 549/781 [00:30<00:13, 17.64it/s]
 71%|#######   | 551/781 [00:30<00:13, 17.69it/s]
 71%|#######   | 553/781 [00:30<00:12, 17.69it/s]
 71%|#######1  | 555/781 [00:30<00:12, 17.83it/s]
 71%|#######1  | 557/781 [00:30<00:12, 17.84it/s]
 72%|#######1  | 559/781 [00:30<00:12, 17.88it/s]
 72%|#######1  | 561/781 [00:30<00:12, 17.87it/s]
 72%|#######2  | 563/781 [00:31<00:12, 17.97it/s]
 72%|#######2  | 565/781 [00:31<00:11, 18.04it/s]
 73%|#######2  | 567/781 [00:31<00:11, 18.09it/s]
 73%|#######2  | 569/781 [00:31<00:11, 18.12it/s]
 73%|#######3  | 571/781 [00:31<00:11, 18.16it/s]
 73%|#######3  | 573/781 [00:31<00:11, 18.15it/s]
 74%|#######3  | 575/781 [00:31<00:11, 18.18it/s]
 74%|#######3  | 577/781 [00:31<00:11, 18.09it/s]
 74%|#######4  | 579/781 [00:31<00:11, 17.94it/s]
 74%|#######4  | 581/781 [00:32<00:11, 17.94it/s]
 75%|#######4  | 583/781 [00:32<00:10, 18.03it/s]
 75%|#######4  | 585/781 [00:32<00:10, 18.02it/s]
 75%|#######5  | 587/781 [00:32<00:10, 18.05it/s]
 75%|#######5  | 589/781 [00:32<00:10, 18.06it/s]
 76%|#######5  | 591/781 [00:32<00:10, 18.01it/s]
 76%|#######5  | 593/781 [00:32<00:10, 17.74it/s]
 76%|#######6  | 595/781 [00:32<00:10, 17.77it/s]
 76%|#######6  | 597/781 [00:32<00:10, 17.86it/s]
 77%|#######6  | 599/781 [00:33<00:10, 17.74it/s]
 77%|#######6  | 601/781 [00:33<00:10, 17.92it/s]
 77%|#######7  | 603/781 [00:33<00:09, 18.09it/s]
 77%|#######7  | 605/781 [00:33<00:09, 18.14it/s]
 78%|#######7  | 607/781 [00:33<00:09, 17.64it/s]
 78%|#######7  | 609/781 [00:33<00:09, 18.11it/s]
 78%|#######8  | 611/781 [00:33<00:09, 18.18it/s]
 78%|#######8  | 613/781 [00:33<00:09, 18.54it/s]
 79%|#######8  | 615/781 [00:33<00:09, 18.35it/s]
 79%|#######9  | 617/781 [00:34<00:08, 18.28it/s]
 79%|#######9  | 619/781 [00:34<00:08, 18.07it/s]
 80%|#######9  | 621/781 [00:34<00:08, 17.92it/s]
 80%|#######9  | 623/781 [00:34<00:08, 17.95it/s]
 80%|########  | 625/781 [00:34<00:08, 18.00it/s]
 80%|########  | 627/781 [00:34<00:08, 17.97it/s]
 81%|########  | 629/781 [00:34<00:08, 17.92it/s]
 81%|########  | 631/781 [00:34<00:08, 17.96it/s]
 81%|########1 | 633/781 [00:34<00:08, 17.93it/s]
 81%|########1 | 635/781 [00:35<00:08, 18.08it/s]
 82%|########1 | 637/781 [00:35<00:07, 18.14it/s]
 82%|########1 | 639/781 [00:35<00:07, 17.82it/s]
 82%|########2 | 641/781 [00:35<00:07, 18.26it/s]
 82%|########2 | 643/781 [00:35<00:07, 18.60it/s]
 83%|########2 | 645/781 [00:35<00:07, 18.87it/s]
 83%|########2 | 647/781 [00:35<00:07, 19.07it/s]
 83%|########3 | 650/781 [00:35<00:06, 19.57it/s]
 83%|########3 | 652/781 [00:35<00:06, 19.62it/s]
 84%|########3 | 655/781 [00:36<00:06, 19.80it/s]
 84%|########4 | 657/781 [00:36<00:06, 19.66it/s]
 84%|########4 | 659/781 [00:36<00:06, 19.70it/s]
 85%|########4 | 661/781 [00:36<00:06, 19.65it/s]
 85%|########4 | 663/781 [00:36<00:06, 19.44it/s]
 85%|########5 | 666/781 [00:36<00:05, 19.59it/s]
 86%|########5 | 668/781 [00:36<00:05, 19.43it/s]
 86%|########5 | 670/781 [00:36<00:05, 19.13it/s]
 86%|########6 | 672/781 [00:36<00:05, 19.15it/s]
 86%|########6 | 674/781 [00:37<00:05, 18.97it/s]
 87%|########6 | 676/781 [00:37<00:05, 18.77it/s]
 87%|########6 | 678/781 [00:37<00:05, 18.94it/s]
 87%|########7 | 680/781 [00:37<00:05, 18.43it/s]
 87%|########7 | 682/781 [00:37<00:05, 18.46it/s]
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100%|##########| 781/781 [00:42<00:00, 18.26it/s]




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 29%|##9       | 46/157 [00:02<00:06, 17.34it/s]
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 32%|###1      | 50/157 [00:02<00:06, 17.44it/s]
 33%|###3      | 52/157 [00:03<00:06, 17.42it/s]
 34%|###4      | 54/157 [00:03<00:05, 17.40it/s]
 36%|###5      | 56/157 [00:03<00:05, 17.42it/s]
 37%|###6      | 58/157 [00:03<00:05, 17.41it/s]
 38%|###8      | 60/157 [00:03<00:05, 17.45it/s]
 39%|###9      | 62/157 [00:03<00:05, 17.47it/s]
 41%|####      | 64/157 [00:03<00:05, 17.50it/s]
 42%|####2     | 66/157 [00:03<00:05, 17.51it/s]
 43%|####3     | 68/157 [00:03<00:05, 17.53it/s]
 45%|####4     | 70/157 [00:04<00:04, 17.51it/s]
 46%|####5     | 72/157 [00:04<00:04, 17.39it/s]
 47%|####7     | 74/157 [00:04<00:04, 17.42it/s]
 48%|####8     | 76/157 [00:04<00:04, 17.38it/s]
 50%|####9     | 78/157 [00:04<00:04, 17.26it/s]
 51%|#####     | 80/157 [00:04<00:04, 17.34it/s]
 52%|#####2    | 82/157 [00:04<00:04, 17.12it/s]
 54%|#####3    | 84/157 [00:04<00:04, 17.12it/s]
 55%|#####4    | 86/157 [00:05<00:04, 16.91it/s]
 56%|#####6    | 88/157 [00:05<00:04, 17.04it/s]
 57%|#####7    | 90/157 [00:05<00:03, 17.13it/s]
 59%|#####8    | 92/157 [00:05<00:03, 17.19it/s]
 60%|#####9    | 94/157 [00:05<00:03, 17.27it/s]
 61%|######1   | 96/157 [00:05<00:03, 17.31it/s]
 62%|######2   | 98/157 [00:05<00:03, 17.25it/s]
 64%|######3   | 100/157 [00:05<00:03, 17.37it/s]
 65%|######4   | 102/157 [00:05<00:03, 17.46it/s]
 66%|######6   | 104/157 [00:06<00:03, 17.00it/s]
 68%|######7   | 106/157 [00:06<00:03, 16.99it/s]
 69%|######8   | 108/157 [00:06<00:02, 16.53it/s]
 70%|#######   | 110/157 [00:06<00:02, 16.80it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.77it/s]
 73%|#######2  | 114/157 [00:06<00:02, 16.45it/s]
 74%|#######3  | 116/157 [00:06<00:02, 16.03it/s]
 75%|#######5  | 118/157 [00:06<00:02, 15.81it/s]
 76%|#######6  | 120/157 [00:07<00:02, 15.79it/s]
 78%|#######7  | 122/157 [00:07<00:02, 15.93it/s]
 79%|#######8  | 124/157 [00:07<00:02, 15.98it/s]
 80%|########  | 126/157 [00:07<00:01, 15.77it/s]
 82%|########1 | 128/157 [00:07<00:01, 15.66it/s]
 83%|########2 | 130/157 [00:07<00:01, 16.09it/s]
 84%|########4 | 132/157 [00:07<00:01, 16.22it/s]
 85%|########5 | 134/157 [00:07<00:01, 15.89it/s]
 87%|########6 | 136/157 [00:08<00:01, 15.76it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.22it/s]
 89%|########9 | 140/157 [00:08<00:01, 16.70it/s]
 90%|######### | 142/157 [00:08<00:00, 17.07it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.91it/s]
 93%|#########2| 146/157 [00:08<00:00, 17.04it/s]
 94%|#########4| 148/157 [00:08<00:00, 17.02it/s]
 96%|#########5| 150/157 [00:08<00:00, 17.15it/s]
 97%|#########6| 152/157 [00:08<00:00, 17.19it/s]
 98%|#########8| 154/157 [00:09<00:00, 17.27it/s]
 99%|#########9| 156/157 [00:09<00:00, 17.33it/s]
100%|##########| 157/157 [00:09<00:00, 16.99it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:41, 18.72it/s]
  1%|          | 4/781 [00:00<00:40, 19.24it/s]
  1%|          | 6/781 [00:00<00:39, 19.55it/s]
  1%|1         | 8/781 [00:00<00:39, 19.61it/s]
  1%|1         | 10/781 [00:00<00:39, 19.61it/s]
  2%|1         | 12/781 [00:00<00:39, 19.61it/s]
  2%|1         | 14/781 [00:00<00:39, 19.46it/s]
  2%|2         | 16/781 [00:00<00:39, 19.59it/s]
  2%|2         | 18/781 [00:00<00:38, 19.66it/s]
  3%|2         | 20/781 [00:01<00:38, 19.63it/s]
  3%|2         | 22/781 [00:01<00:38, 19.68it/s]
  3%|3         | 24/781 [00:01<00:38, 19.73it/s]
  3%|3         | 26/781 [00:01<00:38, 19.63it/s]
  4%|3         | 28/781 [00:01<00:38, 19.72it/s]
  4%|3         | 30/781 [00:01<00:38, 19.76it/s]
  4%|4         | 32/781 [00:01<00:38, 19.58it/s]
  4%|4         | 35/781 [00:01<00:37, 19.84it/s]
  5%|4         | 38/781 [00:01<00:37, 20.07it/s]
  5%|5         | 41/781 [00:02<00:36, 20.13it/s]
  6%|5         | 44/781 [00:02<00:36, 20.13it/s]
  6%|6         | 47/781 [00:02<00:36, 20.03it/s]
  6%|6         | 50/781 [00:02<00:36, 20.04it/s]
  7%|6         | 53/781 [00:02<00:36, 19.70it/s]
  7%|7         | 55/781 [00:02<00:36, 19.74it/s]
  7%|7         | 57/781 [00:02<00:36, 19.71it/s]
  8%|7         | 59/781 [00:02<00:36, 19.76it/s]
  8%|7         | 61/781 [00:03<00:36, 19.76it/s]
  8%|8         | 63/781 [00:03<00:36, 19.75it/s]
  8%|8         | 65/781 [00:03<00:36, 19.74it/s]
  9%|8         | 67/781 [00:03<00:36, 19.68it/s]
  9%|8         | 69/781 [00:03<00:36, 19.59it/s]
  9%|9         | 71/781 [00:03<00:36, 19.68it/s]
  9%|9         | 73/781 [00:03<00:35, 19.72it/s]
 10%|9         | 76/781 [00:03<00:35, 19.78it/s]
 10%|#         | 79/781 [00:03<00:35, 20.02it/s]
 10%|#         | 81/781 [00:04<00:35, 19.81it/s]
 11%|#         | 83/781 [00:04<00:35, 19.54it/s]
 11%|#         | 85/781 [00:04<00:35, 19.62it/s]
 11%|#1        | 87/781 [00:04<00:35, 19.62it/s]
 11%|#1        | 89/781 [00:04<00:35, 19.73it/s]
 12%|#1        | 92/781 [00:04<00:34, 19.83it/s]
 12%|#2        | 94/781 [00:04<00:34, 19.77it/s]
 12%|#2        | 96/781 [00:04<00:35, 19.57it/s]
 13%|#2        | 99/781 [00:05<00:34, 19.71it/s]
 13%|#2        | 101/781 [00:05<00:34, 19.74it/s]
 13%|#3        | 103/781 [00:05<00:34, 19.74it/s]
 14%|#3        | 106/781 [00:05<00:34, 19.85it/s]
 14%|#3        | 108/781 [00:05<00:33, 19.86it/s]
 14%|#4        | 110/781 [00:05<00:34, 19.70it/s]
 14%|#4        | 112/781 [00:05<00:34, 19.56it/s]
 15%|#4        | 114/781 [00:05<00:33, 19.63it/s]
 15%|#4        | 116/781 [00:05<00:33, 19.66it/s]
 15%|#5        | 118/781 [00:05<00:33, 19.69it/s]
 15%|#5        | 120/781 [00:06<00:33, 19.75it/s]
 16%|#5        | 122/781 [00:06<00:33, 19.80it/s]
 16%|#5        | 124/781 [00:06<00:33, 19.79it/s]
 16%|#6        | 126/781 [00:06<00:33, 19.74it/s]
 17%|#6        | 129/781 [00:06<00:32, 19.89it/s]
 17%|#6        | 131/781 [00:06<00:32, 19.82it/s]
 17%|#7        | 133/781 [00:06<00:32, 19.76it/s]
 17%|#7        | 135/781 [00:06<00:32, 19.75it/s]
 18%|#7        | 137/781 [00:06<00:32, 19.69it/s]
 18%|#7        | 140/781 [00:07<00:32, 19.74it/s]
 18%|#8        | 142/781 [00:07<00:32, 19.38it/s]
 18%|#8        | 144/781 [00:07<00:33, 19.12it/s]
 19%|#8        | 146/781 [00:07<00:33, 19.11it/s]
 19%|#8        | 148/781 [00:07<00:33, 18.89it/s]
 19%|#9        | 150/781 [00:07<00:33, 18.75it/s]
 19%|#9        | 152/781 [00:07<00:34, 18.42it/s]
 20%|#9        | 154/781 [00:07<00:34, 18.18it/s]
 20%|#9        | 156/781 [00:07<00:34, 18.26it/s]
 20%|##        | 158/781 [00:08<00:33, 18.54it/s]
 20%|##        | 160/781 [00:08<00:33, 18.79it/s]
 21%|##        | 162/781 [00:08<00:32, 19.12it/s]
 21%|##1       | 165/781 [00:08<00:31, 19.55it/s]
 21%|##1       | 167/781 [00:08<00:31, 19.63it/s]
 22%|##1       | 169/781 [00:08<00:31, 19.72it/s]
 22%|##1       | 171/781 [00:08<00:31, 19.25it/s]
 22%|##2       | 173/781 [00:08<00:32, 18.61it/s]
 22%|##2       | 175/781 [00:08<00:33, 18.22it/s]
 23%|##2       | 177/781 [00:09<00:32, 18.41it/s]
 23%|##2       | 179/781 [00:09<00:32, 18.53it/s]
 23%|##3       | 181/781 [00:09<00:33, 18.15it/s]
 23%|##3       | 183/781 [00:09<00:33, 17.79it/s]
 24%|##3       | 185/781 [00:09<00:33, 17.75it/s]
 24%|##3       | 187/781 [00:09<00:33, 17.61it/s]
 24%|##4       | 189/781 [00:09<00:33, 17.69it/s]
 24%|##4       | 191/781 [00:09<00:33, 17.73it/s]
 25%|##4       | 193/781 [00:09<00:33, 17.46it/s]
 25%|##4       | 195/781 [00:10<00:33, 17.56it/s]
 25%|##5       | 197/781 [00:10<00:33, 17.57it/s]
 25%|##5       | 199/781 [00:10<00:32, 17.65it/s]
 26%|##5       | 201/781 [00:10<00:32, 17.68it/s]
 26%|##5       | 203/781 [00:10<00:32, 17.63it/s]
 26%|##6       | 205/781 [00:10<00:33, 17.44it/s]
 27%|##6       | 207/781 [00:10<00:33, 17.36it/s]
 27%|##6       | 209/781 [00:10<00:32, 17.44it/s]
 27%|##7       | 211/781 [00:11<00:32, 17.42it/s]
 27%|##7       | 213/781 [00:11<00:32, 17.52it/s]
 28%|##7       | 215/781 [00:11<00:32, 17.65it/s]
 28%|##7       | 217/781 [00:11<00:31, 17.67it/s]
 28%|##8       | 219/781 [00:11<00:31, 17.66it/s]
 28%|##8       | 221/781 [00:11<00:31, 17.65it/s]
 29%|##8       | 223/781 [00:11<00:31, 17.82it/s]
 29%|##8       | 225/781 [00:11<00:31, 17.88it/s]
 29%|##9       | 227/781 [00:11<00:30, 17.90it/s]
 29%|##9       | 229/781 [00:12<00:30, 17.97it/s]
 30%|##9       | 231/781 [00:12<00:30, 18.05it/s]
 30%|##9       | 233/781 [00:12<00:30, 18.12it/s]
 30%|###       | 235/781 [00:12<00:30, 18.17it/s]
 30%|###       | 237/781 [00:12<00:29, 18.20it/s]
 31%|###       | 239/781 [00:12<00:29, 18.09it/s]
 31%|###       | 241/781 [00:12<00:30, 17.96it/s]
 31%|###1      | 243/781 [00:12<00:29, 18.01it/s]
 31%|###1      | 245/781 [00:12<00:29, 18.04it/s]
 32%|###1      | 247/781 [00:13<00:29, 17.94it/s]
 32%|###1      | 249/781 [00:13<00:29, 18.05it/s]
 32%|###2      | 251/781 [00:13<00:29, 17.98it/s]
 32%|###2      | 253/781 [00:13<00:29, 18.00it/s]
 33%|###2      | 255/781 [00:13<00:29, 17.95it/s]
 33%|###2      | 257/781 [00:13<00:28, 18.08it/s]
 33%|###3      | 259/781 [00:13<00:28, 18.06it/s]
 33%|###3      | 261/781 [00:13<00:29, 17.93it/s]
 34%|###3      | 263/781 [00:13<00:28, 17.88it/s]
 34%|###3      | 265/781 [00:14<00:28, 17.90it/s]
 34%|###4      | 267/781 [00:14<00:28, 17.92it/s]
 34%|###4      | 269/781 [00:14<00:28, 17.99it/s]
 35%|###4      | 271/781 [00:14<00:28, 18.01it/s]
 35%|###4      | 273/781 [00:14<00:28, 18.05it/s]
 35%|###5      | 275/781 [00:14<00:28, 18.03it/s]
 35%|###5      | 277/781 [00:14<00:27, 18.14it/s]
 36%|###5      | 279/781 [00:14<00:27, 18.17it/s]
 36%|###5      | 281/781 [00:14<00:27, 18.22it/s]
 36%|###6      | 283/781 [00:15<00:27, 18.22it/s]
 36%|###6      | 285/781 [00:15<00:27, 18.11it/s]
 37%|###6      | 287/781 [00:15<00:27, 17.91it/s]
 37%|###7      | 289/781 [00:15<00:27, 17.83it/s]
 37%|###7      | 291/781 [00:15<00:27, 17.91it/s]
 38%|###7      | 293/781 [00:15<00:27, 17.88it/s]
 38%|###7      | 295/781 [00:15<00:26, 18.01it/s]
 38%|###8      | 297/781 [00:15<00:26, 17.96it/s]
 38%|###8      | 299/781 [00:15<00:26, 17.93it/s]
 39%|###8      | 301/781 [00:16<00:27, 17.71it/s]
 39%|###8      | 303/781 [00:16<00:26, 17.72it/s]
 39%|###9      | 305/781 [00:16<00:26, 17.76it/s]
 39%|###9      | 307/781 [00:16<00:26, 17.93it/s]
 40%|###9      | 309/781 [00:16<00:26, 18.05it/s]
 40%|###9      | 311/781 [00:16<00:25, 18.11it/s]
 40%|####      | 313/781 [00:16<00:26, 17.99it/s]
 40%|####      | 315/781 [00:16<00:26, 17.80it/s]
 41%|####      | 317/781 [00:16<00:26, 17.74it/s]
 41%|####      | 319/781 [00:17<00:25, 17.77it/s]
 41%|####1     | 321/781 [00:17<00:25, 17.70it/s]
 41%|####1     | 323/781 [00:17<00:26, 17.46it/s]
 42%|####1     | 325/781 [00:17<00:26, 17.22it/s]
 42%|####1     | 327/781 [00:17<00:26, 17.38it/s]
 42%|####2     | 329/781 [00:17<00:25, 17.64it/s]
 42%|####2     | 331/781 [00:17<00:25, 17.79it/s]
 43%|####2     | 333/781 [00:17<00:25, 17.84it/s]
 43%|####2     | 335/781 [00:17<00:24, 17.93it/s]
 43%|####3     | 337/781 [00:18<00:25, 17.70it/s]
 43%|####3     | 339/781 [00:18<00:24, 17.87it/s]
 44%|####3     | 341/781 [00:18<00:24, 18.02it/s]
 44%|####3     | 343/781 [00:18<00:24, 18.11it/s]
 44%|####4     | 345/781 [00:18<00:24, 18.03it/s]
 44%|####4     | 347/781 [00:18<00:24, 18.05it/s]
 45%|####4     | 349/781 [00:18<00:23, 18.14it/s]
 45%|####4     | 351/781 [00:18<00:23, 18.14it/s]
 45%|####5     | 353/781 [00:18<00:23, 18.12it/s]
 45%|####5     | 355/781 [00:19<00:24, 17.74it/s]
 46%|####5     | 357/781 [00:19<00:23, 17.87it/s]
 46%|####5     | 359/781 [00:19<00:23, 17.74it/s]
 46%|####6     | 361/781 [00:19<00:23, 17.88it/s]
 46%|####6     | 363/781 [00:19<00:23, 17.57it/s]
 47%|####6     | 365/781 [00:19<00:23, 17.81it/s]
 47%|####6     | 367/781 [00:19<00:23, 17.84it/s]
 47%|####7     | 369/781 [00:19<00:22, 17.95it/s]
 48%|####7     | 371/781 [00:19<00:22, 17.95it/s]
 48%|####7     | 373/781 [00:20<00:22, 18.05it/s]
 48%|####8     | 375/781 [00:20<00:22, 18.08it/s]
 48%|####8     | 377/781 [00:20<00:22, 17.79it/s]
 49%|####8     | 379/781 [00:20<00:22, 17.93it/s]
 49%|####8     | 381/781 [00:20<00:22, 18.02it/s]
 49%|####9     | 383/781 [00:20<00:21, 18.11it/s]
 49%|####9     | 385/781 [00:20<00:22, 17.80it/s]
 50%|####9     | 387/781 [00:20<00:22, 17.90it/s]
 50%|####9     | 389/781 [00:20<00:21, 18.05it/s]
 50%|#####     | 391/781 [00:21<00:21, 18.13it/s]
 50%|#####     | 393/781 [00:21<00:21, 18.18it/s]
 51%|#####     | 395/781 [00:21<00:21, 18.13it/s]
 51%|#####     | 397/781 [00:21<00:21, 18.11it/s]
 51%|#####1    | 399/781 [00:21<00:20, 18.21it/s]
 51%|#####1    | 401/781 [00:21<00:20, 18.22it/s]
 52%|#####1    | 403/781 [00:21<00:20, 18.25it/s]
 52%|#####1    | 405/781 [00:21<00:20, 18.20it/s]
 52%|#####2    | 407/781 [00:21<00:20, 17.99it/s]
 52%|#####2    | 409/781 [00:22<00:20, 18.05it/s]
 53%|#####2    | 411/781 [00:22<00:20, 18.18it/s]
 53%|#####2    | 413/781 [00:22<00:20, 18.11it/s]
 53%|#####3    | 415/781 [00:22<00:20, 18.11it/s]
 53%|#####3    | 417/781 [00:22<00:20, 18.19it/s]
 54%|#####3    | 419/781 [00:22<00:20, 18.02it/s]
 54%|#####3    | 421/781 [00:22<00:19, 18.06it/s]
 54%|#####4    | 423/781 [00:22<00:19, 18.15it/s]
 54%|#####4    | 425/781 [00:22<00:19, 18.13it/s]
 55%|#####4    | 427/781 [00:23<00:19, 17.94it/s]
 55%|#####4    | 429/781 [00:23<00:19, 17.94it/s]
 55%|#####5    | 431/781 [00:23<00:19, 17.96it/s]
 55%|#####5    | 433/781 [00:23<00:19, 17.94it/s]
 56%|#####5    | 435/781 [00:23<00:19, 18.00it/s]
 56%|#####5    | 437/781 [00:23<00:19, 17.98it/s]
 56%|#####6    | 439/781 [00:23<00:19, 17.81it/s]
 56%|#####6    | 441/781 [00:23<00:18, 17.91it/s]
 57%|#####6    | 443/781 [00:23<00:18, 17.99it/s]
 57%|#####6    | 445/781 [00:24<00:18, 18.08it/s]
 57%|#####7    | 447/781 [00:24<00:18, 18.19it/s]
 57%|#####7    | 449/781 [00:24<00:18, 18.17it/s]
 58%|#####7    | 451/781 [00:24<00:18, 18.13it/s]
 58%|#####8    | 453/781 [00:24<00:18, 18.16it/s]
 58%|#####8    | 455/781 [00:24<00:18, 18.07it/s]
 59%|#####8    | 457/781 [00:24<00:17, 18.12it/s]
 59%|#####8    | 459/781 [00:24<00:17, 18.14it/s]
 59%|#####9    | 461/781 [00:24<00:17, 18.19it/s]
 59%|#####9    | 463/781 [00:25<00:17, 18.20it/s]
 60%|#####9    | 465/781 [00:25<00:17, 18.21it/s]
 60%|#####9    | 467/781 [00:25<00:17, 18.04it/s]
 60%|######    | 469/781 [00:25<00:17, 18.03it/s]
 60%|######    | 471/781 [00:25<00:17, 17.96it/s]
 61%|######    | 473/781 [00:25<00:17, 17.97it/s]
 61%|######    | 475/781 [00:25<00:17, 17.97it/s]
 61%|######1   | 477/781 [00:25<00:16, 18.06it/s]
 61%|######1   | 479/781 [00:25<00:16, 17.93it/s]
 62%|######1   | 481/781 [00:26<00:16, 17.97it/s]
 62%|######1   | 483/781 [00:26<00:16, 18.14it/s]
 62%|######2   | 485/781 [00:26<00:16, 18.18it/s]
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100%|##########| 781/781 [00:42<00:00, 18.43it/s]




