diff --git "a/Embedding.mlmodelc/model.mil" "b/Embedding.mlmodelc/model.mil" --- "a/Embedding.mlmodelc/model.mil" +++ "b/Embedding.mlmodelc/model.mil" @@ -1,524 +1,429 @@ program(1.0) -[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}})] +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.8.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})] { - func main(tensor audio_and_weights) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"audio_and_weights", [1, 1, 1, 160589]}}), ("RangeDims", {{"audio_and_weights", [[1, 32], [1, 1], [1, 1], [160589, 160589]]}})))] { - tensor _interp_right_weight = const()[name = tensor("_interp_right_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; - tensor _interp_left_weight = const()[name = tensor("_interp_left_weight"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(640)))]; - tensor _fbank_mel_weight_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("_fbank_mel_weight_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1216))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22080))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21888)))]; - tensor _fbank_dft_imag_weight_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("_fbank_dft_imag_weight_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22464))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154496))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154112)))]; - tensor _fbank_dft_real_weight_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("_fbank_dft_real_weight_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(155648))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(287296))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154112)))]; - tensor _fbank_window = const()[name = tensor("_fbank_window"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(288448)))]; - tensor _fbank_eps = const()[name = tensor("_fbank_eps"), val = tensor(0x1.b7cdfep-34)]; - tensor _fbank_frame_kernel_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("_fbank_frame_kernel_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290112))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(450688))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(450176)))]; - tensor resnet_seg_1_bias = const()[name = tensor("resnet_seg_1_bias"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(452352)))]; - tensor resnet_seg_1_weight_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("resnet_seg_1_weight_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(453440))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764544))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor var_24_begin_0 = const()[name = tensor("op_24_begin_0"), val = tensor([0, 0, 0, 0])]; - tensor var_24_end_0 = const()[name = tensor("op_24_end_0"), val = tensor([0, 1, 1, 160000])]; - tensor var_24_end_mask_0 = const()[name = tensor("op_24_end_mask_0"), val = tensor([true, true, true, false])]; - tensor var_24 = slice_by_index(begin = var_24_begin_0, end = var_24_end_0, end_mask = var_24_end_mask_0, x = audio_and_weights)[name = tensor("op_24")]; - tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([-1, 1, 160000])]; - tensor waveforms_1 = reshape(shape = concat_0x, x = var_24)[name = tensor("waveforms_1")]; - tensor var_33_begin_0 = const()[name = tensor("op_33_begin_0"), val = tensor([0, 0, 0, 160000])]; - tensor var_33_end_0 = const()[name = tensor("op_33_end_0"), val = tensor([0, 1, 1, 160589])]; - tensor var_33_end_mask_0 = const()[name = tensor("op_33_end_mask_0"), val = tensor([true, true, true, true])]; - tensor var_33 = slice_by_index(begin = var_33_begin_0, end = var_33_end_0, end_mask = var_33_end_mask_0, x = audio_and_weights)[name = tensor("op_33")]; - tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([-1, 589])]; - tensor weights_1 = reshape(shape = concat_1x, x = var_33)[name = tensor("weights_1")]; - tensor var_36_promoted = const()[name = tensor("op_36_promoted"), val = tensor(0x1p+15)]; - tensor waveforms_3 = mul(x = waveforms_1, y = var_36_promoted)[name = tensor("waveforms_3")]; - tensor frames_1_pad_type_0 = const()[name = tensor("frames_1_pad_type_0"), val = tensor("valid")]; - tensor frames_1_strides_0 = const()[name = tensor("frames_1_strides_0"), val = tensor([160])]; - tensor frames_1_pad_0 = const()[name = tensor("frames_1_pad_0"), val = tensor([0, 0])]; - tensor frames_1_dilations_0 = const()[name = tensor("frames_1_dilations_0"), val = tensor([1])]; - tensor frames_1_groups_0 = const()[name = tensor("frames_1_groups_0"), val = tensor(1)]; - tensor frames_1 = conv(dilations = frames_1_dilations_0, groups = frames_1_groups_0, pad = frames_1_pad_0, pad_type = frames_1_pad_type_0, strides = frames_1_strides_0, weight = _fbank_frame_kernel_quantized, x = waveforms_3)[name = tensor("frames_1")]; - tensor frames_3_perm_0 = const()[name = tensor("frames_3_perm_0"), val = tensor([0, 2, 1])]; - tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([-1, 400])]; - tensor frames_3 = transpose(perm = frames_3_perm_0, x = frames_1)[name = tensor("transpose_1")]; - tensor frames_5 = reshape(shape = concat_2x, x = frames_3)[name = tensor("frames_5")]; - tensor var_86_axes_0 = const()[name = tensor