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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.11s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.20s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:14<00:00, 14.62s/it]
100%|##########| 1/1 [00:14<00:00, 14.62s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:11, 13.69it/s]
  3%|2         | 4/157 [00:00<00:11, 13.77it/s]
  4%|3         | 6/157 [00:00<00:10, 13.74it/s]
  5%|5         | 8/157 [00:00<00:10, 14.10it/s]
  6%|6         | 10/157 [00:00<00:10, 14.15it/s]
  8%|7         | 12/157 [00:00<00:10, 14.16it/s]
  9%|8         | 14/157 [00:00<00:10, 14.04it/s]
 10%|#         | 16/157 [00:01<00:10, 14.09it/s]
 11%|#1        | 18/157 [00:01<00:09, 14.11it/s]
 13%|#2        | 20/157 [00:01<00:09, 14.17it/s]
 14%|#4        | 22/157 [00:01<00:09, 14.33it/s]
 15%|#5        | 24/157 [00:01<00:09, 14.47it/s]
 17%|#6        | 26/157 [00:01<00:09, 14.53it/s]
 18%|#7        | 28/157 [00:01<00:08, 14.61it/s]
 19%|#9        | 30/157 [00:02<00:08, 14.52it/s]
 20%|##        | 32/157 [00:02<00:08, 14.18it/s]
 22%|##1       | 34/157 [00:02<00:08, 14.33it/s]
 23%|##2       | 36/157 [00:02<00:08, 14.30it/s]
 24%|##4       | 38/157 [00:02<00:08, 14.40it/s]
 25%|##5       | 40/157 [00:02<00:08, 14.24it/s]
 27%|##6       | 42/157 [00:02<00:07, 14.41it/s]
 28%|##8       | 44/157 [00:03<00:07, 14.51it/s]
 29%|##9       | 46/157 [00:03<00:07, 14.47it/s]
 31%|###       | 48/157 [00:03<00:07, 14.23it/s]
 32%|###1      | 50/157 [00:03<00:07, 14.14it/s]
 33%|###3      | 52/157 [00:03<00:07, 13.93it/s]
 34%|###4      | 54/157 [00:03<00:07, 13.79it/s]
 36%|###5      | 56/157 [00:03<00:07, 13.78it/s]
 37%|###6      | 58/157 [00:04<00:07, 14.01it/s]
 38%|###8      | 60/157 [00:04<00:06, 14.22it/s]
 39%|###9      | 62/157 [00:04<00:06, 14.32it/s]
 41%|####      | 64/157 [00:04<00:06, 14.46it/s]
 42%|####2     | 66/157 [00:04<00:06, 14.52it/s]
 43%|####3     | 68/157 [00:04<00:06, 14.64it/s]
 45%|####4     | 70/157 [00:04<00:05, 14.65it/s]
 46%|####5     | 72/157 [00:05<00:05, 14.67it/s]
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 48%|####8     | 76/157 [00:05<00:05, 14.72it/s]
 50%|####9     | 78/157 [00:05<00:05, 14.78it/s]
 51%|#####     | 80/157 [00:05<00:05, 14.83it/s]
 52%|#####2    | 82/157 [00:05<00:05, 14.79it/s]
 54%|#####3    | 84/157 [00:05<00:04, 14.81it/s]
 55%|#####4    | 86/157 [00:05<00:04, 14.94it/s]
 56%|#####6    | 88/157 [00:06<00:04, 14.89it/s]
 57%|#####7    | 90/157 [00:06<00:04, 14.89it/s]
 59%|#####8    | 92/157 [00:06<00:04, 14.94it/s]
 60%|#####9    | 94/157 [00:06<00:04, 14.99it/s]
 61%|######1   | 96/157 [00:06<00:04, 14.75it/s]
 62%|######2   | 98/157 [00:06<00:04, 14.53it/s]
 64%|######3   | 100/157 [00:06<00:03, 14.46it/s]
 65%|######4   | 102/157 [00:07<00:03, 14.59it/s]
 66%|######6   | 104/157 [00:07<00:03, 14.67it/s]
 68%|######7   | 106/157 [00:07<00:03, 14.74it/s]
 69%|######8   | 108/157 [00:07<00:03, 14.82it/s]
 70%|#######   | 110/157 [00:07<00:03, 14.85it/s]
 71%|#######1  | 112/157 [00:07<00:03, 14.75it/s]
 73%|#######2  | 114/157 [00:07<00:02, 14.81it/s]
 74%|#######3  | 116/157 [00:08<00:02, 14.84it/s]
 75%|#######5  | 118/157 [00:08<00:02, 14.64it/s]
 76%|#######6  | 120/157 [00:08<00:02, 14.41it/s]
 78%|#######7  | 122/157 [00:08<00:02, 14.56it/s]
 79%|#######8  | 124/157 [00:08<00:02, 14.63it/s]
 80%|########  | 126/157 [00:08<00:02, 14.67it/s]
 82%|########1 | 128/157 [00:08<00:01, 14.74it/s]
 83%|########2 | 130/157 [00:08<00:01, 14.72it/s]
 84%|########4 | 132/157 [00:09<00:01, 14.64it/s]
 85%|########5 | 134/157 [00:09<00:01, 14.61it/s]
 87%|########6 | 136/157 [00:09<00:01, 14.68it/s]
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 89%|########9 | 140/157 [00:09<00:01, 14.33it/s]
 90%|######### | 142/157 [00:09<00:01, 14.30it/s]
 92%|#########1| 144/157 [00:09<00:00, 14.44it/s]
 93%|#########2| 146/157 [00:10<00:00, 14.59it/s]
 94%|#########4| 148/157 [00:10<00:00, 14.69it/s]
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 99%|#########9| 156/157 [00:10<00:00, 14.76it/s]
100%|##########| 157/157 [00:10<00:00, 14.56it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:40, 19.28it/s]
  1%|          | 4/781 [00:00<00:39, 19.67it/s]
  1%|          | 6/781 [00:00<00:39, 19.67it/s]
  1%|1         | 8/781 [00:00<00:39, 19.66it/s]
  1%|1         | 10/781 [00:00<00:39, 19.63it/s]
  2%|1         | 12/781 [00:00<00:39, 19.56it/s]
  2%|1         | 14/781 [00:00<00:39, 19.51it/s]
  2%|2         | 16/781 [00:00<00:39, 19.57it/s]
  2%|2         | 19/781 [00:00<00:38, 19.86it/s]
  3%|2         | 22/781 [00:01<00:37, 20.03it/s]
  3%|3         | 25/781 [00:01<00:37, 20.12it/s]
  4%|3         | 28/781 [00:01<00:37, 20.32it/s]
  4%|3         | 31/781 [00:01<00:36, 20.31it/s]
  4%|4         | 34/781 [00:01<00:36, 20.29it/s]
  5%|4         | 37/781 [00:01<00:36, 20.31it/s]
  5%|5         | 40/781 [00:01<00:36, 20.32it/s]
  6%|5         | 43/781 [00:02<00:36, 20.37it/s]
  6%|5         | 46/781 [00:02<00:36, 20.24it/s]
  6%|6         | 49/781 [00:02<00:36, 20.31it/s]
  7%|6         | 52/781 [00:02<00:35, 20.31it/s]
  7%|7         | 55/781 [00:02<00:35, 20.23it/s]
  7%|7         | 58/781 [00:02<00:35, 20.16it/s]
  8%|7         | 61/781 [00:03<00:36, 19.98it/s]
  8%|8         | 64/781 [00:03<00:36, 19.89it/s]
  8%|8         | 66/781 [00:03<00:36, 19.79it/s]
  9%|8         | 68/781 [00:03<00:36, 19.75it/s]
  9%|8         | 70/781 [00:03<00:36, 19.74it/s]
  9%|9         | 72/781 [00:03<00:36, 19.67it/s]
  9%|9         | 74/781 [00:03<00:36, 19.51it/s]
 10%|9         | 76/781 [00:03<00:36, 19.56it/s]
 10%|9         | 78/781 [00:03<00:36, 19.03it/s]
 10%|#         | 80/781 [00:04<00:37, 18.57it/s]
 10%|#         | 82/781 [00:04<00:38, 18.25it/s]
 11%|#         | 84/781 [00:04<00:38, 18.06it/s]
 11%|#1        | 86/781 [00:04<00:38, 17.88it/s]
 11%|#1        | 88/781 [00:04<00:38, 17.90it/s]
 12%|#1        | 90/781 [00:04<00:38, 17.94it/s]
 12%|#1        | 92/781 [00:04<00:38, 17.98it/s]
 12%|#2        | 94/781 [00:04<00:38, 17.93it/s]
 12%|#2        | 96/781 [00:04<00:38, 18.02it/s]
 13%|#2        | 98/781 [00:05<00:37, 18.09it/s]
 13%|#2        | 100/781 [00:05<00:37, 18.07it/s]
 13%|#3        | 102/781 [00:05<00:37, 18.15it/s]
 13%|#3        | 104/781 [00:05<00:37, 18.20it/s]
 14%|#3        | 106/781 [00:05<00:37, 18.20it/s]
 14%|#3        | 108/781 [00:05<00:36, 18.24it/s]
 14%|#4        | 110/781 [00:05<00:37, 18.07it/s]
 14%|#4        | 112/781 [00:05<00:36, 18.09it/s]
 15%|#4        | 114/781 [00:05<00:36, 18.16it/s]
 15%|#4        | 116/781 [00:06<00:36, 18.19it/s]
 15%|#5        | 118/781 [00:06<00:36, 18.13it/s]
 15%|#5        | 120/781 [00:06<00:36, 18.22it/s]
 16%|#5        | 122/781 [00:06<00:36, 18.16it/s]
 16%|#5        | 124/781 [00:06<00:36, 18.01it/s]
 16%|#6        | 126/781 [00:06<00:36, 18.03it/s]
 16%|#6        | 128/781 [00:06<00:36, 17.88it/s]
 17%|#6        | 130/781 [00:06<00:36, 17.99it/s]
 17%|#6        | 132/781 [00:06<00:35, 18.09it/s]
 17%|#7        | 134/781 [00:07<00:35, 18.16it/s]
 17%|#7        | 136/781 [00:07<00:35, 18.12it/s]
 18%|#7        | 138/781 [00:07<00:35, 18.02it/s]
 18%|#7        | 140/781 [00:07<00:35, 17.98it/s]
 18%|#8        | 142/781 [00:07<00:35, 18.10it/s]
 18%|#8        | 144/781 [00:07<00:35, 18.18it/s]
 19%|#8        | 146/781 [00:07<00:35, 18.13it/s]
 19%|#8        | 148/781 [00:07<00:34, 18.19it/s]
 19%|#9        | 150/781 [00:07<00:34, 18.12it/s]
 19%|#9        | 152/781 [00:08<00:34, 18.12it/s]
 20%|#9        | 154/781 [00:08<00:34, 18.08it/s]
 20%|#9        | 156/781 [00:08<00:34, 18.08it/s]
 20%|##        | 158/781 [00:08<00:34, 18.06it/s]
 20%|##        | 160/781 [00:08<00:34, 18.25it/s]
 21%|##        | 162/781 [00:08<01:13,  8.47it/s]
 21%|##        | 164/781 [00:09<01:01, 10.04it/s]
 21%|##1       | 166/781 [00:09<00:53, 11.57it/s]
 22%|##1       | 168/781 [00:09<00:47, 12.97it/s]
 22%|##1       | 170/781 [00:09<00:43, 14.16it/s]
 22%|##2       | 172/781 [00:09<00:40, 15.19it/s]
 22%|##2       | 174/781 [00:09<00:38, 15.93it/s]
 23%|##2       | 176/781 [00:09<00:36, 16.55it/s]
 23%|##2       | 178/781 [00:09<00:35, 16.97it/s]
 23%|##3       | 180/781 [00:09<00:34, 17.33it/s]
 23%|##3       | 182/781 [00:10<00:34, 17.20it/s]
 24%|##3       | 184/781 [00:10<00:34, 17.37it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.53it/s]
 24%|##4       | 188/781 [00:10<00:33, 17.57it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.74it/s]
 25%|##4       | 192/781 [00:10<00:32, 17.86it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.96it/s]
 25%|##5       | 196/781 [00:10<00:32, 17.94it/s]
 25%|##5       | 198/781 [00:10<00:32, 18.07it/s]
 26%|##5       | 200/781 [00:11<00:31, 18.20it/s]
 26%|##5       | 202/781 [00:11<00:31, 18.20it/s]
 26%|##6       | 204/781 [00:11<00:31, 18.18it/s]
 26%|##6       | 206/781 [00:11<00:31, 18.18it/s]
 27%|##6       | 208/781 [00:11<00:31, 18.22it/s]
 27%|##6       | 210/781 [00:11<00:31, 18.26it/s]
 27%|##7       | 212/781 [00:11<00:31, 18.22it/s]
 27%|##7       | 214/781 [00:11<00:31, 18.27it/s]
 28%|##7       | 216/781 [00:11<00:31, 18.21it/s]
 28%|##7       | 218/781 [00:12<00:31, 17.95it/s]
 28%|##8       | 220/781 [00:12<00:31, 17.98it/s]
 28%|##8       | 222/781 [00:12<00:31, 18.00it/s]
 29%|##8       | 224/781 [00:12<00:31, 17.80it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.87it/s]
 29%|##9       | 228/781 [00:12<00:30, 18.00it/s]
 29%|##9       | 230/781 [00:12<00:30, 18.07it/s]
 30%|##9       | 232/781 [00:12<00:30, 18.11it/s]
 30%|##9       | 234/781 [00:12<00:30, 18.18it/s]
 30%|###       | 236/781 [00:13<00:30, 17.97it/s]
 30%|###       | 238/781 [00:13<00:30, 17.87it/s]
 31%|###       | 240/781 [00:13<00:30, 17.88it/s]
 31%|###       | 242/781 [00:13<00:30, 17.95it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.07it/s]
 31%|###1      | 246/781 [00:13<00:29, 17.90it/s]
 32%|###1      | 248/781 [00:13<00:29, 18.02it/s]
 32%|###2      | 250/781 [00:13<00:29, 17.97it/s]
 32%|###2      | 252/781 [00:13<00:29, 17.92it/s]
 33%|###2      | 254/781 [00:14<00:29, 18.03it/s]
 33%|###2      | 256/781 [00:14<00:29, 18.07it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.67it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.61it/s]
 34%|###3      | 262/781 [00:14<00:29, 17.60it/s]
 34%|###3      | 264/781 [00:14<00:29, 17.61it/s]
 34%|###4      | 266/781 [00:14<00:29, 17.55it/s]
 34%|###4      | 268/781 [00:14<00:29, 17.46it/s]
 35%|###4      | 270/781 [00:15<00:29, 17.58it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.64it/s]
 35%|###5      | 274/781 [00:15<00:28, 17.59it/s]
 35%|###5      | 276/781 [00:15<00:28, 17.60it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.72it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.81it/s]
 36%|###6      | 282/781 [00:15<00:27, 17.86it/s]
 36%|###6      | 284/781 [00:15<00:27, 17.93it/s]
 37%|###6      | 286/781 [00:15<00:27, 17.94it/s]
 37%|###6      | 288/781 [00:16<00:27, 17.99it/s]
 37%|###7      | 290/781 [00:16<00:27, 18.09it/s]
 37%|###7      | 292/781 [00:16<00:26, 18.17it/s]
 38%|###7      | 294/781 [00:16<00:26, 18.26it/s]
 38%|###7      | 296/781 [00:16<00:26, 18.24it/s]
 38%|###8      | 298/781 [00:16<00:26, 18.13it/s]
 38%|###8      | 300/781 [00:16<00:27, 17.80it/s]
 39%|###8      | 302/781 [00:16<00:27, 17.68it/s]
 39%|###8      | 304/781 [00:16<00:27, 17.65it/s]
 39%|###9      | 306/781 [00:17<00:26, 17.83it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.98it/s]
 40%|###9      | 310/781 [00:17<00:26, 18.04it/s]
 40%|###9      | 312/781 [00:17<00:25, 18.07it/s]
 40%|####      | 314/781 [00:17<00:25, 18.15it/s]
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 41%|####      | 318/781 [00:17<00:25, 17.92it/s]
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 41%|####1     | 322/781 [00:17<00:25, 17.90it/s]
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 42%|####1     | 326/781 [00:18<00:25, 18.08it/s]
 42%|####1     | 328/781 [00:18<00:25, 17.91it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.99it/s]
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 43%|####3     | 336/781 [00:18<00:24, 18.13it/s]
 43%|####3     | 338/781 [00:18<00:24, 18.13it/s]
 44%|####3     | 340/781 [00:18<00:24, 18.15it/s]
 44%|####3     | 342/781 [00:19<00:24, 18.22it/s]
 44%|####4     | 344/781 [00:19<00:23, 18.22it/s]
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 45%|####4     | 348/781 [00:19<00:23, 18.21it/s]
 45%|####4     | 350/781 [00:19<00:23, 18.24it/s]
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 46%|####6     | 360/781 [00:20<00:23, 17.94it/s]
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 47%|####7     | 368/781 [00:20<00:23, 17.88it/s]
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 50%|####9     | 388/781 [00:21<00:21, 18.00it/s]
 50%|####9     | 390/781 [00:21<00:22, 17.75it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.73it/s]
 50%|#####     | 394/781 [00:21<00:21, 17.71it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.87it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.79it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.82it/s]
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 71%|#######1  | 556/781 [00:30<00:12, 18.08it/s]
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 80%|########  | 626/781 [00:34<00:08, 17.45it/s]
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100%|#########9| 778/781 [00:43<00:00, 17.79it/s]
100%|#########9| 780/781 [00:43<00:00, 17.72it/s]
100%|##########| 781/781 [00:43<00:00, 17.95it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
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Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.01it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.00it/s]
Validation Progress:   2%|2         | 1/44 [00:01<00:44,  1.03s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.05s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:44,  1.06s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.02s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:41,  1.02s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:42,  1.03s/it]
Validation Progress:   7%|6         | 3/44 [00:03<00:42,  1.03s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.00s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.00s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.01s/it]
Validation Progress:   9%|9         | 4/44 [00:04<00:40,  1.01s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.04s/it]
Validation Progress:  11%|#1        | 5/44 [00:05<00:40,  1.05s/it]
Validation Progress:  14%|#3        | 6/44 [00:06<00:37,  1.01it/s]
Validation Progress:  14%|#3        | 6/44 [00:06<00:37,  1.01it/s]
Validation Progress:  14%|#3        | 6/44 [00:06<00:37,  1.01it/s]
Validation Progress:  14%|#3        | 6/44 [00:06<00:37,  1.01it/s]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.02s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.03s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:37,  1.03s/it]
Validation Progress:  16%|#5        | 7/44 [00:07<00:39,  1.05s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:36,  1.01s/it]
Validation Progress:  18%|#8        | 8/44 [00:08<00:37,  1.03s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.01s/it]
Validation Progress:  20%|##        | 9/44 [00:09<00:35,  1.02s/it]
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 10%|#         | 80/781 [00:04<00:36, 18.98it/s]
 10%|#         | 82/781 [00:04<00:36, 19.06it/s]
 11%|#         | 84/781 [00:04<00:36, 19.13it/s]
 11%|#1        | 86/781 [00:04<00:36, 19.17it/s]
 11%|#1        | 88/781 [00:04<00:36, 19.02it/s]
 12%|#1        | 90/781 [00:04<00:36, 19.11it/s]
 12%|#1        | 92/781 [00:04<00:35, 19.16it/s]
 12%|#2        | 94/781 [00:04<00:36, 18.75it/s]
 12%|#2        | 96/781 [00:05<00:36, 18.71it/s]
 13%|#2        | 98/781 [00:05<00:36, 18.71it/s]
 13%|#2        | 100/781 [00:05<00:36, 18.74it/s]
 13%|#3        | 102/781 [00:05<00:36, 18.71it/s]
 13%|#3        | 104/781 [00:05<00:36, 18.75it/s]
 14%|#3        | 106/781 [00:05<00:36, 18.71it/s]
 14%|#3        | 108/781 [00:05<00:35, 18.85it/s]
 14%|#4        | 110/781 [00:05<00:35, 18.93it/s]
 14%|#4        | 112/781 [00:05<00:35, 19.06it/s]
 15%|#4        | 114/781 [00:06<00:35, 18.92it/s]
 15%|#4        | 116/781 [00:06<00:35, 18.60it/s]
 15%|#5        | 118/781 [00:06<00:35, 18.52it/s]
 15%|#5        | 120/781 [00:06<00:35, 18.61it/s]
 16%|#5        | 122/781 [00:06<00:35, 18.49it/s]
 16%|#5        | 124/781 [00:06<00:35, 18.65it/s]
 16%|#6        | 126/781 [00:06<00:34, 18.84it/s]
 16%|#6        | 128/781 [00:06<00:34, 18.85it/s]
 17%|#6        | 130/781 [00:06<00:34, 18.73it/s]
 17%|#6        | 132/781 [00:07<00:34, 18.72it/s]
 17%|#7        | 134/781 [00:07<00:34, 18.83it/s]
 17%|#7        | 136/781 [00:07<00:34, 18.79it/s]
 18%|#7        | 138/781 [00:07<00:34, 18.80it/s]
 18%|#7        | 140/781 [00:07<00:34, 18.66it/s]
 18%|#8        | 142/781 [00:07<00:34, 18.72it/s]
 18%|#8        | 144/781 [00:07<00:34, 18.56it/s]
 19%|#8        | 146/781 [00:07<00:34, 18.64it/s]
 19%|#8        | 148/781 [00:07<00:33, 18.72it/s]
 19%|#9        | 150/781 [00:07<00:33, 18.82it/s]
 19%|#9        | 152/781 [00:08<00:33, 18.63it/s]
 20%|#9        | 154/781 [00:08<00:33, 18.77it/s]
 20%|#9        | 156/781 [00:08<00:33, 18.92it/s]
 20%|##        | 158/781 [00:08<00:33, 18.80it/s]
 20%|##        | 160/781 [00:08<00:33, 18.81it/s]
 21%|##        | 162/781 [00:08<00:33, 18.69it/s]
 21%|##        | 164/781 [00:08<00:33, 18.67it/s]
 21%|##1       | 166/781 [00:08<00:33, 18.61it/s]
 22%|##1       | 168/781 [00:08<00:33, 18.45it/s]
 22%|##1       | 170/781 [00:09<00:33, 18.23it/s]
 22%|##2       | 172/781 [00:09<00:33, 18.27it/s]
 22%|##2       | 174/781 [00:09<00:33, 18.34it/s]
 23%|##2       | 176/781 [00:09<00:32, 18.44it/s]
 23%|##2       | 178/781 [00:09<00:32, 18.57it/s]
 23%|##3       | 180/781 [00:09<00:32, 18.67it/s]
 23%|##3       | 182/781 [00:09<00:32, 18.56it/s]
 24%|##3       | 184/781 [00:09<00:32, 18.65it/s]
 24%|##3       | 186/781 [00:09<00:31, 18.61it/s]
 24%|##4       | 188/781 [00:10<00:31, 18.64it/s]
 24%|##4       | 190/781 [00:10<00:31, 18.53it/s]
 25%|##4       | 192/781 [00:10<00:32, 18.04it/s]
 25%|##4       | 194/781 [00:10<00:32, 18.21it/s]
 25%|##5       | 196/781 [00:10<00:32, 18.22it/s]
 25%|##5       | 198/781 [00:10<00:31, 18.31it/s]
 26%|##5       | 200/781 [00:10<00:31, 18.38it/s]
 26%|##5       | 202/781 [00:10<00:31, 18.41it/s]
 26%|##6       | 204/781 [00:10<00:31, 18.55it/s]
 26%|##6       | 206/781 [00:11<00:30, 18.79it/s]
 27%|##6       | 208/781 [00:11<00:30, 18.72it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.73it/s]
 27%|##7       | 212/781 [00:11<00:30, 18.80it/s]
 27%|##7       | 214/781 [00:11<00:30, 18.65it/s]
 28%|##7       | 216/781 [00:11<00:30, 18.76it/s]
 28%|##7       | 218/781 [00:11<00:29, 18.94it/s]
 28%|##8       | 220/781 [00:11<00:29, 18.84it/s]
 28%|##8       | 222/781 [00:11<00:30, 18.53it/s]
 29%|##8       | 224/781 [00:11<00:30, 18.55it/s]
 29%|##8       | 226/781 [00:12<00:29, 18.62it/s]
 29%|##9       | 228/781 [00:12<00:29, 18.74it/s]
 29%|##9       | 230/781 [00:12<00:29, 18.82it/s]
 30%|##9       | 232/781 [00:12<00:28, 19.01it/s]
 30%|##9       | 234/781 [00:12<00:29, 18.85it/s]
 30%|###       | 236/781 [00:12<00:28, 18.80it/s]
 30%|###       | 238/781 [00:12<00:28, 19.10it/s]
 31%|###       | 240/781 [00:12<00:28, 19.23it/s]
 31%|###       | 242/781 [00:12<00:27, 19.34it/s]
 31%|###1      | 244/781 [00:13<00:27, 19.39it/s]
 31%|###1      | 246/781 [00:13<00:27, 19.39it/s]
 32%|###1      | 248/781 [00:13<00:27, 19.24it/s]
 32%|###2      | 250/781 [00:13<00:27, 19.35it/s]
 32%|###2      | 252/781 [00:13<00:27, 19.25it/s]
 33%|###2      | 254/781 [00:13<00:27, 19.17it/s]
 33%|###2      | 256/781 [00:13<00:27, 19.25it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.13it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.14it/s]
 34%|###3      | 262/781 [00:13<00:26, 19.30it/s]
 34%|###3      | 264/781 [00:14<00:26, 19.49it/s]
 34%|###4      | 266/781 [00:14<00:26, 19.60it/s]
 34%|###4      | 268/781 [00:14<00:26, 19.68it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.62it/s]
 35%|###4      | 272/781 [00:14<00:25, 19.65it/s]
 35%|###5      | 274/781 [00:14<00:25, 19.73it/s]
 35%|###5      | 276/781 [00:14<00:25, 19.66it/s]
 36%|###5      | 278/781 [00:14<00:25, 19.57it/s]
 36%|###5      | 280/781 [00:14<00:25, 19.55it/s]
 36%|###6      | 282/781 [00:14<00:25, 19.64it/s]
 36%|###6      | 284/781 [00:15<00:25, 19.73it/s]
 37%|###6      | 286/781 [00:15<00:25, 19.47it/s]
 37%|###6      | 288/781 [00:15<00:25, 19.52it/s]
 37%|###7      | 290/781 [00:15<00:25, 19.64it/s]
 37%|###7      | 292/781 [00:15<00:24, 19.65it/s]
 38%|###7      | 294/781 [00:15<00:24, 19.67it/s]
 38%|###7      | 296/781 [00:15<00:24, 19.67it/s]
 38%|###8      | 298/781 [00:15<00:24, 19.32it/s]
 38%|###8      | 300/781 [00:15<00:25, 19.12it/s]
 39%|###8      | 302/781 [00:15<00:24, 19.32it/s]
 39%|###8      | 304/781 [00:16<00:24, 19.15it/s]
 39%|###9      | 306/781 [00:16<00:24, 19.32it/s]
 40%|###9      | 309/781 [00:16<00:24, 19.60it/s]
 40%|###9      | 311/781 [00:16<00:23, 19.64it/s]
 40%|####      | 313/781 [00:16<00:23, 19.72it/s]
 40%|####      | 316/781 [00:16<00:23, 19.84it/s]
 41%|####      | 318/781 [00:16<00:23, 19.64it/s]
 41%|####      | 320/781 [00:16<00:23, 19.59it/s]
 41%|####1     | 322/781 [00:17<00:23, 19.41it/s]
 41%|####1     | 324/781 [00:17<00:23, 19.35it/s]
 42%|####1     | 326/781 [00:17<00:23, 19.42it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.53it/s]
 42%|####2     | 330/781 [00:17<00:23, 19.42it/s]
 43%|####2     | 332/781 [00:17<00:23, 19.17it/s]
 43%|####2     | 334/781 [00:17<00:23, 18.67it/s]
 43%|####3     | 336/781 [00:17<00:24, 18.51it/s]
 43%|####3     | 338/781 [00:17<00:23, 18.66it/s]
 44%|####3     | 340/781 [00:17<00:23, 18.72it/s]
 44%|####3     | 342/781 [00:18<00:23, 18.93it/s]
 44%|####4     | 344/781 [00:18<00:22, 19.10it/s]
 44%|####4     | 346/781 [00:18<00:23, 18.78it/s]
 45%|####4     | 348/781 [00:18<00:22, 18.93it/s]
 45%|####4     | 350/781 [00:18<00:22, 19.03it/s]
 45%|####5     | 352/781 [00:18<00:22, 18.87it/s]
 45%|####5     | 354/781 [00:18<00:22, 18.72it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.65it/s]
 46%|####5     | 358/781 [00:18<00:22, 18.62it/s]
 46%|####6     | 360/781 [00:19<00:22, 18.41it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.58it/s]
 47%|####6     | 364/781 [00:19<00:22, 18.55it/s]
 47%|####6     | 366/781 [00:19<00:22, 18.54it/s]
 47%|####7     | 368/781 [00:19<00:22, 18.46it/s]
 47%|####7     | 370/781 [00:19<00:22, 18.61it/s]
 48%|####7     | 372/781 [00:19<00:22, 18.56it/s]
 48%|####7     | 374/781 [00:19<00:21, 18.88it/s]
 48%|####8     | 376/781 [00:19<00:21, 18.65it/s]
 48%|####8     | 378/781 [00:20<00:21, 18.39it/s]
 49%|####8     | 380/781 [00:20<00:22, 18.20it/s]
 49%|####8     | 382/781 [00:20<00:21, 18.14it/s]
 49%|####9     | 384/781 [00:20<00:21, 18.17it/s]
 49%|####9     | 386/781 [00:20<00:21, 18.55it/s]
 50%|####9     | 388/781 [00:20<00:21, 18.69it/s]
 50%|####9     | 390/781 [00:20<00:20, 18.92it/s]
 50%|#####     | 392/781 [00:20<00:20, 18.96it/s]
 50%|#####     | 394/781 [00:20<00:20, 19.01it/s]
 51%|#####     | 396/781 [00:20<00:20, 19.10it/s]
 51%|#####     | 398/781 [00:21<00:19, 19.33it/s]
 51%|#####1    | 401/781 [00:21<00:19, 19.61it/s]
 52%|#####1    | 403/781 [00:21<00:19, 19.67it/s]
 52%|#####1    | 405/781 [00:21<00:19, 19.73it/s]
 52%|#####2    | 407/781 [00:21<00:18, 19.72it/s]
 52%|#####2    | 409/781 [00:21<00:19, 19.56it/s]
 53%|#####2    | 412/781 [00:21<00:18, 19.70it/s]
 53%|#####3    | 414/781 [00:21<00:18, 19.45it/s]
 53%|#####3    | 416/781 [00:21<00:18, 19.48it/s]
 54%|#####3    | 418/781 [00:22<00:18, 19.57it/s]
 54%|#####3    | 420/781 [00:22<00:18, 19.43it/s]
 54%|#####4    | 422/781 [00:22<00:18, 19.49it/s]
 54%|#####4    | 424/781 [00:22<00:18, 19.30it/s]
 55%|#####4    | 426/781 [00:22<00:18, 19.31it/s]
 55%|#####4    | 428/781 [00:22<00:18, 19.36it/s]
 55%|#####5    | 430/781 [00:22<00:18, 19.37it/s]
 55%|#####5    | 432/781 [00:22<00:18, 19.38it/s]
 56%|#####5    | 434/781 [00:22<00:17, 19.48it/s]
 56%|#####5    | 436/781 [00:23<00:17, 19.47it/s]
 56%|#####6    | 438/781 [00:23<00:17, 19.48it/s]
 56%|#####6    | 441/781 [00:23<00:17, 19.69it/s]
 57%|#####6    | 443/781 [00:23<00:17, 19.64it/s]
 57%|#####6    | 445/781 [00:23<00:17, 19.59it/s]
 57%|#####7    | 447/781 [00:23<00:17, 19.57it/s]
 57%|#####7    | 449/781 [00:23<00:16, 19.60it/s]
 58%|#####7    | 451/781 [00:23<00:16, 19.65it/s]
 58%|#####8    | 453/781 [00:23<00:16, 19.64it/s]
 58%|#####8    | 455/781 [00:23<00:16, 19.62it/s]
 59%|#####8    | 457/781 [00:24<00:16, 19.64it/s]
 59%|#####8    | 459/781 [00:24<00:16, 19.61it/s]
 59%|#####9    | 461/781 [00:24<00:16, 19.63it/s]
 59%|#####9    | 463/781 [00:24<00:16, 19.71it/s]
 60%|#####9    | 465/781 [00:24<00:15, 19.77it/s]
 60%|#####9    | 467/781 [00:24<00:15, 19.79it/s]
 60%|######    | 469/781 [00:24<00:15, 19.69it/s]
 60%|######    | 472/781 [00:24<00:15, 19.82it/s]
 61%|######    | 474/781 [00:24<00:15, 19.61it/s]
 61%|######    | 476/781 [00:25<00:15, 19.48it/s]
 61%|######1   | 478/781 [00:25<00:15, 19.62it/s]
 61%|######1   | 480/781 [00:25<00:15, 19.61it/s]
 62%|######1   | 482/781 [00:25<00:15, 19.65it/s]
 62%|######1   | 484/781 [00:25<00:15, 19.74it/s]
 62%|######2   | 486/781 [00:25<00:14, 19.81it/s]
 62%|######2   | 488/781 [00:25<00:14, 19.77it/s]
 63%|######2   | 491/781 [00:25<00:14, 19.84it/s]
 63%|######3   | 493/781 [00:25<00:14, 19.68it/s]
 63%|######3   | 495/781 [00:26<00:14, 19.63it/s]
 64%|######3   | 498/781 [00:26<00:14, 19.79it/s]
 64%|######4   | 500/781 [00:26<00:14, 19.80it/s]
 64%|######4   | 502/781 [00:26<00:14, 19.69it/s]
 65%|######4   | 504/781 [00:26<00:14, 19.72it/s]
 65%|######4   | 506/781 [00:26<00:13, 19.80it/s]
 65%|######5   | 508/781 [00:26<00:13, 19.83it/s]
 65%|######5   | 510/781 [00:26<00:14, 19.33it/s]
 66%|######5   | 512/781 [00:26<00:13, 19.34it/s]
 66%|######5   | 514/781 [00:26<00:13, 19.23it/s]
 66%|######6   | 516/781 [00:27<00:13, 18.96it/s]
 66%|######6   | 518/781 [00:27<00:13, 19.00it/s]
 67%|######6   | 520/781 [00:27<00:13, 18.99it/s]
 67%|######6   | 522/781 [00:27<00:13, 19.21it/s]
 67%|######7   | 524/781 [00:27<00:13, 19.28it/s]
 67%|######7   | 526/781 [00:27<00:13, 18.91it/s]
 68%|######7   | 528/781 [00:27<00:14, 17.61it/s]
 68%|######7   | 530/781 [00:27<00:14, 17.76it/s]
 68%|######8   | 532/781 [00:27<00:14, 17.75it/s]
 68%|######8   | 534/781 [00:28<00:13, 17.83it/s]
 69%|######8   | 536/781 [00:28<00:13, 17.75it/s]
 69%|######8   | 538/781 [00:28<00:13, 18.03it/s]
 69%|######9   | 540/781 [00:28<00:13, 18.26it/s]
 69%|######9   | 542/781 [00:28<00:13, 18.23it/s]
 70%|######9   | 544/781 [00:28<00:13, 18.01it/s]
 70%|######9   | 546/781 [00:28<00:13, 18.01it/s]
 70%|#######   | 548/781 [00:28<00:12, 18.15it/s]
 70%|#######   | 550/781 [00:28<00:12, 18.41it/s]
 71%|#######   | 552/781 [00:29<00:12, 18.81it/s]
 71%|#######1  | 555/781 [00:29<00:11, 19.08it/s]
 71%|#######1  | 558/781 [00:29<00:11, 19.40it/s]
 72%|#######1  | 560/781 [00:29<00:11, 19.52it/s]
 72%|#######1  | 562/781 [00:29<00:11, 19.43it/s]
 72%|#######2  | 564/781 [00:29<00:11, 19.53it/s]
 72%|#######2  | 566/781 [00:29<00:11, 19.34it/s]
 73%|#######2  | 568/781 [00:29<00:11, 19.26it/s]
 73%|#######2  | 570/781 [00:29<00:10, 19.35it/s]
 73%|#######3  | 572/781 [00:30<00:10, 19.45it/s]
 73%|#######3  | 574/781 [00:30<00:10, 19.45it/s]
 74%|#######3  | 576/781 [00:30<00:10, 19.53it/s]
 74%|#######4  | 578/781 [00:30<00:10, 19.57it/s]
 74%|#######4  | 580/781 [00:30<00:10, 19.44it/s]
 75%|#######4  | 582/781 [00:30<00:10, 19.46it/s]
 75%|#######4  | 585/781 [00:30<00:10, 19.42it/s]
 75%|#######5  | 587/781 [00:30<00:09, 19.43it/s]
 75%|#######5  | 589/781 [00:30<00:09, 19.56it/s]
 76%|#######5  | 591/781 [00:31<00:09, 19.52it/s]
 76%|#######5  | 593/781 [00:31<00:09, 19.64it/s]
 76%|#######6  | 595/781 [00:31<00:09, 19.73it/s]
 77%|#######6  | 598/781 [00:31<00:09, 19.73it/s]
 77%|#######6  | 600/781 [00:31<00:09, 19.63it/s]
 77%|#######7  | 602/781 [00:31<00:09, 19.72it/s]
 77%|#######7  | 604/781 [00:31<00:09, 19.53it/s]
 78%|#######7  | 606/781 [00:31<00:08, 19.54it/s]
 78%|#######7  | 608/781 [00:31<00:08, 19.54it/s]
 78%|#######8  | 610/781 [00:32<00:08, 19.56it/s]
 78%|#######8  | 612/781 [00:32<00:08, 19.61it/s]
 79%|#######8  | 614/781 [00:32<00:08, 19.67it/s]
 79%|#######8  | 616/781 [00:32<00:08, 19.66it/s]
 79%|#######9  | 618/781 [00:32<00:08, 19.68it/s]
 79%|#######9  | 620/781 [00:32<00:08, 19.72it/s]
 80%|#######9  | 622/781 [00:32<00:08, 19.75it/s]
 80%|#######9  | 624/781 [00:32<00:08, 19.61it/s]
 80%|########  | 626/781 [00:32<00:07, 19.65it/s]
 80%|########  | 628/781 [00:32<00:07, 19.55it/s]
 81%|########  | 630/781 [00:33<00:07, 19.68it/s]
 81%|########  | 632/781 [00:33<00:07, 19.75it/s]
 81%|########1 | 634/781 [00:33<00:07, 19.80it/s]
 81%|########1 | 636/781 [00:33<00:07, 19.65it/s]
 82%|########1 | 638/781 [00:33<00:07, 19.49it/s]
 82%|########1 | 640/781 [00:33<00:07, 19.42it/s]
 82%|########2 | 642/781 [00:33<00:07, 19.27it/s]
 82%|########2 | 644/781 [00:33<00:07, 18.76it/s]
 83%|########2 | 646/781 [00:33<00:07, 18.67it/s]
 83%|########2 | 648/781 [00:33<00:07, 18.76it/s]
 83%|########3 | 650/781 [00:34<00:06, 18.85it/s]
 83%|########3 | 652/781 [00:34<00:06, 18.97it/s]
 84%|########3 | 655/781 [00:34<00:06, 19.37it/s]
 84%|########4 | 657/781 [00:34<00:06, 19.34it/s]
 84%|########4 | 659/781 [00:34<00:06, 19.46it/s]
 85%|########4 | 661/781 [00:34<00:06, 19.47it/s]
 85%|########4 | 663/781 [00:34<00:06, 19.59it/s]
 85%|########5 | 665/781 [00:34<00:05, 19.66it/s]
 85%|########5 | 667/781 [00:34<00:05, 19.66it/s]
 86%|########5 | 669/781 [00:35<00:05, 19.69it/s]
 86%|########6 | 672/781 [00:35<00:05, 19.82it/s]
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 25%|##5       | 40/157 [00:02<00:06, 17.26it/s]
 27%|##6       | 42/157 [00:02<00:06, 17.26it/s]
 28%|##8       | 44/157 [00:02<00:06, 17.37it/s]
 29%|##9       | 46/157 [00:02<00:06, 17.38it/s]
 31%|###       | 48/157 [00:02<00:06, 17.53it/s]
 32%|###1      | 50/157 [00:02<00:06, 17.70it/s]
 33%|###3      | 52/157 [00:03<00:05, 17.81it/s]
 34%|###4      | 54/157 [00:03<00:05, 17.87it/s]
 36%|###5      | 56/157 [00:03<00:05, 17.83it/s]
 37%|###6      | 58/157 [00:03<00:05, 17.89it/s]
 38%|###8      | 60/157 [00:03<00:05, 17.94it/s]
 39%|###9      | 62/157 [00:03<00:05, 17.93it/s]
 41%|####      | 64/157 [00:03<00:05, 17.79it/s]
 42%|####2     | 66/157 [00:03<00:05, 17.91it/s]
 43%|####3     | 68/157 [00:03<00:04, 18.01it/s]
 45%|####4     | 70/157 [00:04<00:04, 17.94it/s]
 46%|####5     | 72/157 [00:04<00:04, 17.85it/s]
 47%|####7     | 74/157 [00:04<00:04, 17.81it/s]
 48%|####8     | 76/157 [00:04<00:04, 17.51it/s]
 50%|####9     | 78/157 [00:04<00:04, 17.51it/s]
 51%|#####     | 80/157 [00:04<00:04, 17.54it/s]
 52%|#####2    | 82/157 [00:04<00:04, 17.52it/s]
 54%|#####3    | 84/157 [00:04<00:04, 17.52it/s]
 55%|#####4    | 86/157 [00:04<00:04, 17.31it/s]
 56%|#####6    | 88/157 [00:05<00:04, 17.07it/s]
 57%|#####7    | 90/157 [00:05<00:03, 17.16it/s]
 59%|#####8    | 92/157 [00:05<00:03, 17.37it/s]
 60%|#####9    | 94/157 [00:05<00:03, 17.46it/s]
 61%|######1   | 96/157 [00:05<00:03, 17.41it/s]
 62%|######2   | 98/157 [00:05<00:03, 17.35it/s]
 64%|######3   | 100/157 [00:05<00:03, 16.95it/s]
 65%|######4   | 102/157 [00:05<00:03, 17.07it/s]
 66%|######6   | 104/157 [00:06<00:03, 16.86it/s]
 68%|######7   | 106/157 [00:06<00:03, 16.96it/s]
 69%|######8   | 108/157 [00:06<00:02, 16.80it/s]
 70%|#######   | 110/157 [00:06<00:02, 17.11it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.96it/s]
 73%|#######2  | 114/157 [00:06<00:02, 17.07it/s]
 74%|#######3  | 116/157 [00:06<00:02, 17.03it/s]
 75%|#######5  | 118/157 [00:06<00:02, 16.68it/s]
 76%|#######6  | 120/157 [00:06<00:02, 16.36it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.49it/s]
 79%|#######8  | 124/157 [00:07<00:01, 16.62it/s]
 80%|########  | 126/157 [00:07<00:01, 16.80it/s]
 82%|########1 | 128/157 [00:07<00:01, 16.96it/s]
 83%|########2 | 130/157 [00:07<00:01, 17.07it/s]
 84%|########4 | 132/157 [00:07<00:01, 17.24it/s]
 85%|########5 | 134/157 [00:07<00:01, 17.38it/s]
 87%|########6 | 136/157 [00:07<00:01, 17.49it/s]
 88%|########7 | 138/157 [00:08<00:01, 17.65it/s]
 89%|########9 | 140/157 [00:08<00:00, 17.65it/s]
 90%|######### | 142/157 [00:08<00:00, 17.71it/s]
 92%|#########1| 144/157 [00:08<00:00, 17.87it/s]
 93%|#########2| 146/157 [00:08<00:00, 17.80it/s]
 94%|#########4| 148/157 [00:08<00:00, 17.87it/s]
 96%|#########5| 150/157 [00:08<00:00, 17.83it/s]
 97%|#########6| 152/157 [00:08<00:00, 17.66it/s]
 98%|#########8| 154/157 [00:08<00:00, 17.68it/s]
 99%|#########9| 156/157 [00:09<00:00, 17.78it/s]
100%|##########| 157/157 [00:09<00:00, 17.37it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:39, 19.91it/s]
  1%|          | 5/781 [00:00<00:38, 20.13it/s]
  1%|1         | 8/781 [00:00<00:37, 20.36it/s]
  1%|1         | 11/781 [00:00<00:37, 20.41it/s]
  2%|1         | 14/781 [00:00<00:37, 20.27it/s]
  2%|2         | 17/781 [00:00<00:37, 20.14it/s]
  3%|2         | 20/781 [00:00<00:37, 20.35it/s]
  3%|2         | 23/781 [00:01<00:36, 20.49it/s]
  3%|3         | 26/781 [00:01<00:37, 20.40it/s]
  4%|3         | 29/781 [00:01<00:36, 20.38it/s]
  4%|4         | 32/781 [00:01<00:36, 20.35it/s]
  4%|4         | 35/781 [00:01<00:36, 20.34it/s]
  5%|4         | 38/781 [00:01<00:36, 20.43it/s]
  5%|5         | 41/781 [00:02<00:36, 20.29it/s]
  6%|5         | 44/781 [00:02<00:36, 20.14it/s]
  6%|6         | 47/781 [00:02<00:36, 20.23it/s]
  6%|6         | 50/781 [00:02<00:36, 20.30it/s]
  7%|6         | 53/781 [00:02<00:35, 20.26it/s]
  7%|7         | 56/781 [00:02<00:35, 20.34it/s]
  8%|7         | 59/781 [00:02<00:35, 20.42it/s]
  8%|7         | 62/781 [00:03<00:35, 20.32it/s]
  8%|8         | 65/781 [00:03<00:35, 20.24it/s]
  9%|8         | 68/781 [00:03<00:35, 20.24it/s]
  9%|9         | 71/781 [00:03<00:35, 20.17it/s]
  9%|9         | 74/781 [00:03<00:34, 20.21it/s]
 10%|9         | 77/781 [00:03<00:34, 20.26it/s]
 10%|#         | 80/781 [00:03<00:34, 20.21it/s]
 11%|#         | 83/781 [00:04<00:34, 20.22it/s]
 11%|#1        | 86/781 [00:04<00:34, 20.06it/s]
 11%|#1        | 89/781 [00:04<00:34, 20.12it/s]
 12%|#1        | 92/781 [00:04<00:34, 20.07it/s]
 12%|#2        | 95/781 [00:04<00:34, 20.05it/s]
 13%|#2        | 98/781 [00:04<00:33, 20.11it/s]
 13%|#2        | 101/781 [00:04<00:33, 20.30it/s]
 13%|#3        | 104/781 [00:05<00:34, 19.91it/s]
 14%|#3        | 107/781 [00:05<00:33, 20.03it/s]
 14%|#4        | 110/781 [00:05<00:33, 20.19it/s]
 14%|#4        | 113/781 [00:05<00:33, 20.06it/s]
 15%|#4        | 116/781 [00:05<00:33, 19.85it/s]
 15%|#5        | 119/781 [00:05<00:33, 19.99it/s]
 16%|#5        | 122/781 [00:06<00:32, 20.19it/s]
 16%|#6        | 125/781 [00:06<00:32, 20.27it/s]
 16%|#6        | 128/781 [00:06<00:32, 20.00it/s]
 17%|#6        | 131/781 [00:06<00:32, 20.02it/s]
 17%|#7        | 134/781 [00:06<00:32, 20.17it/s]
 18%|#7        | 137/781 [00:06<00:32, 19.83it/s]
 18%|#7        | 139/781 [00:06<00:32, 19.53it/s]
 18%|#8        | 141/781 [00:07<00:33, 18.86it/s]
 18%|#8        | 143/781 [00:07<00:34, 18.57it/s]
 19%|#8        | 145/781 [00:07<00:34, 18.42it/s]
 19%|#8        | 147/781 [00:07<00:34, 18.30it/s]
 19%|#9        | 149/781 [00:07<00:34, 18.20it/s]
 19%|#9        | 151/781 [00:07<00:34, 18.22it/s]
 20%|#9        | 153/781 [00:07<00:34, 18.28it/s]
 20%|#9        | 155/781 [00:07<00:34, 18.17it/s]
 20%|##        | 157/781 [00:07<00:34, 18.17it/s]
 20%|##        | 159/781 [00:08<00:34, 18.22it/s]
 21%|##        | 161/781 [00:08<00:33, 18.24it/s]
 21%|##        | 163/781 [00:08<00:33, 18.26it/s]
 21%|##1       | 165/781 [00:08<00:33, 18.22it/s]
 21%|##1       | 167/781 [00:08<00:33, 18.17it/s]
 22%|##1       | 169/781 [00:08<00:33, 18.08it/s]
 22%|##1       | 171/781 [00:08<00:34, 17.85it/s]
 22%|##2       | 173/781 [00:08<00:34, 17.85it/s]
 22%|##2       | 175/781 [00:08<00:33, 17.88it/s]
 23%|##2       | 177/781 [00:09<00:33, 17.83it/s]
 23%|##2       | 179/781 [00:09<00:33, 17.90it/s]
 23%|##3       | 181/781 [00:09<00:33, 17.75it/s]
 23%|##3       | 183/781 [00:09<00:33, 17.91it/s]
 24%|##3       | 185/781 [00:09<00:33, 18.01it/s]
 24%|##3       | 187/781 [00:09<00:33, 17.89it/s]
 24%|##4       | 189/781 [00:09<00:33, 17.86it/s]
 24%|##4       | 191/781 [00:09<00:32, 17.89it/s]
 25%|##4       | 193/781 [00:09<00:32, 18.12it/s]
 25%|##4       | 195/781 [00:10<00:32, 17.84it/s]
 25%|##5       | 197/781 [00:10<00:32, 18.02it/s]
 25%|##5       | 199/781 [00:10<00:31, 18.22it/s]
 26%|##5       | 201/781 [00:10<00:31, 18.39it/s]
 26%|##5       | 203/781 [00:10<00:31, 18.56it/s]
 26%|##6       | 205/781 [00:10<00:31, 18.11it/s]
 27%|##6       | 207/781 [00:10<00:31, 18.21it/s]
 27%|##6       | 209/781 [00:10<00:31, 18.03it/s]
 27%|##7       | 211/781 [00:10<00:31, 18.16it/s]
 27%|##7       | 213/781 [00:10<00:30, 18.56it/s]
 28%|##7       | 215/781 [00:11<00:30, 18.84it/s]
 28%|##7       | 218/781 [00:11<00:29, 19.13it/s]
 28%|##8       | 221/781 [00:11<00:28, 19.52it/s]
 29%|##8       | 224/781 [00:11<00:28, 19.86it/s]
 29%|##9       | 227/781 [00:11<00:27, 20.10it/s]
 29%|##9       | 230/781 [00:11<00:27, 20.16it/s]
 30%|##9       | 233/781 [00:11<00:27, 19.98it/s]
 30%|###       | 236/781 [00:12<00:27, 19.96it/s]
 31%|###       | 239/781 [00:12<00:27, 20.07it/s]
 31%|###       | 242/781 [00:12<00:26, 20.03it/s]
 31%|###1      | 245/781 [00:12<00:27, 19.78it/s]
 32%|###1      | 247/781 [00:12<00:27, 19.75it/s]
 32%|###2      | 250/781 [00:12<00:26, 19.94it/s]
 32%|###2      | 253/781 [00:12<00:26, 20.11it/s]
 33%|###2      | 256/781 [00:13<00:26, 20.07it/s]
 33%|###3      | 259/781 [00:13<00:25, 20.14it/s]
 34%|###3      | 262/781 [00:13<00:26, 19.91it/s]
 34%|###3      | 265/781 [00:13<00:25, 20.09it/s]
 34%|###4      | 268/781 [00:13<00:25, 20.25it/s]
 35%|###4      | 271/781 [00:13<00:25, 20.08it/s]
 35%|###5      | 274/781 [00:14<00:25, 20.10it/s]
 35%|###5      | 277/781 [00:14<00:24, 20.17it/s]
 36%|###5      | 280/781 [00:14<00:24, 20.08it/s]
 36%|###6      | 283/781 [00:14<00:24, 20.18it/s]
 37%|###6      | 286/781 [00:14<00:24, 20.33it/s]
 37%|###7      | 289/781 [00:14<00:24, 20.18it/s]
 37%|###7      | 292/781 [00:14<00:24, 20.24it/s]
 38%|###7      | 295/781 [00:15<00:24, 20.21it/s]
 38%|###8      | 298/781 [00:15<00:23, 20.35it/s]
 39%|###8      | 301/781 [00:15<00:23, 20.37it/s]
 39%|###8      | 304/781 [00:15<00:23, 20.37it/s]
 39%|###9      | 307/781 [00:15<00:23, 20.46it/s]
 40%|###9      | 310/781 [00:15<00:23, 20.32it/s]
 40%|####      | 313/781 [00:15<00:23, 20.09it/s]
 40%|####      | 316/781 [00:16<00:23, 20.07it/s]
 41%|####      | 319/781 [00:16<00:22, 20.26it/s]
 41%|####1     | 322/781 [00:16<00:22, 20.36it/s]
 42%|####1     | 325/781 [00:16<00:22, 20.27it/s]
 42%|####1     | 328/781 [00:16<00:22, 20.26it/s]
 42%|####2     | 331/781 [00:16<00:22, 20.32it/s]
 43%|####2     | 334/781 [00:17<00:22, 20.03it/s]
 43%|####3     | 337/781 [00:17<00:22, 19.85it/s]
 44%|####3     | 340/781 [00:17<00:22, 19.96it/s]
 44%|####3     | 342/781 [00:17<00:22, 19.91it/s]
 44%|####4     | 345/781 [00:17<00:21, 20.06it/s]
 45%|####4     | 348/781 [00:17<00:21, 19.98it/s]
 45%|####4     | 351/781 [00:17<00:21, 20.06it/s]
 45%|####5     | 354/781 [00:18<00:21, 19.89it/s]
 46%|####5     | 357/781 [00:18<00:21, 19.98it/s]
 46%|####6     | 360/781 [00:18<00:20, 20.15it/s]
 46%|####6     | 363/781 [00:18<00:20, 20.24it/s]
 47%|####6     | 366/781 [00:18<00:20, 20.20it/s]
 47%|####7     | 369/781 [00:18<00:21, 19.51it/s]
 48%|####7     | 371/781 [00:18<00:21, 19.45it/s]
 48%|####7     | 373/781 [00:18<00:21, 18.85it/s]
 48%|####8     | 375/781 [00:19<00:21, 19.11it/s]
 48%|####8     | 378/781 [00:19<00:20, 19.38it/s]
 49%|####8     | 380/781 [00:19<00:20, 19.41it/s]
 49%|####8     | 382/781 [00:19<00:20, 19.50it/s]
 49%|####9     | 385/781 [00:19<00:20, 19.79it/s]
 50%|####9     | 387/781 [00:19<00:20, 19.67it/s]
 50%|####9     | 389/781 [00:19<00:19, 19.63it/s]
 50%|#####     | 392/781 [00:19<00:19, 19.99it/s]
 51%|#####     | 395/781 [00:20<00:19, 20.04it/s]
 51%|#####     | 398/781 [00:20<00:19, 20.13it/s]
 51%|#####1    | 401/781 [00:20<00:18, 20.11it/s]
 52%|#####1    | 404/781 [00:20<00:18, 19.98it/s]
 52%|#####1    | 406/781 [00:20<00:18, 19.95it/s]
 52%|#####2    | 408/781 [00:20<00:19, 19.56it/s]
 53%|#####2    | 411/781 [00:20<00:18, 19.82it/s]
 53%|#####3    | 414/781 [00:21<00:18, 20.03it/s]
 53%|#####3    | 417/781 [00:21<00:18, 20.13it/s]
 54%|#####3    | 420/781 [00:21<00:17, 20.19it/s]
 54%|#####4    | 423/781 [00:21<00:17, 20.34it/s]
 55%|#####4    | 426/781 [00:21<00:17, 20.16it/s]
 55%|#####4    | 429/781 [00:21<00:17, 20.08it/s]
 55%|#####5    | 432/781 [00:21<00:17, 20.08it/s]
 56%|#####5    | 435/781 [00:22<00:17, 20.16it/s]
 56%|#####6    | 438/781 [00:22<00:17, 20.15it/s]
 56%|#####6    | 441/781 [00:22<00:16, 20.09it/s]
 57%|#####6    | 444/781 [00:22<00:16, 19.87it/s]
 57%|#####7    | 446/781 [00:22<00:16, 19.89it/s]
 57%|#####7    | 449/781 [00:22<00:16, 20.02it/s]
 58%|#####7    | 452/781 [00:22<00:16, 20.16it/s]
 58%|#####8    | 455/781 [00:23<00:16, 20.15it/s]
 59%|#####8    | 458/781 [00:23<00:16, 20.11it/s]
 59%|#####9    | 461/781 [00:23<00:15, 20.09it/s]
 59%|#####9    | 464/781 [00:23<00:15, 20.15it/s]
 60%|#####9    | 467/781 [00:23<00:15, 20.29it/s]
 60%|######    | 470/781 [00:23<00:15, 20.29it/s]
 61%|######    | 473/781 [00:23<00:15, 20.35it/s]
 61%|######    | 476/781 [00:24<00:14, 20.41it/s]
 61%|######1   | 479/781 [00:24<00:14, 20.37it/s]
 62%|######1   | 482/781 [00:24<00:14, 20.24it/s]
 62%|######2   | 485/781 [00:24<00:14, 20.36it/s]
 62%|######2   | 488/781 [00:24<00:14, 19.88it/s]
 63%|######2   | 490/781 [00:24<00:14, 19.87it/s]
 63%|######3   | 493/781 [00:24<00:14, 20.03it/s]
 64%|######3   | 496/781 [00:25<00:14, 20.08it/s]
 64%|######3   | 499/781 [00:25<00:13, 20.21it/s]
 64%|######4   | 502/781 [00:25<00:13, 20.22it/s]
 65%|######4   | 505/781 [00:25<00:13, 19.97it/s]
 65%|######5   | 508/781 [00:25<00:13, 19.74it/s]
 65%|######5   | 511/781 [00:25<00:13, 19.99it/s]
 66%|######5   | 514/781 [00:26<00:13, 19.99it/s]
 66%|######6   | 517/781 [00:26<00:13, 20.11it/s]
 67%|######6   | 520/781 [00:26<00:13, 20.00it/s]
 67%|######6   | 523/781 [00:26<00:12, 20.08it/s]
 67%|######7   | 526/781 [00:26<00:12, 19.73it/s]
 68%|######7   | 528/781 [00:26<00:12, 19.71it/s]
 68%|######7   | 530/781 [00:26<00:12, 19.59it/s]
 68%|######8   | 532/781 [00:26<00:12, 19.50it/s]
 68%|######8   | 534/781 [00:27<00:12, 19.51it/s]
 69%|######8   | 536/781 [00:27<00:12, 19.29it/s]
 69%|######8   | 538/781 [00:27<00:12, 19.40it/s]
 69%|######9   | 540/781 [00:27<00:12, 18.84it/s]
 69%|######9   | 542/781 [00:27<00:12, 18.46it/s]
 70%|######9   | 544/781 [00:27<00:13, 18.00it/s]
 70%|######9   | 546/781 [00:27<00:13, 17.86it/s]
 70%|#######   | 548/781 [00:27<00:12, 18.12it/s]
 70%|#######   | 550/781 [00:27<00:12, 17.98it/s]
 71%|#######   | 552/781 [00:28<00:12, 17.96it/s]
 71%|#######   | 554/781 [00:28<00:12, 17.79it/s]
 71%|#######1  | 556/781 [00:28<00:12, 17.79it/s]
 71%|#######1  | 558/781 [00:28<00:12, 17.85it/s]
 72%|#######1  | 560/781 [00:28<00:12, 17.91it/s]
 72%|#######1  | 562/781 [00:28<00:12, 17.90it/s]
 72%|#######2  | 564/781 [00:28<00:12, 17.97it/s]
 72%|#######2  | 566/781 [00:28<00:12, 17.76it/s]
 73%|#######2  | 568/781 [00:28<00:11, 17.83it/s]
 73%|#######2  | 570/781 [00:29<00:11, 17.90it/s]
 73%|#######3  | 572/781 [00:29<00:11, 17.97it/s]
 73%|#######3  | 574/781 [00:29<00:11, 18.04it/s]
 74%|#######3  | 576/781 [00:29<00:11, 18.09it/s]
 74%|#######4  | 578/781 [00:29<00:11, 17.95it/s]
 74%|#######4  | 580/781 [00:29<00:11, 18.01it/s]
 75%|#######4  | 582/781 [00:29<00:11, 17.78it/s]
 75%|#######4  | 584/781 [00:29<00:11, 17.88it/s]
 75%|#######5  | 586/781 [00:29<00:10, 17.88it/s]
 75%|#######5  | 588/781 [00:30<00:10, 17.93it/s]
 76%|#######5  | 590/781 [00:30<00:10, 17.94it/s]
 76%|#######5  | 592/781 [00:30<00:10, 18.00it/s]
 76%|#######6  | 594/781 [00:30<00:10, 18.07it/s]
 76%|#######6  | 596/781 [00:30<00:10, 18.05it/s]
 77%|#######6  | 598/781 [00:30<00:10, 18.04it/s]
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Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.21s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.21s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.21s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.21s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.02s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:16<00:00, 16.56s/it]
100%|##########| 1/1 [00:16<00:00, 16.56s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:11, 13.99it/s]
  3%|2         | 4/157 [00:00<00:09, 15.44it/s]
  4%|3         | 6/157 [00:00<00:09, 16.46it/s]
  5%|5         | 8/157 [00:00<00:08, 17.04it/s]
  6%|6         | 10/157 [00:00<00:08, 17.22it/s]
  8%|7         | 12/157 [00:00<00:08, 17.22it/s]
  9%|8         | 14/157 [00:00<00:08, 17.37it/s]
 10%|#         | 16/157 [00:00<00:08, 17.40it/s]
 11%|#1        | 18/157 [00:01<00:08, 17.23it/s]
 13%|#2        | 20/157 [00:01<00:07, 17.18it/s]
 14%|#4        | 22/157 [00:01<00:07, 17.42it/s]
 15%|#5        | 24/157 [00:01<00:07, 17.26it/s]
 17%|#6        | 26/157 [00:01<00:07, 17.34it/s]
 18%|#7        | 28/157 [00:01<00:07, 17.43it/s]
 19%|#9        | 30/157 [00:01<00:07, 17.35it/s]
 20%|##        | 32/157 [00:01<00:07, 17.18it/s]
 22%|##1       | 34/157 [00:01<00:07, 17.29it/s]
 23%|##2       | 36/157 [00:02<00:07, 17.10it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.58it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.31it/s]
 27%|##6       | 42/157 [00:02<00:07, 16.13it/s]
 28%|##8       | 44/157 [00:02<00:07, 15.98it/s]
 29%|##9       | 46/157 [00:02<00:06, 15.93it/s]
 31%|###       | 48/157 [00:02<00:06, 15.96it/s]
 32%|###1      | 50/157 [00:02<00:06, 15.89it/s]
 33%|###3      | 52/157 [00:03<00:06, 15.93it/s]
 34%|###4      | 54/157 [00:03<00:06, 15.86it/s]
 36%|###5      | 56/157 [00:03<00:06, 15.86it/s]
 37%|###6      | 58/157 [00:03<00:06, 15.79it/s]
 38%|###8      | 60/157 [00:03<00:06, 15.61it/s]
 39%|###9      | 62/157 [00:03<00:06, 15.59it/s]
 41%|####      | 64/157 [00:03<00:06, 15.46it/s]
 42%|####2     | 66/157 [00:04<00:05, 15.55it/s]
 43%|####3     | 68/157 [00:04<00:05, 15.60it/s]
 45%|####4     | 70/157 [00:04<00:05, 15.76it/s]
 46%|####5     | 72/157 [00:04<00:05, 15.64it/s]
 47%|####7     | 74/157 [00:04<00:05, 15.69it/s]
 48%|####8     | 76/157 [00:04<00:05, 15.90it/s]
 50%|####9     | 78/157 [00:04<00:04, 16.01it/s]
 51%|#####     | 80/157 [00:04<00:04, 16.06it/s]
 52%|#####2    | 82/157 [00:05<00:04, 16.36it/s]
 54%|#####3    | 84/157 [00:05<00:04, 16.17it/s]
 55%|#####4    | 86/157 [00:05<00:04, 16.35it/s]
 56%|#####6    | 88/157 [00:05<00:04, 16.49it/s]
 57%|#####7    | 90/157 [00:05<00:04, 16.64it/s]
 59%|#####8    | 92/157 [00:05<00:03, 16.40it/s]
 60%|#####9    | 94/157 [00:05<00:03, 16.49it/s]
 61%|######1   | 96/157 [00:05<00:03, 16.65it/s]
 62%|######2   | 98/157 [00:05<00:03, 16.78it/s]
 64%|######3   | 100/157 [00:06<00:03, 16.69it/s]
 65%|######4   | 102/157 [00:06<00:03, 16.91it/s]
 66%|######6   | 104/157 [00:06<00:03, 16.80it/s]
 68%|######7   | 106/157 [00:06<00:02, 17.08it/s]
 69%|######8   | 108/157 [00:06<00:02, 17.39it/s]
 70%|#######   | 110/157 [00:06<00:02, 17.55it/s]
 71%|#######1  | 112/157 [00:06<00:02, 17.40it/s]
 73%|#######2  | 114/157 [00:06<00:02, 17.55it/s]
 74%|#######3  | 116/157 [00:07<00:02, 17.52it/s]
 75%|#######5  | 118/157 [00:07<00:02, 17.63it/s]
 76%|#######6  | 120/157 [00:07<00:02, 17.67it/s]
 78%|#######7  | 122/157 [00:07<00:01, 17.67it/s]
 79%|#######8  | 124/157 [00:07<00:01, 17.74it/s]
 80%|########  | 126/157 [00:07<00:01, 17.54it/s]
 82%|########1 | 128/157 [00:07<00:01, 17.38it/s]
 83%|########2 | 130/157 [00:07<00:01, 17.43it/s]
 84%|########4 | 132/157 [00:07<00:01, 17.47it/s]
 85%|########5 | 134/157 [00:08<00:01, 17.35it/s]
 87%|########6 | 136/157 [00:08<00:01, 17.40it/s]
 88%|########7 | 138/157 [00:08<00:01, 17.36it/s]
 89%|########9 | 140/157 [00:08<00:00, 17.49it/s]
 90%|######### | 142/157 [00:08<00:00, 17.40it/s]
 92%|#########1| 144/157 [00:08<00:00, 17.60it/s]
 93%|#########2| 146/157 [00:08<00:00, 17.58it/s]
 94%|#########4| 148/157 [00:08<00:00, 17.71it/s]
 96%|#########5| 150/157 [00:08<00:00, 17.74it/s]
 97%|#########6| 152/157 [00:09<00:00, 17.75it/s]
 98%|#########8| 154/157 [00:09<00:00, 17.55it/s]
 99%|#########9| 156/157 [00:09<00:00, 17.58it/s]
100%|##########| 157/157 [00:09<00:00, 16.85it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:41, 18.60it/s]
  1%|          | 4/781 [00:00<00:40, 19.14it/s]
  1%|          | 7/781 [00:00<00:39, 19.75it/s]
  1%|1         | 10/781 [00:00<00:38, 20.03it/s]
  2%|1         | 13/781 [00:00<00:37, 20.23it/s]
  2%|2         | 16/781 [00:00<00:37, 20.20it/s]
  2%|2         | 19/781 [00:00<00:37, 20.26it/s]
  3%|2         | 22/781 [00:01<00:37, 20.25it/s]
  3%|3         | 25/781 [00:01<00:37, 20.30it/s]
  4%|3         | 28/781 [00:01<00:36, 20.38it/s]
  4%|3         | 31/781 [00:01<00:36, 20.39it/s]
  4%|4         | 34/781 [00:01<00:36, 20.22it/s]
  5%|4         | 37/781 [00:01<00:36, 20.23it/s]
  5%|5         | 40/781 [00:01<00:36, 20.31it/s]
  6%|5         | 43/781 [00:02<00:36, 20.00it/s]
  6%|5         | 46/781 [00:02<00:36, 20.05it/s]
  6%|6         | 49/781 [00:02<00:37, 19.56it/s]
  7%|6         | 51/781 [00:02<00:37, 19.49it/s]
  7%|6         | 53/781 [00:02<00:38, 18.96it/s]
  7%|7         | 55/781 [00:02<00:39, 18.48it/s]
  7%|7         | 57/781 [00:02<00:39, 18.25it/s]
  8%|7         | 59/781 [00:03<00:39, 18.11it/s]
  8%|7         | 61/781 [00:03<00:39, 18.27it/s]
  8%|8         | 63/781 [00:03<00:39, 18.10it/s]
  8%|8         | 65/781 [00:03<00:39, 18.08it/s]
  9%|8         | 67/781 [00:03<00:39, 17.85it/s]
  9%|8         | 69/781 [00:03<00:39, 17.88it/s]
  9%|9         | 71/781 [00:03<00:38, 18.24it/s]
  9%|9         | 73/781 [00:03<00:39, 17.92it/s]
 10%|9         | 75/781 [00:03<00:39, 17.83it/s]
 10%|9         | 77/781 [00:04<00:39, 18.01it/s]
 10%|#         | 79/781 [00:04<00:39, 18.00it/s]
 10%|#         | 81/781 [00:04<00:38, 18.02it/s]
 11%|#         | 83/781 [00:04<00:39, 17.87it/s]
 11%|#         | 85/781 [00:04<00:38, 18.22it/s]
 11%|#1        | 87/781 [00:04<00:37, 18.33it/s]
 11%|#1        | 89/781 [00:04<00:39, 17.62it/s]
 12%|#1        | 91/781 [00:04<00:39, 17.65it/s]
 12%|#1        | 93/781 [00:04<00:38, 17.89it/s]
 12%|#2        | 95/781 [00:05<00:38, 17.84it/s]
 12%|#2        | 97/781 [00:05<00:38, 17.81it/s]
 13%|#2        | 99/781 [00:05<00:38, 17.89it/s]
 13%|#2        | 101/781 [00:05<00:38, 17.86it/s]
 13%|#3        | 103/781 [00:05<00:37, 17.93it/s]
 13%|#3        | 105/781 [00:05<00:37, 17.83it/s]
 14%|#3        | 107/781 [00:05<00:37, 17.91it/s]
 14%|#3        | 109/781 [00:05<00:37, 18.10it/s]
 14%|#4        | 111/781 [00:05<00:36, 18.41it/s]
 14%|#4        | 113/781 [00:06<00:36, 18.32it/s]
 15%|#4        | 115/781 [00:06<00:36, 18.22it/s]
 15%|#4        | 117/781 [00:06<00:36, 18.35it/s]
 15%|#5        | 119/781 [00:06<00:35, 18.42it/s]
 15%|#5        | 121/781 [00:06<00:36, 18.26it/s]
 16%|#5        | 123/781 [00:06<00:36, 18.18it/s]
 16%|#6        | 125/781 [00:06<00:36, 18.16it/s]
 16%|#6        | 127/781 [00:06<00:35, 18.22it/s]
 17%|#6        | 129/781 [00:06<00:34, 18.66it/s]
 17%|#6        | 131/781 [00:06<00:34, 18.74it/s]
 17%|#7        | 133/781 [00:07<00:35, 18.23it/s]
 17%|#7        | 135/781 [00:07<00:34, 18.56it/s]
 18%|#7        | 138/781 [00:07<00:33, 19.32it/s]
 18%|#8        | 141/781 [00:07<00:32, 19.74it/s]
 18%|#8        | 144/781 [00:07<00:32, 19.78it/s]
 19%|#8        | 147/781 [00:07<00:31, 20.03it/s]
 19%|#9        | 149/781 [00:07<00:31, 19.94it/s]
 19%|#9        | 151/781 [00:07<00:32, 19.64it/s]
 20%|#9        | 153/781 [00:08<00:31, 19.70it/s]
 20%|#9        | 155/781 [00:08<00:32, 19.49it/s]
 20%|##        | 157/781 [00:08<00:32, 19.01it/s]
 20%|##        | 159/781 [00:08<00:33, 18.59it/s]
 21%|##        | 161/781 [00:08<00:33, 18.27it/s]
 21%|##        | 163/781 [00:08<00:34, 18.11it/s]
 21%|##1       | 165/781 [00:08<00:34, 17.99it/s]
 21%|##1       | 167/781 [00:08<00:34, 17.84it/s]
 22%|##1       | 169/781 [00:08<00:34, 17.85it/s]
 22%|##1       | 171/781 [00:09<00:34, 17.83it/s]
 22%|##2       | 173/781 [00:09<00:33, 17.96it/s]
 22%|##2       | 175/781 [00:09<00:33, 17.90it/s]
 23%|##2       | 177/781 [00:09<00:34, 17.71it/s]
 23%|##2       | 179/781 [00:09<00:34, 17.58it/s]
 23%|##3       | 181/781 [00:09<00:34, 17.62it/s]
 23%|##3       | 183/781 [00:09<00:33, 17.61it/s]
 24%|##3       | 185/781 [00:09<00:33, 17.65it/s]
 24%|##3       | 187/781 [00:10<00:33, 17.69it/s]
 24%|##4       | 189/781 [00:10<00:33, 17.70it/s]
 24%|##4       | 191/781 [00:10<00:33, 17.60it/s]
 25%|##4       | 193/781 [00:10<00:33, 17.30it/s]
 25%|##4       | 195/781 [00:10<00:33, 17.25it/s]
 25%|##5       | 197/781 [00:10<00:33, 17.41it/s]
 25%|##5       | 199/781 [00:10<00:33, 17.55it/s]
 26%|##5       | 201/781 [00:10<00:32, 17.73it/s]
 26%|##6       | 204/781 [00:10<00:31, 18.39it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.88it/s]
 27%|##6       | 208/781 [00:11<00:31, 18.15it/s]
 27%|##6       | 210/781 [00:11<00:30, 18.51it/s]
 27%|##7       | 212/781 [00:11<00:30, 18.73it/s]
 28%|##7       | 215/781 [00:11<00:29, 19.39it/s]
 28%|##7       | 217/781 [00:11<00:29, 19.28it/s]
 28%|##8       | 219/781 [00:11<00:28, 19.45it/s]
 28%|##8       | 221/781 [00:11<00:28, 19.60it/s]
 29%|##8       | 224/781 [00:11<00:27, 19.96it/s]
 29%|##8       | 226/781 [00:12<00:28, 19.81it/s]
 29%|##9       | 228/781 [00:12<00:27, 19.76it/s]
 30%|##9       | 231/781 [00:12<00:27, 19.95it/s]
 30%|##9       | 233/781 [00:12<00:27, 19.95it/s]
 30%|###       | 235/781 [00:12<00:27, 19.90it/s]
 30%|###       | 238/781 [00:12<00:26, 20.13it/s]
 31%|###       | 241/781 [00:12<00:26, 20.19it/s]
 31%|###1      | 244/781 [00:12<00:26, 20.24it/s]
 32%|###1      | 247/781 [00:13<00:26, 20.13it/s]
 32%|###2      | 250/781 [00:13<00:26, 20.00it/s]
 32%|###2      | 253/781 [00:13<00:26, 19.96it/s]
 33%|###2      | 255/781 [00:13<00:26, 19.84it/s]
 33%|###3      | 258/781 [00:13<00:26, 19.95it/s]
 33%|###3      | 260/781 [00:13<00:26, 19.94it/s]
 34%|###3      | 262/781 [00:14<00:47, 10.97it/s]
 34%|###3      | 265/781 [00:14<00:39, 13.04it/s]
 34%|###4      | 268/781 [00:14<00:34, 14.83it/s]
 35%|###4      | 271/781 [00:14<00:31, 16.27it/s]
 35%|###4      | 273/781 [00:14<00:29, 16.97it/s]
 35%|###5      | 276/781 [00:14<00:28, 18.02it/s]
 36%|###5      | 279/781 [00:15<00:26, 18.75it/s]
 36%|###6      | 282/781 [00:15<00:25, 19.26it/s]
 36%|###6      | 285/781 [00:15<00:25, 19.69it/s]
 37%|###6      | 288/781 [00:15<00:24, 19.93it/s]
 37%|###7      | 291/781 [00:15<00:24, 19.96it/s]
 38%|###7      | 294/781 [00:15<00:24, 20.12it/s]
 38%|###8      | 297/781 [00:15<00:23, 20.19it/s]
 38%|###8      | 300/781 [00:16<00:23, 20.19it/s]
 39%|###8      | 303/781 [00:16<00:23, 20.25it/s]
 39%|###9      | 306/781 [00:16<00:23, 20.29it/s]
 40%|###9      | 309/781 [00:16<00:23, 20.36it/s]
 40%|###9      | 312/781 [00:16<00:23, 20.21it/s]
 40%|####      | 315/781 [00:16<00:23, 19.92it/s]
 41%|####      | 318/781 [00:16<00:23, 20.01it/s]
 41%|####1     | 321/781 [00:17<00:22, 20.09it/s]
 41%|####1     | 324/781 [00:17<00:22, 20.20it/s]
 42%|####1     | 327/781 [00:17<00:22, 20.10it/s]
 42%|####2     | 330/781 [00:17<00:22, 20.00it/s]
 43%|####2     | 333/781 [00:17<00:22, 19.92it/s]
 43%|####2     | 335/781 [00:17<00:23, 19.14it/s]
 43%|####3     | 337/781 [00:17<00:23, 18.63it/s]
 43%|####3     | 339/781 [00:18<00:24, 18.23it/s]
 44%|####3     | 341/781 [00:18<00:24, 18.01it/s]
 44%|####3     | 343/781 [00:18<00:25, 17.36it/s]
 44%|####4     | 345/781 [00:18<00:25, 17.23it/s]
 44%|####4     | 347/781 [00:18<00:25, 17.30it/s]
 45%|####4     | 349/781 [00:18<00:25, 17.18it/s]
 45%|####4     | 351/781 [00:18<00:24, 17.20it/s]
 45%|####5     | 353/781 [00:18<00:24, 17.19it/s]
 45%|####5     | 355/781 [00:19<00:24, 17.37it/s]
 46%|####5     | 357/781 [00:19<00:24, 17.58it/s]
 46%|####5     | 359/781 [00:19<00:23, 17.74it/s]
 46%|####6     | 361/781 [00:19<00:23, 17.78it/s]
 46%|####6     | 363/781 [00:19<00:23, 17.79it/s]
 47%|####6     | 365/781 [00:19<00:23, 17.92it/s]
 47%|####6     | 367/781 [00:19<00:23, 18.00it/s]
 47%|####7     | 369/781 [00:19<00:22, 17.97it/s]
 48%|####7     | 371/781 [00:19<00:22, 17.89it/s]
 48%|####7     | 373/781 [00:20<00:22, 17.81it/s]
 48%|####8     | 375/781 [00:20<00:22, 17.88it/s]
 48%|####8     | 377/781 [00:20<00:22, 17.95it/s]
 49%|####8     | 379/781 [00:20<00:22, 18.05it/s]
 49%|####8     | 381/781 [00:20<00:22, 18.13it/s]
 49%|####9     | 383/781 [00:20<00:21, 18.17it/s]
 49%|####9     | 385/781 [00:20<00:21, 18.25it/s]
 50%|####9     | 387/781 [00:20<00:21, 18.24it/s]
 50%|####9     | 389/781 [00:20<00:21, 18.11it/s]
 50%|#####     | 391/781 [00:21<00:21, 18.16it/s]
 50%|#####     | 393/781 [00:21<00:21, 18.20it/s]
 51%|#####     | 395/781 [00:21<00:21, 18.12it/s]
 51%|#####     | 397/781 [00:21<00:21, 18.19it/s]
 51%|#####1    | 399/781 [00:21<00:20, 18.22it/s]
 51%|#####1    | 401/781 [00:21<00:21, 18.09it/s]
 52%|#####1    | 403/781 [00:21<00:20, 18.04it/s]
 52%|#####1    | 405/781 [00:21<00:20, 18.09it/s]
 52%|#####2    | 407/781 [00:21<00:20, 17.92it/s]
 52%|#####2    | 409/781 [00:22<00:20, 17.95it/s]
 53%|#####2    | 411/781 [00:22<00:20, 18.04it/s]
 53%|#####2    | 413/781 [00:22<00:20, 18.08it/s]
 53%|#####3    | 415/781 [00:22<00:20, 18.05it/s]
 53%|#####3    | 417/781 [00:22<00:20, 18.11it/s]
 54%|#####3    | 419/781 [00:22<00:19, 18.15it/s]
 54%|#####3    | 421/781 [00:22<00:19, 18.10it/s]
 54%|#####4    | 423/781 [00:22<00:19, 18.07it/s]
 54%|#####4    | 425/781 [00:22<00:19, 18.00it/s]
 55%|#####4    | 427/781 [00:23<00:19, 18.00it/s]
 55%|#####4    | 429/781 [00:23<00:19, 17.94it/s]
 55%|#####5    | 431/781 [00:23<00:19, 17.92it/s]
 55%|#####5    | 433/781 [00:23<00:19, 17.90it/s]
 56%|#####5    | 435/781 [00:23<00:19, 17.96it/s]
 56%|#####5    | 437/781 [00:23<00:19, 17.96it/s]
 56%|#####6    | 439/781 [00:23<00:19, 17.99it/s]
 56%|#####6    | 441/781 [00:23<00:19, 17.89it/s]
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100%|##########| 781/781 [00:42<00:00, 18.40it/s]




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Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.13s/it]
Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.12s/it]
Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.13s/it]
Validation Progress:  59%|#####9    | 26/44 [00:27<00:20,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
Validation Progress:  61%|######1   | 27/44 [00:28<00:19,  1.13s/it]
Validation Progress:  64%|######3   | 28/44 [00:29<00:17,  1.12s/it]
Validation Progress:  64%|######3   | 28/44 [00:29<00:17,  1.12s/it]
Validation Progress:  64%|######3   | 28/44 [00:29<00:17,  1.12s/it]
Validation Progress:  64%|######3   | 28/44 [00:29<00:17,  1.12s/it]
Validation Progress:  66%|######5   | 29/44 [00:30<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:30<00:16,  1.10s/it]
Validation Progress:  66%|######5   | 29/44 [00:30<00:16,  1.09s/it]
Validation Progress:  66%|######5   | 29/44 [00:30<00:16,  1.10s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.11s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.11s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.11s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.11s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.10s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.11s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.09s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  77%|#######7  | 34/44 [00:36<00:11,  1.18s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:37<00:10,  1.17s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.18s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.18s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.18s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.18s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.21s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.17s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:42<00:05,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:43<00:04,  1.16s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.09s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:17<00:00, 17.51s/it]
100%|##########| 1/1 [00:17<00:00, 17.51s/it]

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  8%|7         | 12/157 [00:00<00:10, 14.27it/s]
  9%|8         | 14/157 [00:00<00:09, 14.36it/s]
 10%|#         | 16/157 [00:01<00:09, 14.38it/s]
 11%|#1        | 18/157 [00:01<00:09, 14.43it/s]
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 18%|#7        | 28/157 [00:01<00:08, 14.40it/s]
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 41%|####      | 64/157 [00:04<00:06, 14.28it/s]
 42%|####2     | 66/157 [00:04<00:06, 14.19it/s]
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100%|##########| 157/157 [00:10<00:00, 14.34it/s]

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 21%|##        | 162/781 [00:10<00:39, 15.59it/s]
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 21%|##1       | 166/781 [00:10<00:38, 15.83it/s]
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 22%|##2       | 172/781 [00:10<00:38, 15.96it/s]
 22%|##2       | 174/781 [00:10<00:37, 16.01it/s]
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 29%|##9       | 228/781 [00:14<00:33, 16.38it/s]
 29%|##9       | 230/781 [00:14<00:33, 16.27it/s]
 30%|##9       | 232/781 [00:14<00:33, 16.17it/s]
 30%|##9       | 234/781 [00:14<00:34, 16.04it/s]
 30%|###       | 236/781 [00:14<00:34, 15.85it/s]
 30%|###       | 238/781 [00:14<00:34, 15.94it/s]
 31%|###       | 240/781 [00:15<00:33, 16.04it/s]
 31%|###       | 242/781 [00:15<00:33, 16.06it/s]
 31%|###1      | 244/781 [00:15<00:33, 16.14it/s]
 31%|###1      | 246/781 [00:15<00:33, 16.13it/s]
 32%|###1      | 248/781 [00:15<00:33, 16.04it/s]
 32%|###2      | 250/781 [00:15<00:33, 15.90it/s]
 32%|###2      | 252/781 [00:15<00:33, 15.84it/s]
 33%|###2      | 254/781 [00:15<00:33, 15.87it/s]
 33%|###2      | 256/781 [00:16<00:33, 15.86it/s]
 33%|###3      | 258/781 [00:16<00:32, 15.93it/s]
 33%|###3      | 260/781 [00:16<00:32, 15.93it/s]
 34%|###3      | 262/781 [00:16<00:32, 16.02it/s]
 34%|###3      | 264/781 [00:16<00:32, 15.98it/s]
 34%|###4      | 266/781 [00:16<00:33, 15.52it/s]
 34%|###4      | 268/781 [00:16<00:32, 15.62it/s]
 35%|###4      | 270/781 [00:16<00:32, 15.76it/s]
 35%|###4      | 272/781 [00:17<00:32, 15.86it/s]
 35%|###5      | 274/781 [00:17<00:31, 15.97it/s]
 35%|###5      | 276/781 [00:17<00:31, 16.01it/s]
 36%|###5      | 278/781 [00:17<00:31, 16.09it/s]
 36%|###5      | 280/781 [00:17<00:31, 16.07it/s]
 36%|###6      | 282/781 [00:17<00:30, 16.13it/s]
 36%|###6      | 284/781 [00:17<00:31, 16.03it/s]
 37%|###6      | 286/781 [00:17<00:31, 15.95it/s]
 37%|###6      | 288/781 [00:18<00:30, 15.99it/s]
 37%|###7      | 290/781 [00:18<00:30, 15.92it/s]
 37%|###7      | 292/781 [00:18<00:30, 15.99it/s]
 38%|###7      | 294/781 [00:18<00:30, 16.04it/s]
 38%|###7      | 296/781 [00:18<00:30, 15.94it/s]
 38%|###8      | 298/781 [00:18<00:30, 16.04it/s]
 38%|###8      | 300/781 [00:18<00:29, 16.10it/s]
 39%|###8      | 302/781 [00:18<00:29, 16.15it/s]
 39%|###8      | 304/781 [00:19<00:29, 16.17it/s]
 39%|###9      | 306/781 [00:19<00:29, 16.21it/s]
 39%|###9      | 308/781 [00:19<00:29, 16.25it/s]
 40%|###9      | 310/781 [00:19<00:29, 16.06it/s]
 40%|###9      | 312/781 [00:19<00:29, 16.02it/s]
 40%|####      | 314/781 [00:19<00:29, 16.07it/s]
 40%|####      | 316/781 [00:19<00:28, 16.06it/s]
 41%|####      | 318/781 [00:19<00:28, 16.01it/s]
 41%|####      | 320/781 [00:20<00:28, 15.90it/s]
 41%|####1     | 322/781 [00:20<00:29, 15.79it/s]
 41%|####1     | 324/781 [00:20<00:28, 15.84it/s]
 42%|####1     | 326/781 [00:20<00:28, 15.86it/s]
 42%|####1     | 328/781 [00:20<00:28, 15.81it/s]
 42%|####2     | 330/781 [00:20<00:28, 15.85it/s]
 43%|####2     | 332/781 [00:20<00:28, 15.89it/s]
 43%|####2     | 334/781 [00:20<00:28, 15.81it/s]
 43%|####3     | 336/781 [00:21<00:28, 15.76it/s]
 43%|####3     | 338/781 [00:21<00:28, 15.79it/s]
 44%|####3     | 340/781 [00:21<00:27, 15.86it/s]
 44%|####3     | 342/781 [00:21<00:27, 15.84it/s]
 44%|####4     | 344/781 [00:21<00:27, 15.83it/s]
 44%|####4     | 346/781 [00:21<00:27, 15.73it/s]
 45%|####4     | 348/781 [00:21<00:27, 15.78it/s]
 45%|####4     | 350/781 [00:21<00:27, 15.89it/s]
 45%|####5     | 352/781 [00:22<00:26, 16.00it/s]
 45%|####5     | 354/781 [00:22<00:26, 15.94it/s]
 46%|####5     | 356/781 [00:22<00:26, 16.00it/s]
 46%|####5     | 358/781 [00:22<00:26, 15.96it/s]
 46%|####6     | 360/781 [00:22<00:26, 15.85it/s]
 46%|####6     | 362/781 [00:22<00:26, 15.86it/s]
 47%|####6     | 364/781 [00:22<00:26, 15.96it/s]
 47%|####6     | 366/781 [00:22<00:25, 16.01it/s]
 47%|####7     | 368/781 [00:23<00:25, 16.00it/s]
 47%|####7     | 370/781 [00:23<00:25, 15.95it/s]
 48%|####7     | 372/781 [00:23<00:25, 16.05it/s]
 48%|####7     | 374/781 [00:23<00:25, 16.11it/s]
 48%|####8     | 376/781 [00:23<00:25, 16.11it/s]
 48%|####8     | 378/781 [00:23<00:24, 16.15it/s]
 49%|####8     | 380/781 [00:23<00:24, 16.06it/s]
 49%|####8     | 382/781 [00:23<00:24, 16.13it/s]
 49%|####9     | 384/781 [00:24<00:24, 16.20it/s]
 49%|####9     | 386/781 [00:24<00:24, 16.24it/s]
 50%|####9     | 388/781 [00:24<00:24, 16.09it/s]
 50%|####9     | 390/781 [00:24<00:24, 16.13it/s]
 50%|#####     | 392/781 [00:24<00:24, 16.15it/s]
 50%|#####     | 394/781 [00:24<00:23, 16.18it/s]
 51%|#####     | 396/781 [00:24<00:23, 16.18it/s]
 51%|#####     | 398/781 [00:24<00:23, 16.19it/s]
 51%|#####1    | 400/781 [00:25<00:23, 16.19it/s]
 51%|#####1    | 402/781 [00:25<00:23, 16.04it/s]
 52%|#####1    | 404/781 [00:25<00:23, 16.06it/s]
 52%|#####1    | 406/781 [00:25<00:23, 16.12it/s]
 52%|#####2    | 408/781 [00:25<00:23, 15.97it/s]
 52%|#####2    | 410/781 [00:25<00:23, 16.03it/s]
 53%|#####2    | 412/781 [00:25<00:23, 15.96it/s]
 53%|#####3    | 414/781 [00:25<00:22, 16.02it/s]
 53%|#####3    | 416/781 [00:26<00:22, 16.05it/s]
 54%|#####3    | 418/781 [00:26<00:22, 16.09it/s]
 54%|#####3    | 420/781 [00:26<00:22, 16.13it/s]
 54%|#####4    | 422/781 [00:26<00:22, 16.21it/s]
 54%|#####4    | 424/781 [00:26<00:22, 16.17it/s]
 55%|#####4    | 426/781 [00:26<00:22, 15.98it/s]
 55%|#####4    | 428/781 [00:26<00:22, 15.89it/s]
 55%|#####5    | 430/781 [00:26<00:22, 15.85it/s]
 55%|#####5    | 432/781 [00:27<00:22, 15.83it/s]
 56%|#####5    | 434/781 [00:27<00:21, 15.87it/s]
 56%|#####5    | 436/781 [00:27<00:21, 15.88it/s]
 56%|#####6    | 438/781 [00:27<00:21, 15.85it/s]
 56%|#####6    | 440/781 [00:27<00:21, 15.79it/s]
 57%|#####6    | 442/781 [00:27<00:21, 15.96it/s]
 57%|#####6    | 444/781 [00:27<00:21, 16.02it/s]
 57%|#####7    | 446/781 [00:27<00:20, 16.13it/s]
 57%|#####7    | 448/781 [00:28<00:20, 16.03it/s]
 58%|#####7    | 450/781 [00:28<00:20, 16.08it/s]
 58%|#####7    | 452/781 [00:28<00:20, 16.16it/s]
 58%|#####8    | 454/781 [00:28<00:20, 16.14it/s]
 58%|#####8    | 456/781 [00:28<00:20, 16.16it/s]
 59%|#####8    | 458/781 [00:28<00:20, 16.13it/s]
 59%|#####8    | 460/781 [00:28<00:19, 16.18it/s]
 59%|#####9    | 462/781 [00:28<00:19, 16.20it/s]
 59%|#####9    | 464/781 [00:29<00:19, 16.11it/s]
 60%|#####9    | 466/781 [00:29<00:19, 16.14it/s]
 60%|#####9    | 468/781 [00:29<00:19, 15.88it/s]
 60%|######    | 470/781 [00:29<00:19, 15.74it/s]
 60%|######    | 472/781 [00:29<00:19, 15.90it/s]
 61%|######    | 474/781 [00:29<00:19, 15.93it/s]
 61%|######    | 476/781 [00:29<00:19, 15.86it/s]
 61%|######1   | 478/781 [00:29<00:19, 15.86it/s]
 61%|######1   | 480/781 [00:30<00:18, 15.91it/s]
 62%|######1   | 482/781 [00:30<00:18, 15.78it/s]
 62%|######1   | 484/781 [00:30<00:18, 15.93it/s]
 62%|######2   | 486/781 [00:30<00:18, 15.96it/s]
 62%|######2   | 488/781 [00:30<00:18, 15.76it/s]
 63%|######2   | 490/781 [00:30<00:18, 15.56it/s]
 63%|######2   | 492/781 [00:30<00:18, 15.64it/s]
 63%|######3   | 494/781 [00:30<00:18, 15.67it/s]
 64%|######3   | 496/781 [00:31<00:18, 15.79it/s]
 64%|######3   | 498/781 [00:31<00:17, 15.73it/s]
 64%|######4   | 500/781 [00:31<00:17, 15.78it/s]
 64%|######4   | 502/781 [00:31<00:17, 15.76it/s]
 65%|######4   | 504/781 [00:31<00:17, 15.81it/s]
 65%|######4   | 506/781 [00:31<00:17, 15.86it/s]
 65%|######5   | 508/781 [00:31<00:17, 15.97it/s]
 65%|######5   | 510/781 [00:31<00:16, 16.07it/s]
 66%|######5   | 512/781 [00:32<00:16, 16.12it/s]
 66%|######5   | 514/781 [00:32<00:16, 16.10it/s]
 66%|######6   | 516/781 [00:32<00:16, 15.99it/s]
 66%|######6   | 518/781 [00:32<00:16, 15.92it/s]
 67%|######6   | 520/781 [00:32<00:16, 15.91it/s]
 67%|######6   | 522/781 [00:32<00:16, 15.96it/s]
 67%|######7   | 524/781 [00:32<00:16, 16.02it/s]
 67%|######7   | 526/781 [00:32<00:15, 16.00it/s]
 68%|######7   | 528/781 [00:33<00:15, 16.10it/s]
 68%|######7   | 530/781 [00:33<00:15, 15.94it/s]
 68%|######8   | 532/781 [00:33<00:15, 15.98it/s]
 68%|######8   | 534/781 [00:33<00:15, 16.06it/s]
 69%|######8   | 536/781 [00:33<00:15, 16.07it/s]
 69%|######8   | 538/781 [00:33<00:15, 16.11it/s]
 69%|######9   | 540/781 [00:33<00:14, 16.07it/s]
 69%|######9   | 542/781 [00:33<00:14, 15.93it/s]
 70%|######9   | 544/781 [00:34<00:14, 15.98it/s]
 70%|######9   | 546/781 [00:34<00:14, 15.96it/s]
 70%|#######   | 548/781 [00:34<00:14, 15.99it/s]
 70%|#######   | 550/781 [00:34<00:14, 16.06it/s]
 71%|#######   | 552/781 [00:34<00:14, 15.98it/s]
 71%|#######   | 554/781 [00:34<00:14, 15.78it/s]
 71%|#######1  | 556/781 [00:34<00:14, 15.79it/s]
 71%|#######1  | 558/781 [00:34<00:14, 15.85it/s]
 72%|#######1  | 560/781 [00:35<00:13, 15.93it/s]
 72%|#######1  | 562/781 [00:35<00:13, 15.89it/s]
 72%|#######2  | 564/781 [00:35<00:13, 15.88it/s]
 72%|#######2  | 566/781 [00:35<00:13, 15.83it/s]
 73%|#######2  | 568/781 [00:35<00:13, 15.95it/s]
 73%|#######2  | 570/781 [00:35<00:13, 15.94it/s]
 73%|#######3  | 572/781 [00:35<00:13, 15.83it/s]
 73%|#######3  | 574/781 [00:35<00:13, 15.83it/s]
 74%|#######3  | 576/781 [00:36<00:12, 15.83it/s]
 74%|#######4  | 578/781 [00:36<00:12, 15.94it/s]
 74%|#######4  | 580/781 [00:36<00:12, 16.00it/s]
 75%|#######4  | 582/781 [00:36<00:12, 15.84it/s]
 75%|#######4  | 584/781 [00:36<00:12, 15.78it/s]
 75%|#######5  | 586/781 [00:36<00:12, 15.87it/s]
 75%|#######5  | 588/781 [00:36<00:12, 15.76it/s]
 76%|#######5  | 590/781 [00:36<00:12, 15.70it/s]
 76%|#######5  | 592/781 [00:37<00:11, 15.77it/s]
 76%|#######6  | 594/781 [00:37<00:11, 15.90it/s]
 76%|#######6  | 596/781 [00:37<00:11, 16.04it/s]
 77%|#######6  | 598/781 [00:37<00:11, 15.99it/s]
 77%|#######6  | 600/781 [00:37<00:11, 16.03it/s]
 77%|#######7  | 602/781 [00:37<00:11, 15.87it/s]
 77%|#######7  | 604/781 [00:37<00:11, 15.81it/s]
 78%|#######7  | 606/781 [00:38<00:11, 15.76it/s]
 78%|#######7  | 608/781 [00:38<00:11, 15.72it/s]
 78%|#######8  | 610/781 [00:38<00:10, 15.79it/s]
 78%|#######8  | 612/781 [00:38<00:10, 15.79it/s]
 79%|#######8  | 614/781 [00:38<00:10, 15.63it/s]
 79%|#######8  | 616/781 [00:38<00:10, 15.75it/s]
 79%|#######9  | 618/781 [00:38<00:10, 15.89it/s]
 79%|#######9  | 620/781 [00:38<00:10, 15.90it/s]
 80%|#######9  | 622/781 [00:39<00:09, 15.93it/s]
 80%|#######9  | 624/781 [00:39<00:09, 16.02it/s]
 80%|########  | 626/781 [00:39<00:09, 16.06it/s]
 80%|########  | 628/781 [00:39<00:09, 16.04it/s]
 81%|########  | 630/781 [00:39<00:09, 16.11it/s]
 81%|########  | 632/781 [00:39<00:09, 16.17it/s]
 81%|########1 | 634/781 [00:39<00:09, 15.80it/s]
 81%|########1 | 636/781 [00:39<00:09, 15.78it/s]
 82%|########1 | 638/781 [00:40<00:09, 15.72it/s]
 82%|########1 | 640/781 [00:40<00:08, 15.72it/s]
 82%|########2 | 642/781 [00:40<00:08, 15.99it/s]
 82%|########2 | 644/781 [00:40<00:08, 15.95it/s]
 83%|########2 | 646/781 [00:40<00:08, 16.00it/s]
 83%|########2 | 648/781 [00:40<00:08, 15.95it/s]
 83%|########3 | 650/781 [00:40<00:08, 15.94it/s]
 83%|########3 | 652/781 [00:40<00:08, 16.02it/s]
 84%|########3 | 654/781 [00:41<00:07, 15.98it/s]
 84%|########3 | 656/781 [00:41<00:07, 15.87it/s]
 84%|########4 | 658/781 [00:41<00:07, 15.66it/s]
 85%|########4 | 660/781 [00:41<00:07, 15.78it/s]
 85%|########4 | 662/781 [00:41<00:07, 16.01it/s]
 85%|########5 | 664/781 [00:41<00:07, 16.39it/s]
 85%|########5 | 666/781 [00:41<00:07, 16.32it/s]
 86%|########5 | 668/781 [00:41<00:06, 16.23it/s]
 86%|########5 | 670/781 [00:42<00:06, 16.42it/s]
 86%|########6 | 672/781 [00:42<00:06, 16.71it/s]
 86%|########6 | 674/781 [00:42<00:06, 16.53it/s]
 87%|########6 | 676/781 [00:42<00:06, 16.49it/s]
 87%|########6 | 678/781 [00:42<00:06, 16.32it/s]
 87%|########7 | 680/781 [00:42<00:06, 16.50it/s]
 87%|########7 | 682/781 [00:42<00:06, 16.33it/s]
 88%|########7 | 684/781 [00:42<00:05, 16.39it/s]
 88%|########7 | 686/781 [00:42<00:05, 16.54it/s]
 88%|########8 | 688/781 [00:43<00:05, 16.39it/s]
 88%|########8 | 690/781 [00:43<00:05, 16.35it/s]
 89%|########8 | 692/781 [00:43<00:05, 16.44it/s]
 89%|########8 | 694/781 [00:43<00:05, 16.50it/s]
 89%|########9 | 696/781 [00:43<00:05, 16.63it/s]
 89%|########9 | 698/781 [00:43<00:05, 16.35it/s]
 90%|########9 | 700/781 [00:43<00:04, 16.49it/s]
 90%|########9 | 702/781 [00:43<00:04, 16.71it/s]
 90%|######### | 704/781 [00:44<00:04, 16.81it/s]
 90%|######### | 706/781 [00:44<00:04, 16.74it/s]
 91%|######### | 708/781 [00:44<00:04, 16.77it/s]
 91%|######### | 710/781 [00:44<00:04, 16.83it/s]
 91%|#########1| 712/781 [00:44<00:04, 16.80it/s]
 91%|#########1| 714/781 [00:44<00:03, 16.82it/s]
 92%|#########1| 716/781 [00:44<00:03, 16.85it/s]
 92%|#########1| 718/781 [00:44<00:03, 16.95it/s]
 92%|#########2| 720/781 [00:45<00:03, 17.07it/s]
 92%|#########2| 722/781 [00:45<00:03, 17.12it/s]
 93%|#########2| 724/781 [00:45<00:03, 17.18it/s]
 93%|#########2| 726/781 [00:45<00:03, 17.10it/s]
 93%|#########3| 728/781 [00:45<00:03, 17.16it/s]
 93%|#########3| 730/781 [00:45<00:02, 17.18it/s]
 94%|#########3| 732/781 [00:45<00:02, 17.10it/s]
 94%|#########3| 734/781 [00:45<00:02, 16.96it/s]
 94%|#########4| 736/781 [00:45<00:02, 17.04it/s]
 94%|#########4| 738/781 [00:46<00:02, 16.90it/s]
 95%|#########4| 740/781 [00:46<00:02, 17.04it/s]
 95%|#########5| 742/781 [00:46<00:02, 17.12it/s]
 95%|#########5| 744/781 [00:46<00:02, 17.08it/s]
 96%|#########5| 746/781 [00:46<00:02, 17.18it/s]
 96%|#########5| 748/781 [00:46<00:01, 17.18it/s]
 96%|#########6| 750/781 [00:46<00:01, 17.12it/s]
 96%|#########6| 752/781 [00:46<00:01, 16.78it/s]
 97%|#########6| 754/781 [00:46<00:01, 16.82it/s]
 97%|#########6| 756/781 [00:47<00:01, 16.95it/s]
 97%|#########7| 758/781 [00:47<00:01, 17.05it/s]
 97%|#########7| 760/781 [00:47<00:01, 17.09it/s]
 98%|#########7| 762/781 [00:47<00:01, 16.78it/s]
 98%|#########7| 764/781 [00:47<00:01, 16.82it/s]
 98%|#########8| 766/781 [00:47<00:00, 16.87it/s]
 98%|#########8| 768/781 [00:47<00:00, 16.97it/s]
 99%|#########8| 770/781 [00:47<00:00, 16.99it/s]
 99%|#########8| 772/781 [00:48<00:00, 16.51it/s]
 99%|#########9| 774/781 [00:48<00:00, 16.73it/s]
 99%|#########9| 776/781 [00:48<00:00, 16.79it/s]
100%|#########9| 778/781 [00:48<00:00, 16.90it/s]
100%|#########9| 780/781 [00:48<00:00, 16.94it/s]
100%|##########| 781/781 [00:48<00:00, 16.07it/s]




Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   0%|          | 0/44 [00:00<?, ?it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.04it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:41,  1.03it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.02it/s]
Validation Progress:   2%|2         | 1/44 [00:00<00:42,  1.00it/s]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:43,  1.04s/it]
Validation Progress:   5%|4         | 2/44 [00:02<00:44,  1.05s/it]
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  1%|1         | 10/781 [00:00<00:41, 18.45it/s]
  2%|1         | 12/781 [00:00<00:41, 18.58it/s]
  2%|1         | 14/781 [00:00<00:41, 18.60it/s]
  2%|2         | 16/781 [00:00<00:40, 18.67it/s]
  2%|2         | 18/781 [00:00<00:40, 18.78it/s]
  3%|2         | 20/781 [00:01<00:40, 18.81it/s]
  3%|2         | 22/781 [00:01<00:40, 18.83it/s]
  3%|3         | 24/781 [00:01<00:40, 18.88it/s]
  3%|3         | 26/781 [00:01<00:39, 18.95it/s]
  4%|3         | 28/781 [00:01<00:39, 18.96it/s]
  4%|3         | 30/781 [00:01<00:39, 18.95it/s]
  4%|4         | 32/781 [00:01<00:39, 18.99it/s]
  4%|4         | 34/781 [00:01<00:39, 18.83it/s]
  5%|4         | 36/781 [00:01<00:39, 18.65it/s]
  5%|4         | 38/781 [00:02<00:39, 18.75it/s]
  5%|5         | 40/781 [00:02<00:39, 18.80it/s]
  5%|5         | 42/781 [00:02<00:39, 18.88it/s]
  6%|5         | 44/781 [00:02<00:38, 18.94it/s]
  6%|5         | 46/781 [00:02<00:38, 19.08it/s]
  6%|6         | 48/781 [00:02<00:38, 18.80it/s]
  6%|6         | 50/781 [00:02<00:39, 18.66it/s]
  7%|6         | 52/781 [00:02<00:39, 18.49it/s]
  7%|6         | 54/781 [00:02<00:39, 18.42it/s]
  7%|7         | 56/781 [00:02<00:39, 18.46it/s]
  7%|7         | 58/781 [00:03<00:38, 18.65it/s]
  8%|7         | 60/781 [00:03<00:38, 18.60it/s]
  8%|7         | 62/781 [00:03<00:38, 18.61it/s]
  8%|8         | 64/781 [00:03<00:38, 18.66it/s]
  8%|8         | 66/781 [00:03<00:38, 18.75it/s]
  9%|8         | 68/781 [00:03<00:38, 18.76it/s]
  9%|8         | 70/781 [00:03<00:38, 18.67it/s]
  9%|9         | 72/781 [00:03<00:37, 18.67it/s]
  9%|9         | 74/781 [00:03<00:38, 18.57it/s]
 10%|9         | 76/781 [00:04<00:37, 18.70it/s]
 10%|9         | 78/781 [00:04<00:37, 18.68it/s]
 10%|#         | 80/781 [00:04<00:37, 18.75it/s]
 10%|#         | 82/781 [00:04<00:37, 18.70it/s]
 11%|#         | 84/781 [00:04<00:36, 19.02it/s]
 11%|#1        | 86/781 [00:04<00:37, 18.77it/s]
 11%|#1        | 88/781 [00:04<00:36, 19.12it/s]
 12%|#1        | 90/781 [00:04<00:35, 19.29it/s]
 12%|#1        | 92/781 [00:04<00:35, 19.31it/s]
 12%|#2        | 94/781 [00:05<00:35, 19.42it/s]
 12%|#2        | 96/781 [00:05<00:35, 19.17it/s]
 13%|#2        | 98/781 [00:05<00:36, 18.93it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.05it/s]
 13%|#3        | 103/781 [00:05<00:34, 19.45it/s]
 13%|#3        | 105/781 [00:05<00:34, 19.56it/s]
 14%|#3        | 107/781 [00:05<00:34, 19.53it/s]
 14%|#3        | 109/781 [00:05<00:34, 19.23it/s]
 14%|#4        | 111/781 [00:05<00:34, 19.24it/s]
 14%|#4        | 113/781 [00:05<00:34, 19.14it/s]
 15%|#4        | 115/781 [00:06<00:35, 18.97it/s]
 15%|#4        | 117/781 [00:06<00:34, 19.01it/s]
 15%|#5        | 119/781 [00:06<00:35, 18.86it/s]
 15%|#5        | 121/781 [00:06<00:35, 18.74it/s]
 16%|#5        | 123/781 [00:06<00:35, 18.67it/s]
 16%|#6        | 125/781 [00:06<00:35, 18.51it/s]
 16%|#6        | 127/781 [00:06<00:35, 18.39it/s]
 17%|#6        | 129/781 [00:06<00:35, 18.53it/s]
 17%|#6        | 131/781 [00:06<00:35, 18.38it/s]
 17%|#7        | 133/781 [00:07<00:34, 18.69it/s]
 17%|#7        | 135/781 [00:07<00:34, 18.70it/s]
 18%|#7        | 137/781 [00:07<00:34, 18.91it/s]
 18%|#7        | 139/781 [00:07<00:34, 18.70it/s]
 18%|#8        | 141/781 [00:07<00:34, 18.66it/s]
 18%|#8        | 143/781 [00:07<00:34, 18.67it/s]
 19%|#8        | 145/781 [00:07<00:33, 18.96it/s]
 19%|#8        | 147/781 [00:07<00:33, 18.86it/s]
 19%|#9        | 149/781 [00:07<00:33, 18.65it/s]
 19%|#9        | 151/781 [00:08<00:33, 18.70it/s]
 20%|#9        | 153/781 [00:08<00:34, 18.18it/s]
 20%|#9        | 155/781 [00:08<00:34, 18.36it/s]
 20%|##        | 157/781 [00:08<00:33, 18.73it/s]
 20%|##        | 159/781 [00:08<00:32, 18.90it/s]
 21%|##        | 161/781 [00:08<00:32, 19.15it/s]
 21%|##        | 163/781 [00:08<00:31, 19.32it/s]
 21%|##1       | 165/781 [00:08<00:31, 19.29it/s]
 21%|##1       | 167/781 [00:08<00:31, 19.31it/s]
 22%|##1       | 169/781 [00:08<00:31, 19.45it/s]
 22%|##1       | 171/781 [00:09<00:31, 19.47it/s]
 22%|##2       | 173/781 [00:09<00:31, 19.30it/s]
 22%|##2       | 175/781 [00:09<00:31, 19.36it/s]
 23%|##2       | 177/781 [00:09<00:31, 19.11it/s]
 23%|##2       | 179/781 [00:09<00:31, 19.16it/s]
 23%|##3       | 181/781 [00:09<00:31, 19.17it/s]
 23%|##3       | 183/781 [00:09<00:31, 19.20it/s]
 24%|##3       | 185/781 [00:09<00:30, 19.38it/s]
 24%|##4       | 188/781 [00:09<00:30, 19.63it/s]
 24%|##4       | 190/781 [00:10<00:30, 19.51it/s]
 25%|##4       | 192/781 [00:10<00:30, 19.56it/s]
 25%|##4       | 194/781 [00:10<00:29, 19.61it/s]
 25%|##5       | 196/781 [00:10<00:29, 19.61it/s]
 25%|##5       | 198/781 [00:10<00:29, 19.63it/s]
 26%|##5       | 200/781 [00:10<00:29, 19.47it/s]
 26%|##5       | 202/781 [00:10<00:29, 19.55it/s]
 26%|##6       | 205/781 [00:10<00:29, 19.77it/s]
 27%|##6       | 208/781 [00:10<00:28, 19.82it/s]
 27%|##7       | 211/781 [00:11<00:28, 19.93it/s]
 27%|##7       | 213/781 [00:11<00:28, 19.90it/s]
 28%|##7       | 215/781 [00:11<00:28, 19.79it/s]
 28%|##7       | 218/781 [00:11<00:29, 19.32it/s]
 28%|##8       | 220/781 [00:11<00:28, 19.35it/s]
 28%|##8       | 222/781 [00:11<00:29, 19.12it/s]
 29%|##8       | 224/781 [00:11<00:29, 19.12it/s]
 29%|##9       | 227/781 [00:11<00:28, 19.46it/s]
 29%|##9       | 229/781 [00:12<00:28, 19.48it/s]
 30%|##9       | 232/781 [00:12<00:27, 19.66it/s]
 30%|###       | 235/781 [00:12<00:27, 19.77it/s]
 30%|###       | 237/781 [00:12<00:27, 19.51it/s]
 31%|###       | 239/781 [00:12<00:27, 19.47it/s]
 31%|###       | 241/781 [00:12<00:27, 19.45it/s]
 31%|###1      | 243/781 [00:12<00:27, 19.55it/s]
 31%|###1      | 245/781 [00:12<00:27, 19.61it/s]
 32%|###1      | 247/781 [00:12<00:27, 19.66it/s]
 32%|###2      | 250/781 [00:13<00:26, 19.87it/s]
 32%|###2      | 252/781 [00:13<00:26, 19.74it/s]
 33%|###2      | 254/781 [00:13<00:26, 19.60it/s]
 33%|###2      | 256/781 [00:13<00:26, 19.70it/s]
 33%|###3      | 259/781 [00:13<00:26, 19.82it/s]
 34%|###3      | 262/781 [00:13<00:26, 19.91it/s]
 34%|###3      | 264/781 [00:13<00:26, 19.86it/s]
 34%|###4      | 266/781 [00:13<00:26, 19.48it/s]
 34%|###4      | 269/781 [00:14<00:26, 19.65it/s]
 35%|###4      | 271/781 [00:14<00:25, 19.64it/s]
 35%|###4      | 273/781 [00:14<00:25, 19.58it/s]
 35%|###5      | 275/781 [00:14<00:25, 19.62it/s]
 36%|###5      | 278/781 [00:14<00:25, 19.77it/s]
 36%|###5      | 280/781 [00:14<00:25, 19.81it/s]
 36%|###6      | 282/781 [00:14<00:25, 19.55it/s]
 36%|###6      | 284/781 [00:14<00:25, 19.40it/s]
 37%|###6      | 286/781 [00:14<00:25, 19.54it/s]
 37%|###6      | 288/781 [00:15<00:25, 19.53it/s]
 37%|###7      | 290/781 [00:15<00:25, 19.62it/s]
 37%|###7      | 292/781 [00:15<00:24, 19.65it/s]
 38%|###7      | 294/781 [00:15<00:25, 19.20it/s]
 38%|###7      | 296/781 [00:15<00:24, 19.41it/s]
 38%|###8      | 298/781 [00:15<00:24, 19.48it/s]
 38%|###8      | 300/781 [00:15<00:24, 19.39it/s]
 39%|###8      | 302/781 [00:15<00:25, 19.15it/s]
 39%|###8      | 304/781 [00:15<00:24, 19.27it/s]
 39%|###9      | 306/781 [00:15<00:24, 19.41it/s]
 39%|###9      | 308/781 [00:16<00:24, 19.44it/s]
 40%|###9      | 310/781 [00:16<00:24, 19.50it/s]
 40%|###9      | 312/781 [00:16<00:23, 19.57it/s]
 40%|####      | 314/781 [00:16<00:24, 19.32it/s]
 40%|####      | 316/781 [00:16<00:24, 19.27it/s]
 41%|####      | 318/781 [00:16<00:24, 19.14it/s]
 41%|####      | 320/781 [00:16<00:23, 19.29it/s]
 41%|####1     | 322/781 [00:16<00:23, 19.50it/s]
 41%|####1     | 324/781 [00:16<00:23, 19.44it/s]
 42%|####1     | 326/781 [00:17<00:23, 19.56it/s]
 42%|####1     | 328/781 [00:17<00:23, 19.60it/s]
 42%|####2     | 330/781 [00:17<00:22, 19.71it/s]
 43%|####2     | 332/781 [00:17<00:23, 19.34it/s]
 43%|####2     | 334/781 [00:17<00:23, 19.41it/s]
 43%|####3     | 336/781 [00:17<00:22, 19.52it/s]
 43%|####3     | 338/781 [00:17<00:22, 19.61it/s]
 44%|####3     | 341/781 [00:17<00:22, 19.81it/s]
 44%|####3     | 343/781 [00:17<00:22, 19.84it/s]
 44%|####4     | 345/781 [00:17<00:22, 19.74it/s]
 44%|####4     | 347/781 [00:18<00:22, 19.66it/s]
 45%|####4     | 349/781 [00:18<00:22, 19.63it/s]
 45%|####4     | 351/781 [00:18<00:21, 19.57it/s]
 45%|####5     | 353/781 [00:18<00:21, 19.53it/s]
 45%|####5     | 355/781 [00:18<00:21, 19.67it/s]
 46%|####5     | 357/781 [00:18<00:21, 19.65it/s]
 46%|####5     | 359/781 [00:18<00:21, 19.65it/s]
 46%|####6     | 361/781 [00:18<00:21, 19.47it/s]
 46%|####6     | 363/781 [00:18<00:21, 19.44it/s]
 47%|####6     | 365/781 [00:19<00:21, 19.26it/s]
 47%|####6     | 367/781 [00:19<00:21, 19.05it/s]
 47%|####7     | 369/781 [00:19<00:21, 18.93it/s]
 48%|####7     | 371/781 [00:19<00:21, 19.20it/s]
 48%|####7     | 373/781 [00:19<00:21, 18.97it/s]
 48%|####8     | 375/781 [00:19<00:21, 18.90it/s]
 48%|####8     | 377/781 [00:19<00:21, 18.98it/s]
 49%|####8     | 379/781 [00:19<00:20, 19.24it/s]
 49%|####8     | 381/781 [00:19<00:20, 19.41it/s]
 49%|####9     | 383/781 [00:19<00:20, 19.28it/s]
 49%|####9     | 385/781 [00:20<00:20, 19.03it/s]
 50%|####9     | 387/781 [00:20<00:20, 19.04it/s]
 50%|####9     | 389/781 [00:20<00:20, 18.98it/s]
 50%|#####     | 391/781 [00:20<00:20, 19.09it/s]
 50%|#####     | 393/781 [00:20<00:20, 19.32it/s]
 51%|#####     | 395/781 [00:20<00:19, 19.44it/s]
 51%|#####     | 397/781 [00:20<00:19, 19.37it/s]
 51%|#####1    | 399/781 [00:20<00:19, 19.51it/s]
 51%|#####1    | 401/781 [00:20<00:19, 19.57it/s]
 52%|#####1    | 403/781 [00:20<00:19, 19.49it/s]
 52%|#####1    | 405/781 [00:21<00:19, 19.60it/s]
 52%|#####2    | 407/781 [00:21<00:19, 19.52it/s]
 52%|#####2    | 409/781 [00:21<00:19, 19.53it/s]
 53%|#####2    | 411/781 [00:21<00:18, 19.65it/s]
 53%|#####2    | 413/781 [00:21<00:18, 19.57it/s]
 53%|#####3    | 415/781 [00:21<00:18, 19.37it/s]
 53%|#####3    | 417/781 [00:21<00:18, 19.32it/s]
 54%|#####3    | 419/781 [00:21<00:18, 19.26it/s]
 54%|#####3    | 421/781 [00:21<00:18, 19.33it/s]
 54%|#####4    | 423/781 [00:22<00:18, 19.45it/s]
 54%|#####4    | 425/781 [00:22<00:18, 19.58it/s]
 55%|#####4    | 427/781 [00:22<00:18, 19.60it/s]
 55%|#####4    | 429/781 [00:22<00:17, 19.67it/s]
 55%|#####5    | 432/781 [00:22<00:17, 19.83it/s]
 56%|#####5    | 434/781 [00:22<00:17, 19.84it/s]
 56%|#####5    | 436/781 [00:22<00:17, 19.84it/s]
 56%|#####6    | 438/781 [00:22<00:17, 19.74it/s]
 56%|#####6    | 440/781 [00:22<00:17, 19.61it/s]
 57%|#####6    | 442/781 [00:22<00:17, 19.56it/s]
 57%|#####6    | 444/781 [00:23<00:17, 19.38it/s]
 57%|#####7    | 446/781 [00:23<00:17, 19.20it/s]
 57%|#####7    | 448/781 [00:23<00:17, 19.32it/s]
 58%|#####7    | 450/781 [00:23<00:16, 19.49it/s]
 58%|#####7    | 452/781 [00:23<00:16, 19.59it/s]
 58%|#####8    | 454/781 [00:23<00:16, 19.40it/s]
 59%|#####8    | 457/781 [00:23<00:16, 19.65it/s]
 59%|#####8    | 459/781 [00:23<00:16, 19.69it/s]
 59%|#####9    | 461/781 [00:23<00:16, 19.76it/s]
 59%|#####9    | 463/781 [00:24<00:16, 19.67it/s]
 60%|#####9    | 465/781 [00:24<00:16, 19.66it/s]
 60%|#####9    | 467/781 [00:24<00:16, 19.46it/s]
 60%|######    | 469/781 [00:24<00:15, 19.53it/s]
 60%|######    | 471/781 [00:24<00:15, 19.57it/s]
 61%|######    | 473/781 [00:24<00:15, 19.31it/s]
 61%|######    | 475/781 [00:24<00:15, 19.45it/s]
 61%|######1   | 477/781 [00:24<00:15, 19.42it/s]
 61%|######1   | 479/781 [00:24<00:15, 19.55it/s]
 62%|######1   | 481/781 [00:24<00:15, 19.47it/s]
 62%|######1   | 483/781 [00:25<00:15, 19.51it/s]
 62%|######2   | 485/781 [00:25<00:15, 19.59it/s]
 62%|######2   | 487/781 [00:25<00:14, 19.66it/s]
 63%|######2   | 489/781 [00:25<00:14, 19.73it/s]
 63%|######2   | 492/781 [00:25<00:14, 19.67it/s]
 63%|######3   | 494/781 [00:25<00:14, 19.40it/s]
 64%|######3   | 496/781 [00:25<00:14, 19.38it/s]
 64%|######3   | 498/781 [00:25<00:14, 19.42it/s]
 64%|######4   | 500/781 [00:25<00:14, 19.51it/s]
 64%|######4   | 502/781 [00:26<00:14, 19.39it/s]
 65%|######4   | 504/781 [00:26<00:14, 19.54it/s]
 65%|######4   | 507/781 [00:26<00:13, 19.64it/s]
 65%|######5   | 509/781 [00:26<00:13, 19.51it/s]
 65%|######5   | 511/781 [00:26<00:13, 19.50it/s]
 66%|######5   | 514/781 [00:26<00:13, 19.49it/s]
 66%|######6   | 516/781 [00:26<00:13, 19.47it/s]
 66%|######6   | 518/781 [00:26<00:13, 19.54it/s]
 67%|######6   | 520/781 [00:26<00:13, 19.58it/s]
 67%|######6   | 522/781 [00:27<00:13, 19.63it/s]
 67%|######7   | 524/781 [00:27<00:13, 19.70it/s]
 67%|######7   | 526/781 [00:27<00:12, 19.70it/s]
 68%|######7   | 528/781 [00:27<00:12, 19.72it/s]
 68%|######7   | 531/781 [00:27<00:12, 19.87it/s]
 68%|######8   | 533/781 [00:27<00:12, 19.90it/s]
 69%|######8   | 535/781 [00:27<00:12, 19.81it/s]
 69%|######8   | 538/781 [00:27<00:12, 19.91it/s]
 69%|######9   | 540/781 [00:27<00:12, 19.43it/s]
 69%|######9   | 542/781 [00:28<00:12, 19.46it/s]
 70%|######9   | 544/781 [00:28<00:12, 19.47it/s]
 70%|######9   | 546/781 [00:28<00:12, 18.97it/s]
 70%|#######   | 548/781 [00:28<00:12, 18.75it/s]
 70%|#######   | 550/781 [00:28<00:12, 18.59it/s]
 71%|#######   | 552/781 [00:28<00:12, 18.50it/s]
 71%|#######   | 554/781 [00:28<00:12, 18.61it/s]
 71%|#######1  | 556/781 [00:28<00:12, 18.68it/s]
 71%|#######1  | 558/781 [00:28<00:12, 18.56it/s]
 72%|#######1  | 560/781 [00:29<00:11, 18.66it/s]
 72%|#######1  | 562/781 [00:29<00:11, 18.51it/s]
 72%|#######2  | 564/781 [00:29<00:11, 18.62it/s]
 72%|#######2  | 566/781 [00:29<00:11, 18.49it/s]
 73%|#######2  | 568/781 [00:29<00:11, 18.40it/s]
 73%|#######2  | 570/781 [00:29<00:11, 18.27it/s]
 73%|#######3  | 572/781 [00:29<00:11, 18.25it/s]
 73%|#######3  | 574/781 [00:29<00:11, 18.14it/s]
 74%|#######3  | 576/781 [00:29<00:11, 18.11it/s]
 74%|#######4  | 578/781 [00:30<00:11, 17.99it/s]
 74%|#######4  | 580/781 [00:30<00:10, 18.35it/s]
 75%|#######4  | 582/781 [00:30<00:10, 18.26it/s]
 75%|#######4  | 584/781 [00:30<00:10, 18.37it/s]
 75%|#######5  | 586/781 [00:30<00:10, 18.34it/s]
 75%|#######5  | 588/781 [00:30<00:10, 18.37it/s]
 76%|#######5  | 590/781 [00:30<00:10, 18.14it/s]
 76%|#######5  | 592/781 [00:30<00:10, 18.23it/s]
 76%|#######6  | 594/781 [00:30<00:10, 18.42it/s]
 76%|#######6  | 596/781 [00:31<00:10, 18.39it/s]
 77%|#######6  | 598/781 [00:31<00:09, 18.56it/s]
 77%|#######6  | 600/781 [00:31<00:09, 18.48it/s]
 77%|#######7  | 602/781 [00:31<00:09, 18.53it/s]
 77%|#######7  | 604/781 [00:31<00:09, 18.42it/s]
 78%|#######7  | 606/781 [00:31<00:09, 18.66it/s]
 78%|#######7  | 608/781 [00:31<00:09, 18.49it/s]
 78%|#######8  | 610/781 [00:31<00:09, 18.39it/s]
 78%|#######8  | 612/781 [00:31<00:09, 18.35it/s]
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Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.20s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]

  0%|          | 0/1 [00:00<?, ?it/s]
100%|##########| 1/1 [00:18<00:00, 18.93s/it]
100%|##########| 1/1 [00:18<00:00, 18.93s/it]

  0%|          | 0/157 [00:00<?, ?it/s]
  1%|1         | 2/157 [00:00<00:10, 14.59it/s]
  3%|2         | 4/157 [00:00<00:09, 15.31it/s]
  4%|3         | 6/157 [00:00<00:09, 15.96it/s]
  5%|5         | 8/157 [00:00<00:09, 16.26it/s]
  6%|6         | 10/157 [00:00<00:08, 16.52it/s]
  8%|7         | 12/157 [00:00<00:08, 16.50it/s]
  9%|8         | 14/157 [00:00<00:08, 16.60it/s]
 10%|#         | 16/157 [00:00<00:08, 16.70it/s]
 11%|#1        | 18/157 [00:01<00:08, 16.76it/s]
 13%|#2        | 20/157 [00:01<00:08, 16.78it/s]
 14%|#4        | 22/157 [00:01<00:08, 16.76it/s]
 15%|#5        | 24/157 [00:01<00:07, 16.79it/s]
 17%|#6        | 26/157 [00:01<00:07, 16.73it/s]
 18%|#7        | 28/157 [00:01<00:07, 16.68it/s]
 19%|#9        | 30/157 [00:01<00:07, 16.76it/s]
 20%|##        | 32/157 [00:01<00:07, 16.82it/s]
 22%|##1       | 34/157 [00:02<00:07, 16.91it/s]
 23%|##2       | 36/157 [00:02<00:07, 16.83it/s]
 24%|##4       | 38/157 [00:02<00:07, 16.78it/s]
 25%|##5       | 40/157 [00:02<00:07, 16.67it/s]
 27%|##6       | 42/157 [00:02<00:06, 16.59it/s]
 28%|##8       | 44/157 [00:02<00:06, 16.52it/s]
 29%|##9       | 46/157 [00:02<00:06, 16.66it/s]
 31%|###       | 48/157 [00:02<00:06, 16.80it/s]
 32%|###1      | 50/157 [00:03<00:06, 16.84it/s]
 33%|###3      | 52/157 [00:03<00:06, 16.64it/s]
 34%|###4      | 54/157 [00:03<00:06, 16.72it/s]
 36%|###5      | 56/157 [00:03<00:06, 16.72it/s]
 37%|###6      | 58/157 [00:03<00:05, 16.60it/s]
 38%|###8      | 60/157 [00:03<00:05, 16.66it/s]
 39%|###9      | 62/157 [00:03<00:05, 16.74it/s]
 41%|####      | 64/157 [00:03<00:05, 16.61it/s]
 42%|####2     | 66/157 [00:03<00:05, 16.39it/s]
 43%|####3     | 68/157 [00:04<00:05, 16.39it/s]
 45%|####4     | 70/157 [00:04<00:05, 16.58it/s]
 46%|####5     | 72/157 [00:04<00:05, 16.58it/s]
 47%|####7     | 74/157 [00:04<00:04, 16.70it/s]
 48%|####8     | 76/157 [00:04<00:04, 16.63it/s]
 50%|####9     | 78/157 [00:04<00:04, 16.68it/s]
 51%|#####     | 80/157 [00:04<00:04, 16.78it/s]
 52%|#####2    | 82/157 [00:04<00:04, 16.86it/s]
 54%|#####3    | 84/157 [00:05<00:04, 16.87it/s]
 55%|#####4    | 86/157 [00:05<00:04, 16.71it/s]
 56%|#####6    | 88/157 [00:05<00:04, 16.78it/s]
 57%|#####7    | 90/157 [00:05<00:03, 16.85it/s]
 59%|#####8    | 92/157 [00:05<00:03, 16.97it/s]
 60%|#####9    | 94/157 [00:05<00:03, 17.02it/s]
 61%|######1   | 96/157 [00:05<00:03, 17.01it/s]
 62%|######2   | 98/157 [00:05<00:03, 17.05it/s]
 64%|######3   | 100/157 [00:05<00:03, 17.06it/s]
 65%|######4   | 102/157 [00:06<00:03, 17.10it/s]
 66%|######6   | 104/157 [00:06<00:03, 17.09it/s]
 68%|######7   | 106/157 [00:06<00:02, 17.03it/s]
 69%|######8   | 108/157 [00:06<00:02, 17.03it/s]
 70%|#######   | 110/157 [00:06<00:02, 17.02it/s]
 71%|#######1  | 112/157 [00:06<00:02, 16.90it/s]
 73%|#######2  | 114/157 [00:06<00:02, 16.94it/s]
 74%|#######3  | 116/157 [00:06<00:02, 16.95it/s]
 75%|#######5  | 118/157 [00:07<00:02, 16.89it/s]
 76%|#######6  | 120/157 [00:07<00:02, 16.86it/s]
 78%|#######7  | 122/157 [00:07<00:02, 16.55it/s]
 79%|#######8  | 124/157 [00:07<00:01, 16.65it/s]
 80%|########  | 126/157 [00:07<00:01, 16.77it/s]
 82%|########1 | 128/157 [00:07<00:01, 16.83it/s]
 83%|########2 | 130/157 [00:07<00:01, 16.79it/s]
 84%|########4 | 132/157 [00:07<00:01, 16.68it/s]
 85%|########5 | 134/157 [00:08<00:01, 16.79it/s]
 87%|########6 | 136/157 [00:08<00:01, 16.91it/s]
 88%|########7 | 138/157 [00:08<00:01, 16.97it/s]
 89%|########9 | 140/157 [00:08<00:01, 16.87it/s]
 90%|######### | 142/157 [00:08<00:00, 16.56it/s]
 92%|#########1| 144/157 [00:08<00:00, 16.74it/s]
 93%|#########2| 146/157 [00:08<00:00, 16.76it/s]
 94%|#########4| 148/157 [00:08<00:00, 16.78it/s]
 96%|#########5| 150/157 [00:08<00:00, 16.83it/s]
 97%|#########6| 152/157 [00:09<00:00, 16.69it/s]
 98%|#########8| 154/157 [00:09<00:00, 16.74it/s]
 99%|#########9| 156/157 [00:09<00:00, 16.77it/s]
100%|##########| 157/157 [00:09<00:00, 16.80it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:49, 15.89it/s]
  1%|          | 4/781 [00:00<00:44, 17.36it/s]
  1%|          | 6/781 [00:00<00:42, 18.20it/s]
  1%|1         | 8/781 [00:00<00:41, 18.44it/s]
  1%|1         | 10/781 [00:00<00:41, 18.44it/s]
  2%|1         | 12/781 [00:00<00:41, 18.52it/s]
  2%|1         | 14/781 [00:00<00:41, 18.65it/s]
  2%|2         | 16/781 [00:00<00:40, 18.71it/s]
  2%|2         | 18/781 [00:00<00:40, 18.91it/s]
  3%|2         | 20/781 [00:01<00:39, 19.04it/s]
  3%|2         | 22/781 [00:01<00:39, 19.13it/s]
  3%|3         | 24/781 [00:01<00:39, 19.10it/s]
  3%|3         | 26/781 [00:01<00:39, 18.92it/s]
  4%|3         | 28/781 [00:01<00:39, 19.06it/s]
  4%|3         | 30/781 [00:01<00:39, 19.13it/s]
  4%|4         | 32/781 [00:01<00:39, 19.18it/s]
  4%|4         | 34/781 [00:01<00:39, 19.12it/s]
  5%|4         | 36/781 [00:01<00:38, 19.16it/s]
  5%|4         | 38/781 [00:02<00:38, 19.10it/s]
  5%|5         | 40/781 [00:02<00:38, 19.14it/s]
  5%|5         | 42/781 [00:02<00:38, 19.19it/s]
  6%|5         | 44/781 [00:02<00:38, 19.02it/s]
  6%|5         | 46/781 [00:02<00:38, 18.87it/s]
  6%|6         | 48/781 [00:02<00:38, 18.83it/s]
  6%|6         | 50/781 [00:02<00:38, 18.91it/s]
  7%|6         | 52/781 [00:02<00:38, 18.96it/s]
  7%|6         | 54/781 [00:02<00:38, 19.03it/s]
  7%|7         | 56/781 [00:02<00:37, 19.13it/s]
  7%|7         | 58/781 [00:03<00:37, 19.17it/s]
  8%|7         | 60/781 [00:03<00:38, 18.74it/s]
  8%|7         | 62/781 [00:03<00:38, 18.72it/s]
  8%|8         | 64/781 [00:03<00:38, 18.82it/s]
  8%|8         | 66/781 [00:03<00:37, 18.97it/s]
  9%|8         | 68/781 [00:03<00:37, 19.10it/s]
  9%|8         | 70/781 [00:03<00:37, 19.06it/s]
  9%|9         | 72/781 [00:03<00:37, 18.94it/s]
  9%|9         | 74/781 [00:03<00:37, 18.87it/s]
 10%|9         | 76/781 [00:04<00:37, 18.76it/s]
 10%|9         | 78/781 [00:04<00:37, 18.85it/s]
 10%|#         | 80/781 [00:04<00:37, 18.74it/s]
 10%|#         | 82/781 [00:04<00:37, 18.89it/s]
 11%|#         | 84/781 [00:04<00:37, 18.74it/s]
 11%|#1        | 86/781 [00:04<00:36, 18.91it/s]
 11%|#1        | 88/781 [00:04<00:36, 18.96it/s]
 12%|#1        | 90/781 [00:04<00:36, 18.94it/s]
 12%|#1        | 92/781 [00:04<00:36, 19.00it/s]
 12%|#2        | 94/781 [00:04<00:36, 18.95it/s]
 12%|#2        | 96/781 [00:05<00:36, 18.90it/s]
 13%|#2        | 98/781 [00:05<00:36, 18.88it/s]
 13%|#2        | 100/781 [00:05<00:35, 19.07it/s]
 13%|#3        | 102/781 [00:05<00:35, 19.03it/s]
 13%|#3        | 104/781 [00:05<00:35, 18.90it/s]
 14%|#3        | 106/781 [00:05<00:35, 18.85it/s]
 14%|#3        | 108/781 [00:05<00:35, 18.85it/s]
 14%|#4        | 110/781 [00:05<00:35, 18.81it/s]
 14%|#4        | 112/781 [00:05<00:35, 18.89it/s]
 15%|#4        | 114/781 [00:06<00:36, 18.52it/s]
 15%|#4        | 116/781 [00:06<00:35, 18.73it/s]
 15%|#5        | 118/781 [00:06<00:35, 18.86it/s]
 15%|#5        | 120/781 [00:06<00:34, 19.00it/s]
 16%|#5        | 122/781 [00:06<00:34, 18.98it/s]
 16%|#5        | 124/781 [00:06<00:34, 18.97it/s]
 16%|#6        | 126/781 [00:06<00:34, 19.04it/s]
 16%|#6        | 128/781 [00:06<00:34, 19.00it/s]
 17%|#6        | 130/781 [00:06<00:34, 19.02it/s]
 17%|#6        | 132/781 [00:06<00:34, 19.06it/s]
 17%|#7        | 134/781 [00:07<00:33, 19.08it/s]
 17%|#7        | 136/781 [00:07<00:34, 18.89it/s]
 18%|#7        | 138/781 [00:07<00:33, 19.09it/s]
 18%|#7        | 140/781 [00:07<00:33, 19.20it/s]
 18%|#8        | 142/781 [00:07<00:33, 19.20it/s]
 18%|#8        | 144/781 [00:07<00:33, 19.07it/s]
 19%|#8        | 146/781 [00:07<00:33, 19.14it/s]
 19%|#8        | 148/781 [00:07<00:32, 19.25it/s]
 19%|#9        | 150/781 [00:07<00:32, 19.34it/s]
 19%|#9        | 152/781 [00:08<00:32, 19.41it/s]
 20%|#9        | 154/781 [00:08<00:32, 19.41it/s]
 20%|#9        | 156/781 [00:08<00:32, 19.51it/s]
 20%|##        | 158/781 [00:08<00:31, 19.50it/s]
 20%|##        | 160/781 [00:08<00:31, 19.57it/s]
 21%|##        | 162/781 [00:08<00:31, 19.61it/s]
 21%|##        | 164/781 [00:08<00:31, 19.35it/s]
 21%|##1       | 166/781 [00:08<00:31, 19.50it/s]
 22%|##1       | 168/781 [00:08<00:31, 19.17it/s]
 22%|##1       | 170/781 [00:08<00:31, 19.24it/s]
 22%|##2       | 172/781 [00:09<00:31, 19.42it/s]
 22%|##2       | 174/781 [00:09<00:31, 19.33it/s]
 23%|##2       | 176/781 [00:09<00:31, 19.22it/s]
 23%|##2       | 178/781 [00:09<00:31, 19.27it/s]
 23%|##3       | 180/781 [00:09<00:30, 19.46it/s]
 23%|##3       | 182/781 [00:09<00:30, 19.59it/s]
 24%|##3       | 184/781 [00:09<00:30, 19.66it/s]
 24%|##3       | 186/781 [00:09<00:30, 19.46it/s]
 24%|##4       | 188/781 [00:09<00:30, 19.42it/s]
 24%|##4       | 190/781 [00:09<00:30, 19.48it/s]
 25%|##4       | 192/781 [00:10<00:30, 19.51it/s]
 25%|##4       | 194/781 [00:10<00:31, 18.89it/s]
 25%|##5       | 196/781 [00:10<00:30, 18.93it/s]
 25%|##5       | 198/781 [00:10<00:30, 19.05it/s]
 26%|##5       | 200/781 [00:10<00:30, 19.14it/s]
 26%|##5       | 202/781 [00:10<00:30, 19.20it/s]
 26%|##6       | 204/781 [00:10<00:30, 19.17it/s]
 26%|##6       | 206/781 [00:10<00:29, 19.30it/s]
 27%|##6       | 208/781 [00:10<00:29, 19.40it/s]
 27%|##6       | 210/781 [00:11<00:29, 19.30it/s]
 27%|##7       | 212/781 [00:11<00:29, 19.45it/s]
 27%|##7       | 214/781 [00:11<00:28, 19.56it/s]
 28%|##7       | 216/781 [00:11<00:28, 19.57it/s]
 28%|##7       | 218/781 [00:11<00:28, 19.63it/s]
 28%|##8       | 220/781 [00:11<00:28, 19.73it/s]
 28%|##8       | 222/781 [00:11<00:28, 19.81it/s]
 29%|##8       | 225/781 [00:11<00:27, 19.89it/s]
 29%|##9       | 227/781 [00:11<00:28, 19.61it/s]
 29%|##9       | 230/781 [00:12<00:27, 19.82it/s]
 30%|##9       | 232/781 [00:12<00:27, 19.70it/s]
 30%|##9       | 234/781 [00:12<00:27, 19.77it/s]
 30%|###       | 236/781 [00:12<00:27, 19.82it/s]
 30%|###       | 238/781 [00:12<00:27, 19.64it/s]
 31%|###       | 240/781 [00:12<00:27, 19.58it/s]
 31%|###       | 242/781 [00:12<00:27, 19.47it/s]
 31%|###1      | 244/781 [00:12<00:27, 19.30it/s]
 31%|###1      | 246/781 [00:12<00:27, 19.37it/s]
 32%|###1      | 248/781 [00:12<00:27, 19.35it/s]
 32%|###2      | 250/781 [00:13<00:27, 19.12it/s]
 32%|###2      | 252/781 [00:13<00:27, 18.91it/s]
 33%|###2      | 254/781 [00:13<00:27, 19.19it/s]
 33%|###2      | 256/781 [00:13<00:27, 19.36it/s]
 33%|###3      | 258/781 [00:13<00:27, 19.01it/s]
 33%|###3      | 260/781 [00:13<00:27, 19.17it/s]
 34%|###3      | 262/781 [00:13<00:26, 19.38it/s]
 34%|###3      | 264/781 [00:13<00:26, 19.45it/s]
 34%|###4      | 266/781 [00:13<00:26, 19.18it/s]
 34%|###4      | 268/781 [00:14<00:26, 19.36it/s]
 35%|###4      | 270/781 [00:14<00:26, 19.07it/s]
 35%|###4      | 272/781 [00:14<00:27, 18.76it/s]
 35%|###5      | 274/781 [00:14<00:26, 18.93it/s]
 35%|###5      | 276/781 [00:14<00:26, 18.92it/s]
 36%|###5      | 278/781 [00:14<00:26, 18.84it/s]
 36%|###5      | 280/781 [00:14<00:26, 18.82it/s]
 36%|###6      | 282/781 [00:14<00:26, 18.85it/s]
 36%|###6      | 284/781 [00:14<00:26, 18.69it/s]
 37%|###6      | 286/781 [00:14<00:26, 18.80it/s]
 37%|###6      | 288/781 [00:15<00:26, 18.79it/s]
 37%|###7      | 290/781 [00:15<00:26, 18.83it/s]
 37%|###7      | 292/781 [00:15<00:25, 18.96it/s]
 38%|###7      | 294/781 [00:15<00:25, 19.09it/s]
 38%|###7      | 296/781 [00:15<00:25, 19.14it/s]
 38%|###8      | 298/781 [00:15<00:25, 19.16it/s]
 38%|###8      | 300/781 [00:15<00:25, 19.08it/s]
 39%|###8      | 302/781 [00:15<00:25, 19.03it/s]
 39%|###8      | 304/781 [00:15<00:25, 18.98it/s]
 39%|###9      | 306/781 [00:16<00:25, 18.92it/s]
 39%|###9      | 308/781 [00:16<00:25, 18.84it/s]
 40%|###9      | 310/781 [00:16<00:25, 18.67it/s]
 40%|###9      | 312/781 [00:16<00:26, 17.71it/s]
 40%|####      | 314/781 [00:16<00:25, 18.20it/s]
 40%|####      | 316/781 [00:16<00:25, 18.52it/s]
 41%|####      | 318/781 [00:16<00:24, 18.67it/s]
 41%|####      | 320/781 [00:16<00:24, 18.47it/s]
 41%|####1     | 322/781 [00:16<00:24, 18.69it/s]
 41%|####1     | 324/781 [00:16<00:24, 18.52it/s]
 42%|####1     | 326/781 [00:17<00:24, 18.59it/s]
 42%|####1     | 328/781 [00:17<00:24, 18.75it/s]
 42%|####2     | 330/781 [00:17<00:24, 18.75it/s]
 43%|####2     | 332/781 [00:17<00:23, 18.77it/s]
 43%|####2     | 334/781 [00:17<00:23, 18.88it/s]
 43%|####3     | 336/781 [00:17<00:23, 18.97it/s]
 43%|####3     | 338/781 [00:17<00:23, 19.05it/s]
 44%|####3     | 340/781 [00:17<00:23, 18.99it/s]
 44%|####3     | 342/781 [00:17<00:23, 18.92it/s]
 44%|####4     | 344/781 [00:18<00:23, 18.85it/s]
 44%|####4     | 346/781 [00:18<00:23, 18.82it/s]
 45%|####4     | 348/781 [00:18<00:22, 18.84it/s]
 45%|####4     | 350/781 [00:18<00:22, 18.85it/s]
 45%|####5     | 352/781 [00:18<00:22, 18.86it/s]
 45%|####5     | 354/781 [00:18<00:22, 18.59it/s]
 46%|####5     | 356/781 [00:18<00:22, 18.65it/s]
 46%|####5     | 358/781 [00:18<00:22, 18.73it/s]
 46%|####6     | 360/781 [00:18<00:22, 18.84it/s]
 46%|####6     | 362/781 [00:19<00:22, 18.98it/s]
 47%|####6     | 364/781 [00:19<00:21, 19.22it/s]
 47%|####6     | 366/781 [00:19<00:21, 19.22it/s]
 47%|####7     | 368/781 [00:19<00:21, 19.27it/s]
 47%|####7     | 370/781 [00:19<00:21, 19.35it/s]
 48%|####7     | 372/781 [00:19<00:21, 19.39it/s]
 48%|####7     | 374/781 [00:19<00:20, 19.46it/s]
 48%|####8     | 376/781 [00:19<00:20, 19.47it/s]
 48%|####8     | 378/781 [00:19<00:20, 19.50it/s]
 49%|####8     | 380/781 [00:19<00:20, 19.60it/s]
 49%|####8     | 382/781 [00:20<00:20, 19.61it/s]
 49%|####9     | 384/781 [00:20<00:20, 19.63it/s]
 49%|####9     | 386/781 [00:20<00:20, 19.62it/s]
 50%|####9     | 388/781 [00:20<00:19, 19.66it/s]
 50%|####9     | 390/781 [00:20<00:19, 19.58it/s]
 50%|#####     | 392/781 [00:20<00:19, 19.54it/s]
 50%|#####     | 394/781 [00:20<00:19, 19.56it/s]
 51%|#####     | 396/781 [00:20<00:19, 19.59it/s]
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100%|#########9| 780/781 [00:41<00:00, 18.68it/s]
100%|##########| 781/781 [00:41<00:00, 18.80it/s]




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Validation Progress:  45%|####5     | 20/44 [00:21<00:26,  1.11s/it]
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Validation Progress:  48%|####7     | 21/44 [00:22<00:25,  1.10s/it]
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Validation Progress:  50%|#####     | 22/44 [00:23<00:24,  1.13s/it]
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Validation Progress:  52%|#####2    | 23/44 [00:24<00:24,  1.18s/it]
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Validation Progress:  52%|#####2    | 23/44 [00:24<00:24,  1.19s/it]
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Validation Progress:  55%|#####4    | 24/44 [00:25<00:22,  1.15s/it]
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Validation Progress:  57%|#####6    | 25/44 [00:26<00:21,  1.15s/it]
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Validation Progress:  59%|#####9    | 26/44 [00:28<00:20,  1.14s/it]
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Validation Progress:  59%|#####9    | 26/44 [00:28<00:20,  1.14s/it]
Validation Progress:  61%|######1   | 27/44 [00:29<00:19,  1.15s/it]
Validation Progress:  61%|######1   | 27/44 [00:29<00:19,  1.15s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:18,  1.13s/it]
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Validation Progress:  64%|######3   | 28/44 [00:30<00:18,  1.13s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.11s/it]
Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.11s/it]
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Validation Progress:  66%|######5   | 29/44 [00:31<00:16,  1.11s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
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Validation Progress:  68%|######8   | 30/44 [00:32<00:15,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
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Validation Progress:  70%|#######   | 31/44 [00:33<00:14,  1.14s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  73%|#######2  | 32/44 [00:34<00:13,  1.12s/it]
Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.10s/it]
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Validation Progress:  75%|#######5  | 33/44 [00:35<00:12,  1.10s/it]
Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.17s/it]
Validation Progress:  77%|#######7  | 34/44 [00:37<00:11,  1.17s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  80%|#######9  | 35/44 [00:38<00:10,  1.16s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  82%|########1 | 36/44 [00:39<00:09,  1.15s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  84%|########4 | 37/44 [00:40<00:08,  1.19s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  86%|########6 | 38/44 [00:41<00:07,  1.20s/it]
Validation Progress:  89%|########8 | 39/44 [00:43<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:43<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:43<00:05,  1.16s/it]
Validation Progress:  89%|########8 | 39/44 [00:43<00:05,  1.16s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.15s/it]
Validation Progress:  91%|######### | 40/44 [00:44<00:04,  1.15s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.19s/it]
Validation Progress:  93%|#########3| 41/44 [00:45<00:03,  1.20s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  95%|#########5| 42/44 [00:46<00:02,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress:  98%|#########7| 43/44 [00:47<00:01,  1.19s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.00s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.01s/it]
Validation Progress: 100%|##########| 44/44 [00:48<00:00,  1.10s/it]

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100%|##########| 1/1 [00:19<00:00, 19.89s/it]
100%|##########| 1/1 [00:19<00:00, 19.89s/it]

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 10%|#         | 16/157 [00:00<00:08, 17.27it/s]
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100%|##########| 157/157 [00:09<00:00, 16.14it/s]

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 23%|##2       | 176/781 [00:09<00:34, 17.56it/s]
 23%|##2       | 178/781 [00:09<00:34, 17.51it/s]
 23%|##3       | 180/781 [00:10<00:34, 17.66it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.79it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.94it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.90it/s]
 24%|##4       | 188/781 [00:10<00:33, 17.78it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.72it/s]
 25%|##4       | 192/781 [00:10<00:33, 17.70it/s]
 25%|##4       | 194/781 [00:10<00:33, 17.61it/s]
 25%|##5       | 196/781 [00:10<00:32, 17.75it/s]
 25%|##5       | 198/781 [00:11<00:32, 17.79it/s]
 26%|##5       | 200/781 [00:11<00:32, 17.91it/s]
 26%|##5       | 202/781 [00:11<00:32, 18.00it/s]
 26%|##6       | 204/781 [00:11<00:31, 18.08it/s]
 26%|##6       | 206/781 [00:11<00:31, 18.11it/s]
 27%|##6       | 208/781 [00:11<00:31, 18.15it/s]
 27%|##6       | 210/781 [00:11<00:31, 18.09it/s]
 27%|##7       | 212/781 [00:11<00:31, 18.09it/s]
 27%|##7       | 214/781 [00:11<00:31, 18.06it/s]
 28%|##7       | 216/781 [00:12<00:31, 18.07it/s]
 28%|##7       | 218/781 [00:12<00:31, 18.03it/s]
 28%|##8       | 220/781 [00:12<00:30, 18.11it/s]
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 29%|##8       | 224/781 [00:12<00:30, 18.03it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.78it/s]
 29%|##9       | 228/781 [00:12<00:31, 17.67it/s]
 29%|##9       | 230/781 [00:12<00:30, 17.83it/s]
 30%|##9       | 232/781 [00:12<00:30, 17.92it/s]
 30%|##9       | 234/781 [00:13<00:30, 18.02it/s]
 30%|###       | 236/781 [00:13<00:30, 17.98it/s]
 30%|###       | 238/781 [00:13<00:30, 17.98it/s]
 31%|###       | 240/781 [00:13<00:30, 17.99it/s]
 31%|###       | 242/781 [00:13<00:29, 18.09it/s]
 31%|###1      | 244/781 [00:13<00:29, 18.12it/s]
 31%|###1      | 246/781 [00:13<00:29, 18.16it/s]
 32%|###1      | 248/781 [00:13<00:29, 18.17it/s]
 32%|###2      | 250/781 [00:13<00:29, 18.22it/s]
 32%|###2      | 252/781 [00:14<00:29, 18.13it/s]
 33%|###2      | 254/781 [00:14<00:29, 18.00it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.89it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.83it/s]
 33%|###3      | 260/781 [00:14<00:29, 17.75it/s]
 34%|###3      | 262/781 [00:14<00:29, 17.71it/s]
 34%|###3      | 264/781 [00:14<00:29, 17.71it/s]
 34%|###4      | 266/781 [00:14<00:29, 17.54it/s]
 34%|###4      | 268/781 [00:14<00:29, 17.57it/s]
 35%|###4      | 270/781 [00:15<00:29, 17.57it/s]
 35%|###4      | 272/781 [00:15<00:28, 17.69it/s]
 35%|###5      | 274/781 [00:15<00:28, 17.75it/s]
 35%|###5      | 276/781 [00:15<00:28, 17.57it/s]
 36%|###5      | 278/781 [00:15<00:28, 17.67it/s]
 36%|###5      | 280/781 [00:15<00:28, 17.80it/s]
 36%|###6      | 282/781 [00:15<00:27, 17.88it/s]
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 37%|###6      | 286/781 [00:15<00:27, 17.83it/s]
 37%|###6      | 288/781 [00:16<00:27, 17.84it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.80it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.88it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.91it/s]
 38%|###7      | 296/781 [00:16<00:26, 18.02it/s]
 38%|###8      | 298/781 [00:16<00:26, 18.13it/s]
 38%|###8      | 300/781 [00:16<00:26, 18.18it/s]
 39%|###8      | 302/781 [00:16<00:26, 18.13it/s]
 39%|###8      | 304/781 [00:16<00:26, 18.10it/s]
 39%|###9      | 306/781 [00:17<00:26, 18.16it/s]
 39%|###9      | 308/781 [00:17<00:25, 18.20it/s]
 40%|###9      | 310/781 [00:17<00:25, 18.12it/s]
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 40%|####      | 314/781 [00:17<00:25, 18.22it/s]
 40%|####      | 316/781 [00:17<00:25, 18.26it/s]
 41%|####      | 318/781 [00:17<00:25, 18.31it/s]
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 41%|####1     | 322/781 [00:17<00:25, 17.98it/s]
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 50%|####9     | 388/781 [00:21<00:21, 17.88it/s]
 50%|####9     | 390/781 [00:21<00:21, 17.92it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.95it/s]
 50%|#####     | 394/781 [00:21<00:21, 18.06it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.58it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.75it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.76it/s]
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 71%|#######1  | 555/781 [00:30<00:11, 19.31it/s]
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 72%|#######1  | 560/781 [00:31<00:11, 19.52it/s]
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 73%|#######2  | 568/781 [00:31<00:11, 18.51it/s]
 73%|#######2  | 570/781 [00:31<00:11, 18.18it/s]
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100%|#########9| 780/781 [00:43<00:00, 18.23it/s]
100%|##########| 781/781 [00:43<00:00, 18.02it/s]




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 80%|########  | 126/157 [00:07<00:01, 17.79it/s]
 82%|########1 | 128/157 [00:07<00:01, 17.90it/s]
 83%|########2 | 130/157 [00:07<00:01, 17.94it/s]
 84%|########4 | 132/157 [00:07<00:01, 17.66it/s]
 85%|########5 | 134/157 [00:08<00:01, 17.69it/s]
 87%|########6 | 136/157 [00:08<00:01, 17.82it/s]
 88%|########7 | 138/157 [00:08<00:01, 17.91it/s]
 89%|########9 | 140/157 [00:08<00:00, 17.81it/s]
 90%|######### | 142/157 [00:08<00:00, 17.55it/s]
 92%|#########1| 144/157 [00:08<00:00, 17.48it/s]
 93%|#########2| 146/157 [00:08<00:00, 17.59it/s]
 94%|#########4| 148/157 [00:08<00:00, 17.37it/s]
 96%|#########5| 150/157 [00:09<00:00, 17.40it/s]
 97%|#########6| 152/157 [00:09<00:00, 17.50it/s]
 98%|#########8| 154/157 [00:09<00:00, 17.62it/s]
 99%|#########9| 156/157 [00:09<00:00, 17.40it/s]
100%|##########| 157/157 [00:09<00:00, 16.72it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:42, 18.23it/s]
  1%|          | 4/781 [00:00<00:42, 18.40it/s]
  1%|          | 6/781 [00:00<00:42, 18.41it/s]
  1%|1         | 8/781 [00:00<00:40, 18.98it/s]
  1%|1         | 11/781 [00:00<00:39, 19.58it/s]
  2%|1         | 13/781 [00:00<00:39, 19.53it/s]
  2%|1         | 15/781 [00:01<01:33,  8.22it/s]
  2%|2         | 17/781 [00:01<01:16,  9.97it/s]
  2%|2         | 19/781 [00:01<01:04, 11.73it/s]
  3%|2         | 21/781 [00:01<00:56, 13.37it/s]
  3%|3         | 24/781 [00:01<00:49, 15.43it/s]
  3%|3         | 27/781 [00:01<00:44, 16.98it/s]
  4%|3         | 30/781 [00:01<00:41, 17.95it/s]
  4%|4         | 33/781 [00:02<00:40, 18.69it/s]
  5%|4         | 36/781 [00:02<00:38, 19.20it/s]
  5%|4         | 38/781 [00:02<00:38, 19.33it/s]
  5%|5         | 40/781 [00:02<00:38, 19.47it/s]
  6%|5         | 43/781 [00:02<00:37, 19.71it/s]
  6%|5         | 46/781 [00:02<00:36, 19.94it/s]
  6%|6         | 49/781 [00:02<00:36, 20.05it/s]
  7%|6         | 52/781 [00:03<00:36, 20.04it/s]
  7%|7         | 55/781 [00:03<00:36, 19.89it/s]
  7%|7         | 57/781 [00:03<00:36, 19.75it/s]
  8%|7         | 59/781 [00:03<00:36, 19.78it/s]
  8%|7         | 62/781 [00:03<00:36, 19.90it/s]
  8%|8         | 65/781 [00:03<00:35, 20.09it/s]
  9%|8         | 68/781 [00:03<00:35, 19.98it/s]
  9%|9         | 71/781 [00:04<00:35, 20.03it/s]
  9%|9         | 74/781 [00:04<00:35, 20.19it/s]
 10%|9         | 77/781 [00:04<00:34, 20.16it/s]
 10%|#         | 80/781 [00:04<00:35, 19.93it/s]
 10%|#         | 82/781 [00:04<00:35, 19.94it/s]
 11%|#         | 85/781 [00:04<00:34, 20.09it/s]
 11%|#1        | 88/781 [00:04<00:34, 20.28it/s]
 12%|#1        | 91/781 [00:05<00:33, 20.36it/s]
 12%|#2        | 94/781 [00:05<00:34, 20.12it/s]
 12%|#2        | 97/781 [00:05<00:34, 19.91it/s]
 13%|#2        | 99/781 [00:05<00:34, 19.84it/s]
 13%|#3        | 102/781 [00:05<00:34, 19.93it/s]
 13%|#3        | 105/781 [00:05<00:34, 19.73it/s]
 14%|#3        | 107/781 [00:05<00:34, 19.76it/s]
 14%|#4        | 110/781 [00:05<00:33, 20.02it/s]
 14%|#4        | 113/781 [00:06<00:33, 19.90it/s]
 15%|#4        | 115/781 [00:06<00:33, 19.91it/s]
 15%|#4        | 117/781 [00:06<00:33, 19.87it/s]
 15%|#5        | 119/781 [00:06<00:33, 19.78it/s]
 16%|#5        | 122/781 [00:06<00:33, 19.95it/s]
 16%|#6        | 125/781 [00:06<00:32, 20.15it/s]
 16%|#6        | 128/781 [00:06<00:32, 20.10it/s]
 17%|#6        | 131/781 [00:07<00:32, 20.25it/s]
 17%|#7        | 134/781 [00:07<00:31, 20.32it/s]
 18%|#7        | 137/781 [00:07<00:32, 19.94it/s]
 18%|#7        | 140/781 [00:07<00:31, 20.08it/s]
 18%|#8        | 143/781 [00:07<00:31, 20.21it/s]
 19%|#8        | 146/781 [00:07<00:31, 20.12it/s]
 19%|#9        | 149/781 [00:07<00:31, 20.25it/s]
 19%|#9        | 152/781 [00:08<00:31, 20.15it/s]
 20%|#9        | 155/781 [00:08<00:30, 20.26it/s]
 20%|##        | 158/781 [00:08<00:30, 20.30it/s]
 21%|##        | 161/781 [00:08<00:30, 20.28it/s]
 21%|##        | 164/781 [00:08<00:30, 19.98it/s]
 21%|##1       | 167/781 [00:08<00:30, 20.16it/s]
 22%|##1       | 170/781 [00:08<00:30, 20.27it/s]
 22%|##2       | 173/781 [00:09<00:30, 20.16it/s]
 23%|##2       | 176/781 [00:09<00:30, 20.03it/s]
 23%|##2       | 179/781 [00:09<00:30, 20.04it/s]
 23%|##3       | 182/781 [00:09<00:29, 20.17it/s]
 24%|##3       | 185/781 [00:09<00:29, 20.25it/s]
 24%|##4       | 188/781 [00:09<00:29, 20.21it/s]
 24%|##4       | 191/781 [00:10<00:29, 20.32it/s]
 25%|##4       | 194/781 [00:10<00:28, 20.43it/s]
 25%|##5       | 197/781 [00:10<00:28, 20.41it/s]
 26%|##5       | 200/781 [00:10<00:28, 20.26it/s]
 26%|##5       | 203/781 [00:10<00:28, 20.34it/s]
 26%|##6       | 206/781 [00:10<00:28, 20.44it/s]
 27%|##6       | 209/781 [00:10<00:27, 20.48it/s]
 27%|##7       | 212/781 [00:11<00:27, 20.36it/s]
 28%|##7       | 215/781 [00:11<00:27, 20.45it/s]
 28%|##7       | 218/781 [00:11<00:27, 20.43it/s]
 28%|##8       | 221/781 [00:11<00:27, 20.49it/s]
 29%|##8       | 224/781 [00:11<00:27, 20.27it/s]
 29%|##9       | 227/781 [00:11<00:27, 20.36it/s]
 29%|##9       | 230/781 [00:11<00:27, 20.38it/s]
 30%|##9       | 233/781 [00:12<00:27, 20.24it/s]
 30%|###       | 236/781 [00:12<00:27, 20.18it/s]
 31%|###       | 239/781 [00:12<00:26, 20.12it/s]
 31%|###       | 242/781 [00:12<00:26, 20.27it/s]
 31%|###1      | 245/781 [00:12<00:26, 20.23it/s]
 32%|###1      | 248/781 [00:12<00:26, 19.98it/s]
 32%|###2      | 250/781 [00:12<00:26, 19.75it/s]
 32%|###2      | 253/781 [00:13<00:26, 19.98it/s]
 33%|###2      | 256/781 [00:13<00:26, 20.09it/s]
 33%|###3      | 259/781 [00:13<00:25, 20.17it/s]
 34%|###3      | 262/781 [00:13<00:25, 20.16it/s]
 34%|###3      | 265/781 [00:13<00:25, 20.30it/s]
 34%|###4      | 268/781 [00:13<00:25, 20.20it/s]
 35%|###4      | 271/781 [00:13<00:25, 19.90it/s]
 35%|###4      | 273/781 [00:14<00:25, 19.88it/s]
 35%|###5      | 275/781 [00:14<00:25, 19.86it/s]
 35%|###5      | 277/781 [00:14<00:25, 19.59it/s]
 36%|###5      | 279/781 [00:14<00:25, 19.36it/s]
 36%|###5      | 281/781 [00:14<00:26, 19.04it/s]
 36%|###6      | 283/781 [00:14<00:26, 18.97it/s]
 37%|###6      | 286/781 [00:14<00:25, 19.49it/s]
 37%|###7      | 289/781 [00:14<00:24, 19.88it/s]
 37%|###7      | 292/781 [00:15<00:24, 20.14it/s]
 38%|###7      | 295/781 [00:15<00:23, 20.27it/s]
 38%|###8      | 298/781 [00:15<00:23, 20.39it/s]
 39%|###8      | 301/781 [00:15<00:23, 20.48it/s]
 39%|###8      | 304/781 [00:15<00:23, 20.45it/s]
 39%|###9      | 307/781 [00:15<00:23, 20.36it/s]
 40%|###9      | 310/781 [00:15<00:23, 20.18it/s]
 40%|####      | 313/781 [00:16<00:23, 20.26it/s]
 40%|####      | 316/781 [00:16<00:23, 20.16it/s]
 41%|####      | 319/781 [00:16<00:22, 20.25it/s]
 41%|####1     | 322/781 [00:16<00:22, 20.20it/s]
 42%|####1     | 325/781 [00:16<00:22, 20.18it/s]
 42%|####1     | 328/781 [00:16<00:22, 20.20it/s]
 42%|####2     | 331/781 [00:16<00:22, 20.28it/s]
 43%|####2     | 334/781 [00:17<00:21, 20.45it/s]
 43%|####3     | 337/781 [00:17<00:21, 20.45it/s]
 44%|####3     | 340/781 [00:17<00:21, 20.54it/s]
 44%|####3     | 343/781 [00:17<00:21, 20.54it/s]
 44%|####4     | 346/781 [00:17<00:21, 20.58it/s]
 45%|####4     | 349/781 [00:17<00:20, 20.60it/s]
 45%|####5     | 352/781 [00:17<00:20, 20.59it/s]
 45%|####5     | 355/781 [00:18<00:20, 20.51it/s]
 46%|####5     | 358/781 [00:18<00:20, 20.58it/s]
 46%|####6     | 361/781 [00:18<00:20, 20.54it/s]
 47%|####6     | 364/781 [00:18<00:20, 20.40it/s]
 47%|####6     | 367/781 [00:18<00:20, 20.23it/s]
 47%|####7     | 370/781 [00:18<00:20, 20.19it/s]
 48%|####7     | 373/781 [00:18<00:20, 20.32it/s]
 48%|####8     | 376/781 [00:19<00:19, 20.35it/s]
 49%|####8     | 379/781 [00:19<00:19, 20.38it/s]
 49%|####8     | 382/781 [00:19<00:19, 20.06it/s]
 49%|####9     | 385/781 [00:19<00:19, 19.94it/s]
 50%|####9     | 387/781 [00:19<00:19, 19.91it/s]
 50%|####9     | 389/781 [00:19<00:19, 19.90it/s]
 50%|#####     | 391/781 [00:19<00:19, 19.86it/s]
 50%|#####     | 393/781 [00:20<00:19, 19.88it/s]
 51%|#####     | 395/781 [00:20<00:19, 19.82it/s]
 51%|#####     | 398/781 [00:20<00:19, 20.06it/s]
 51%|#####1    | 401/781 [00:20<00:19, 19.98it/s]
 52%|#####1    | 404/781 [00:20<00:18, 20.06it/s]
 52%|#####2    | 407/781 [00:20<00:19, 19.27it/s]
 52%|#####2    | 409/781 [00:20<00:19, 19.25it/s]
 53%|#####2    | 411/781 [00:20<00:19, 19.21it/s]
 53%|#####3    | 414/781 [00:21<00:18, 19.57it/s]
 53%|#####3    | 416/781 [00:21<00:18, 19.65it/s]
 54%|#####3    | 418/781 [00:21<00:18, 19.69it/s]
 54%|#####3    | 421/781 [00:21<00:18, 19.89it/s]
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 55%|#####4    | 427/781 [00:21<00:17, 19.95it/s]
 55%|#####4    | 429/781 [00:21<00:17, 19.88it/s]
 55%|#####5    | 431/781 [00:21<00:17, 19.74it/s]
 56%|#####5    | 434/781 [00:22<00:17, 19.85it/s]
 56%|#####5    | 437/781 [00:22<00:17, 19.99it/s]
 56%|#####6    | 439/781 [00:22<00:17, 19.74it/s]
 56%|#####6    | 441/781 [00:22<00:17, 19.80it/s]
 57%|#####6    | 444/781 [00:22<00:16, 20.07it/s]
 57%|#####7    | 447/781 [00:22<00:16, 19.93it/s]
 58%|#####7    | 450/781 [00:22<00:16, 20.11it/s]
 58%|#####8    | 453/781 [00:23<00:16, 20.21it/s]
 58%|#####8    | 456/781 [00:23<00:16, 20.29it/s]
 59%|#####8    | 459/781 [00:23<00:15, 20.15it/s]
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 60%|######    | 470/781 [00:23<00:15, 19.98it/s]
 60%|######    | 472/781 [00:23<00:15, 19.89it/s]
 61%|######    | 474/781 [00:24<00:15, 19.90it/s]
 61%|######    | 476/781 [00:24<00:15, 19.82it/s]
 61%|######1   | 478/781 [00:24<00:15, 19.59it/s]
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 62%|######1   | 483/781 [00:24<00:15, 19.81it/s]
 62%|######2   | 486/781 [00:24<00:14, 20.02it/s]
 63%|######2   | 489/781 [00:24<00:14, 20.15it/s]
 63%|######2   | 492/781 [00:24<00:14, 20.23it/s]
 63%|######3   | 495/781 [00:25<00:14, 20.19it/s]
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 65%|######4   | 507/781 [00:25<00:13, 20.25it/s]
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 66%|######5   | 513/781 [00:26<00:13, 20.39it/s]
 66%|######6   | 516/781 [00:26<00:12, 20.46it/s]
 66%|######6   | 519/781 [00:26<00:12, 20.47it/s]
 67%|######6   | 522/781 [00:26<00:12, 20.49it/s]
 67%|######7   | 525/781 [00:26<00:12, 20.54it/s]
 68%|######7   | 528/781 [00:26<00:12, 20.54it/s]
 68%|######7   | 531/781 [00:26<00:12, 20.07it/s]
 68%|######8   | 534/781 [00:27<00:12, 20.00it/s]
 69%|######8   | 537/781 [00:27<00:12, 19.68it/s]
 69%|######9   | 539/781 [00:27<00:12, 19.04it/s]
 69%|######9   | 541/781 [00:27<00:12, 18.71it/s]
 70%|######9   | 543/781 [00:27<00:13, 18.19it/s]
 70%|######9   | 545/781 [00:27<00:12, 18.16it/s]
 70%|#######   | 547/781 [00:27<00:12, 18.46it/s]
 70%|#######   | 549/781 [00:27<00:12, 18.57it/s]
 71%|#######   | 552/781 [00:28<00:12, 18.47it/s]
 71%|#######   | 554/781 [00:28<00:12, 18.48it/s]
 71%|#######1  | 556/781 [00:28<00:12, 18.37it/s]
 71%|#######1  | 558/781 [00:28<00:12, 18.30it/s]
 72%|#######1  | 560/781 [00:28<00:12, 18.18it/s]
 72%|#######1  | 562/781 [00:28<00:12, 18.07it/s]
 72%|#######2  | 564/781 [00:28<00:12, 17.94it/s]
 72%|#######2  | 566/781 [00:28<00:11, 18.06it/s]
 73%|#######2  | 568/781 [00:28<00:11, 18.01it/s]
 73%|#######2  | 570/781 [00:29<00:11, 18.04it/s]
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 76%|#######5  | 590/781 [00:30<00:10, 18.01it/s]
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 77%|#######6  | 600/781 [00:30<00:10, 17.97it/s]
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100%|##########| 781/781 [00:40<00:00, 19.27it/s]




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 39%|###9      | 62/157 [00:04<00:06, 15.75it/s]
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 42%|####2     | 66/157 [00:04<00:05, 15.82it/s]
 43%|####3     | 68/157 [00:04<00:05, 15.80it/s]
 45%|####4     | 70/157 [00:04<00:05, 15.86it/s]
 46%|####5     | 72/157 [00:04<00:05, 15.81it/s]
 47%|####7     | 74/157 [00:04<00:05, 15.71it/s]
 48%|####8     | 76/157 [00:04<00:05, 15.66it/s]
 50%|####9     | 78/157 [00:05<00:05, 15.67it/s]
 51%|#####     | 80/157 [00:05<00:04, 15.62it/s]
 52%|#####2    | 82/157 [00:05<00:04, 15.66it/s]
 54%|#####3    | 84/157 [00:05<00:04, 15.72it/s]
 55%|#####4    | 86/157 [00:05<00:04, 15.73it/s]
 56%|#####6    | 88/157 [00:05<00:04, 15.77it/s]
 57%|#####7    | 90/157 [00:05<00:04, 15.65it/s]
 59%|#####8    | 92/157 [00:05<00:04, 15.60it/s]
 60%|#####9    | 94/157 [00:06<00:04, 15.67it/s]
 61%|######1   | 96/157 [00:06<00:03, 15.68it/s]
 62%|######2   | 98/157 [00:06<00:03, 15.66it/s]
 64%|######3   | 100/157 [00:06<00:03, 15.68it/s]
 65%|######4   | 102/157 [00:06<00:03, 15.65it/s]
 66%|######6   | 104/157 [00:06<00:03, 15.68it/s]
 68%|######7   | 106/157 [00:06<00:03, 15.74it/s]
 69%|######8   | 108/157 [00:06<00:03, 15.84it/s]
 70%|#######   | 110/157 [00:07<00:02, 15.88it/s]
 71%|#######1  | 112/157 [00:07<00:02, 15.89it/s]
 73%|#######2  | 114/157 [00:07<00:02, 15.83it/s]
 74%|#######3  | 116/157 [00:07<00:02, 15.82it/s]
 75%|#######5  | 118/157 [00:07<00:02, 15.88it/s]
 76%|#######6  | 120/157 [00:07<00:02, 15.91it/s]
 78%|#######7  | 122/157 [00:07<00:02, 15.88it/s]
 79%|#######8  | 124/157 [00:07<00:02, 15.88it/s]
 80%|########  | 126/157 [00:08<00:01, 15.62it/s]
 82%|########1 | 128/157 [00:08<00:01, 15.56it/s]
 83%|########2 | 130/157 [00:08<00:01, 15.63it/s]
 84%|########4 | 132/157 [00:08<00:01, 15.72it/s]
 85%|########5 | 134/157 [00:08<00:01, 15.66it/s]
 87%|########6 | 136/157 [00:08<00:01, 15.64it/s]
 88%|########7 | 138/157 [00:08<00:01, 15.61it/s]
 89%|########9 | 140/157 [00:08<00:01, 15.62it/s]
 90%|######### | 142/157 [00:09<00:00, 15.66it/s]
 92%|#########1| 144/157 [00:09<00:00, 15.74it/s]
 93%|#########2| 146/157 [00:09<00:00, 15.72it/s]
 94%|#########4| 148/157 [00:09<00:00, 15.70it/s]
 96%|#########5| 150/157 [00:09<00:00, 15.74it/s]
 97%|#########6| 152/157 [00:09<00:00, 15.76it/s]
 98%|#########8| 154/157 [00:09<00:00, 15.68it/s]
 99%|#########9| 156/157 [00:09<00:00, 15.74it/s]
100%|##########| 157/157 [00:10<00:00, 15.68it/s]

  0%|          | 0/781 [00:00<?, ?it/s]
  0%|          | 2/781 [00:00<00:46, 16.82it/s]
  1%|          | 4/781 [00:00<00:46, 16.63it/s]
  1%|          | 6/781 [00:00<00:47, 16.25it/s]
  1%|1         | 8/781 [00:00<00:45, 17.06it/s]
  1%|1         | 10/781 [00:00<00:44, 17.20it/s]
  2%|1         | 12/781 [00:00<00:44, 17.37it/s]
  2%|1         | 14/781 [00:00<00:43, 17.55it/s]
  2%|2         | 16/781 [00:00<00:44, 17.22it/s]
  2%|2         | 18/781 [00:01<00:43, 17.49it/s]
  3%|2         | 20/781 [00:01<00:43, 17.51it/s]
  3%|2         | 22/781 [00:01<00:43, 17.59it/s]
  3%|3         | 24/781 [00:01<00:42, 17.74it/s]
  3%|3         | 26/781 [00:01<00:42, 17.74it/s]
  4%|3         | 28/781 [00:01<00:42, 17.53it/s]
  4%|3         | 30/781 [00:01<00:42, 17.66it/s]
  4%|4         | 32/781 [00:01<00:42, 17.68it/s]
  4%|4         | 34/781 [00:01<00:42, 17.68it/s]
  5%|4         | 36/781 [00:02<00:41, 17.81it/s]
  5%|4         | 38/781 [00:02<00:41, 17.95it/s]
  5%|5         | 40/781 [00:02<00:41, 18.06it/s]
  5%|5         | 42/781 [00:02<00:40, 18.06it/s]
  6%|5         | 44/781 [00:02<00:40, 18.10it/s]
  6%|5         | 46/781 [00:02<00:40, 17.94it/s]
  6%|6         | 48/781 [00:02<00:40, 17.89it/s]
  6%|6         | 50/781 [00:02<00:40, 17.93it/s]
  7%|6         | 52/781 [00:02<00:40, 17.88it/s]
  7%|6         | 54/781 [00:03<00:40, 17.75it/s]
  7%|7         | 56/781 [00:03<00:40, 17.69it/s]
  7%|7         | 58/781 [00:03<00:40, 17.79it/s]
  8%|7         | 60/781 [00:03<00:40, 17.77it/s]
  8%|7         | 62/781 [00:03<00:40, 17.79it/s]
  8%|8         | 64/781 [00:03<00:40, 17.87it/s]
  8%|8         | 66/781 [00:03<00:40, 17.77it/s]
  9%|8         | 68/781 [00:03<00:40, 17.78it/s]
  9%|8         | 70/781 [00:03<00:39, 17.80it/s]
  9%|9         | 72/781 [00:04<00:39, 17.89it/s]
  9%|9         | 74/781 [00:04<00:39, 17.96it/s]
 10%|9         | 76/781 [00:04<00:39, 18.06it/s]
 10%|9         | 78/781 [00:04<00:38, 18.04it/s]
 10%|#         | 80/781 [00:04<00:39, 17.89it/s]
 10%|#         | 82/781 [00:04<00:39, 17.70it/s]
 11%|#         | 84/781 [00:04<00:39, 17.69it/s]
 11%|#1        | 86/781 [00:04<00:39, 17.59it/s]
 11%|#1        | 88/781 [00:04<00:39, 17.70it/s]
 12%|#1        | 90/781 [00:05<00:38, 17.87it/s]
 12%|#1        | 92/781 [00:05<00:38, 17.81it/s]
 12%|#2        | 94/781 [00:05<00:38, 17.80it/s]
 12%|#2        | 96/781 [00:05<00:38, 17.73it/s]
 13%|#2        | 98/781 [00:05<00:38, 17.88it/s]
 13%|#2        | 100/781 [00:05<00:37, 17.99it/s]
 13%|#3        | 102/781 [00:05<00:37, 17.95it/s]
 13%|#3        | 104/781 [00:05<00:37, 17.96it/s]
 14%|#3        | 106/781 [00:05<00:37, 18.06it/s]
 14%|#3        | 108/781 [00:06<00:37, 18.04it/s]
 14%|#4        | 110/781 [00:06<00:37, 17.98it/s]
 14%|#4        | 112/781 [00:06<00:36, 18.12it/s]
 15%|#4        | 114/781 [00:06<00:37, 17.92it/s]
 15%|#4        | 116/781 [00:06<00:37, 17.95it/s]
 15%|#5        | 118/781 [00:06<00:36, 18.06it/s]
 15%|#5        | 120/781 [00:06<00:36, 17.97it/s]
 16%|#5        | 122/781 [00:06<00:36, 17.86it/s]
 16%|#5        | 124/781 [00:06<00:36, 17.82it/s]
 16%|#6        | 126/781 [00:07<00:36, 17.92it/s]
 16%|#6        | 128/781 [00:07<00:36, 17.96it/s]
 17%|#6        | 130/781 [00:07<00:36, 18.00it/s]
 17%|#6        | 132/781 [00:07<00:35, 18.03it/s]
 17%|#7        | 134/781 [00:07<00:36, 17.94it/s]
 17%|#7        | 136/781 [00:07<00:35, 17.99it/s]
 18%|#7        | 138/781 [00:07<00:35, 18.00it/s]
 18%|#7        | 140/781 [00:07<00:35, 18.02it/s]
 18%|#8        | 142/781 [00:07<00:35, 18.07it/s]
 18%|#8        | 144/781 [00:08<00:35, 18.11it/s]
 19%|#8        | 146/781 [00:08<00:35, 18.07it/s]
 19%|#8        | 148/781 [00:08<00:35, 17.98it/s]
 19%|#9        | 150/781 [00:08<00:34, 18.11it/s]
 19%|#9        | 152/781 [00:08<00:34, 18.18it/s]
 20%|#9        | 154/781 [00:08<00:34, 17.98it/s]
 20%|#9        | 156/781 [00:08<00:35, 17.79it/s]
 20%|##        | 158/781 [00:08<00:34, 17.92it/s]
 20%|##        | 160/781 [00:08<00:34, 18.06it/s]
 21%|##        | 162/781 [00:09<00:34, 18.14it/s]
 21%|##        | 164/781 [00:09<00:34, 18.05it/s]
 21%|##1       | 166/781 [00:09<00:34, 17.95it/s]
 22%|##1       | 168/781 [00:09<00:34, 17.83it/s]
 22%|##1       | 170/781 [00:09<00:34, 17.93it/s]
 22%|##2       | 172/781 [00:09<00:34, 17.87it/s]
 22%|##2       | 174/781 [00:09<00:33, 17.86it/s]
 23%|##2       | 176/781 [00:09<00:34, 17.73it/s]
 23%|##2       | 178/781 [00:09<00:34, 17.70it/s]
 23%|##3       | 180/781 [00:10<00:33, 17.85it/s]
 23%|##3       | 182/781 [00:10<00:33, 17.81it/s]
 24%|##3       | 184/781 [00:10<00:33, 17.71it/s]
 24%|##3       | 186/781 [00:10<00:33, 17.65it/s]
 24%|##4       | 188/781 [00:10<00:33, 17.70it/s]
 24%|##4       | 190/781 [00:10<00:33, 17.79it/s]
 25%|##4       | 192/781 [00:10<00:32, 17.92it/s]
 25%|##4       | 194/781 [00:10<00:32, 17.83it/s]
 25%|##5       | 196/781 [00:10<00:33, 17.68it/s]
 25%|##5       | 198/781 [00:11<00:33, 17.51it/s]
 26%|##5       | 200/781 [00:11<00:33, 17.58it/s]
 26%|##5       | 202/781 [00:11<00:32, 17.57it/s]
 26%|##6       | 204/781 [00:11<00:32, 17.65it/s]
 26%|##6       | 206/781 [00:11<00:32, 17.84it/s]
 27%|##6       | 208/781 [00:11<00:31, 17.96it/s]
 27%|##6       | 210/781 [00:11<00:31, 18.00it/s]
 27%|##7       | 212/781 [00:11<00:31, 17.88it/s]
 27%|##7       | 214/781 [00:12<00:31, 17.97it/s]
 28%|##7       | 216/781 [00:12<00:31, 18.11it/s]
 28%|##7       | 218/781 [00:12<00:31, 17.96it/s]
 28%|##8       | 220/781 [00:12<00:31, 18.01it/s]
 28%|##8       | 222/781 [00:12<00:31, 17.94it/s]
 29%|##8       | 224/781 [00:12<00:31, 17.83it/s]
 29%|##8       | 226/781 [00:12<00:31, 17.74it/s]
 29%|##9       | 228/781 [00:12<00:31, 17.67it/s]
 29%|##9       | 230/781 [00:12<00:31, 17.72it/s]
 30%|##9       | 232/781 [00:13<00:31, 17.65it/s]
 30%|##9       | 234/781 [00:13<00:31, 17.59it/s]
 30%|###       | 236/781 [00:13<00:30, 17.69it/s]
 30%|###       | 238/781 [00:13<00:30, 17.84it/s]
 31%|###       | 240/781 [00:13<00:30, 17.83it/s]
 31%|###       | 242/781 [00:13<00:30, 17.85it/s]
 31%|###1      | 244/781 [00:13<00:30, 17.75it/s]
 31%|###1      | 246/781 [00:13<00:29, 17.91it/s]
 32%|###1      | 248/781 [00:13<00:29, 17.78it/s]
 32%|###2      | 250/781 [00:14<00:29, 17.75it/s]
 32%|###2      | 252/781 [00:14<00:29, 17.76it/s]
 33%|###2      | 254/781 [00:14<00:29, 17.90it/s]
 33%|###2      | 256/781 [00:14<00:29, 17.79it/s]
 33%|###3      | 258/781 [00:14<00:29, 17.87it/s]
 33%|###3      | 260/781 [00:14<00:28, 18.02it/s]
 34%|###3      | 262/781 [00:14<00:28, 18.13it/s]
 34%|###3      | 264/781 [00:14<00:28, 18.20it/s]
 34%|###4      | 266/781 [00:14<00:28, 18.11it/s]
 34%|###4      | 268/781 [00:15<00:28, 18.17it/s]
 35%|###4      | 270/781 [00:15<00:28, 18.17it/s]
 35%|###4      | 272/781 [00:15<00:27, 18.18it/s]
 35%|###5      | 274/781 [00:15<00:27, 18.22it/s]
 35%|###5      | 276/781 [00:15<00:28, 18.01it/s]
 36%|###5      | 278/781 [00:15<00:27, 17.98it/s]
 36%|###5      | 280/781 [00:15<00:27, 17.92it/s]
 36%|###6      | 282/781 [00:15<00:27, 17.88it/s]
 36%|###6      | 284/781 [00:15<00:28, 17.67it/s]
 37%|###6      | 286/781 [00:16<00:28, 17.64it/s]
 37%|###6      | 288/781 [00:16<00:27, 17.63it/s]
 37%|###7      | 290/781 [00:16<00:27, 17.62it/s]
 37%|###7      | 292/781 [00:16<00:27, 17.56it/s]
 38%|###7      | 294/781 [00:16<00:27, 17.67it/s]
 38%|###7      | 296/781 [00:16<00:27, 17.76it/s]
 38%|###8      | 298/781 [00:16<00:26, 17.90it/s]
 38%|###8      | 300/781 [00:16<00:26, 17.94it/s]
 39%|###8      | 302/781 [00:16<00:26, 18.02it/s]
 39%|###8      | 304/781 [00:17<00:26, 17.91it/s]
 39%|###9      | 306/781 [00:17<00:26, 17.99it/s]
 39%|###9      | 308/781 [00:17<00:26, 17.90it/s]
 40%|###9      | 310/781 [00:17<00:26, 17.83it/s]
 40%|###9      | 312/781 [00:17<00:26, 17.48it/s]
 40%|####      | 314/781 [00:17<00:26, 17.63it/s]
 40%|####      | 316/781 [00:17<00:26, 17.69it/s]
 41%|####      | 318/781 [00:17<00:26, 17.67it/s]
 41%|####      | 320/781 [00:17<00:25, 17.82it/s]
 41%|####1     | 322/781 [00:18<00:26, 17.53it/s]
 41%|####1     | 324/781 [00:18<00:25, 17.58it/s]
 42%|####1     | 326/781 [00:18<00:25, 17.66it/s]
 42%|####1     | 328/781 [00:18<00:25, 17.76it/s]
 42%|####2     | 330/781 [00:18<00:25, 17.76it/s]
 43%|####2     | 332/781 [00:18<00:25, 17.92it/s]
 43%|####2     | 334/781 [00:18<00:24, 17.88it/s]
 43%|####3     | 336/781 [00:18<00:24, 17.92it/s]
 43%|####3     | 338/781 [00:18<00:24, 17.83it/s]
 44%|####3     | 340/781 [00:19<00:24, 17.85it/s]
 44%|####3     | 342/781 [00:19<00:24, 18.00it/s]
 44%|####4     | 344/781 [00:19<00:24, 17.97it/s]
 44%|####4     | 346/781 [00:19<00:24, 17.93it/s]
 45%|####4     | 348/781 [00:19<00:24, 17.83it/s]
 45%|####4     | 350/781 [00:19<00:24, 17.78it/s]
 45%|####5     | 352/781 [00:19<00:24, 17.72it/s]
 45%|####5     | 354/781 [00:19<00:24, 17.74it/s]
 46%|####5     | 356/781 [00:19<00:23, 17.85it/s]
 46%|####5     | 358/781 [00:20<00:23, 17.96it/s]
 46%|####6     | 360/781 [00:20<00:23, 17.95it/s]
 46%|####6     | 362/781 [00:20<00:23, 17.95it/s]
 47%|####6     | 364/781 [00:20<00:23, 17.96it/s]
 47%|####6     | 366/781 [00:20<00:23, 17.93it/s]
 47%|####7     | 368/781 [00:20<00:23, 17.75it/s]
 47%|####7     | 370/781 [00:20<00:23, 17.79it/s]
 48%|####7     | 372/781 [00:20<00:22, 17.92it/s]
 48%|####7     | 374/781 [00:20<00:22, 17.82it/s]
 48%|####8     | 376/781 [00:21<00:22, 17.94it/s]
 48%|####8     | 378/781 [00:21<00:22, 17.94it/s]
 49%|####8     | 380/781 [00:21<00:22, 17.86it/s]
 49%|####8     | 382/781 [00:21<00:22, 17.83it/s]
 49%|####9     | 384/781 [00:21<00:22, 17.73it/s]
 49%|####9     | 386/781 [00:21<00:22, 17.77it/s]
 50%|####9     | 388/781 [00:21<00:22, 17.73it/s]
 50%|####9     | 390/781 [00:21<00:21, 17.79it/s]
 50%|#####     | 392/781 [00:21<00:21, 17.89it/s]
 50%|#####     | 394/781 [00:22<00:21, 17.89it/s]
 51%|#####     | 396/781 [00:22<00:21, 17.87it/s]
 51%|#####     | 398/781 [00:22<00:21, 17.98it/s]
 51%|#####1    | 400/781 [00:22<00:21, 17.97it/s]
 51%|#####1    | 402/781 [00:22<00:20, 18.08it/s]
 52%|#####1    | 404/781 [00:22<00:20, 18.17it/s]
 52%|#####1    | 406/781 [00:22<00:20, 18.13it/s]
 52%|#####2    | 408/781 [00:22<00:20, 18.12it/s]
 52%|#####2    | 410/781 [00:22<00:20, 18.12it/s]
 53%|#####2    | 412/781 [00:23<00:20, 18.20it/s]
 53%|#####3    | 414/781 [00:23<00:19, 18.39it/s]
 53%|#####3    | 416/781 [00:23<00:20, 18.16it/s]
 54%|#####3    | 418/781 [00:23<00:20, 17.95it/s]
 54%|#####3    | 420/781 [00:23<00:20, 17.83it/s]
 54%|#####4    | 422/781 [00:23<00:20, 17.62it/s]
 54%|#####4    | 424/781 [00:23<00:20, 17.73it/s]
 55%|#####4    | 426/781 [00:23<00:20, 17.69it/s]
 55%|#####4    | 428/781 [00:23<00:19, 17.79it/s]
 55%|#####5    | 430/781 [00:24<00:19, 17.81it/s]
 55%|#####5    | 432/781 [00:24<00:19, 17.92it/s]
 56%|#####5    | 434/781 [00:24<00:19, 18.04it/s]
 56%|#####5    | 436/781 [00:24<00:19, 18.12it/s]
 56%|#####6    | 438/781 [00:24<00:18, 18.14it/s]
 56%|#####6    | 440/781 [00:24<00:18, 18.03it/s]
 57%|#####6    | 442/781 [00:24<00:18, 18.01it/s]
 57%|#####6    | 444/781 [00:24<00:18, 18.01it/s]
 57%|#####7    | 446/781 [00:24<00:18, 17.97it/s]
 57%|#####7    | 448/781 [00:25<00:18, 18.07it/s]
 58%|#####7    | 450/781 [00:25<00:18, 18.15it/s]
 58%|#####7    | 452/781 [00:25<00:18, 17.95it/s]
 58%|#####8    | 454/781 [00:25<00:18, 18.07it/s]
 58%|#####8    | 456/781 [00:25<00:18, 17.91it/s]
 59%|#####8    | 458/781 [00:25<00:18, 17.90it/s]
 59%|#####8    | 460/781 [00:25<00:18, 17.77it/s]
 59%|#####9    | 462/781 [00:25<00:17, 17.94it/s]
 59%|#####9    | 464/781 [00:25<00:17, 18.06it/s]
 60%|#####9    | 466/781 [00:26<00:17, 18.11it/s]
 60%|#####9    | 468/781 [00:26<00:17, 18.12it/s]
 60%|######    | 470/781 [00:26<00:17, 18.05it/s]
 60%|######    | 472/781 [00:26<00:17, 18.12it/s]
 61%|######    | 474/781 [00:26<00:16, 18.07it/s]
 61%|######    | 476/781 [00:26<00:17, 17.88it/s]
 61%|######1   | 478/781 [00:26<00:16, 17.87it/s]
 61%|######1   | 480/781 [00:26<00:16, 17.84it/s]
 62%|######1   | 482/781 [00:26<00:16, 17.80it/s]
 62%|######1   | 484/781 [00:27<00:16, 17.70it/s]
 62%|######2   | 486/781 [00:27<00:16, 17.61it/s]
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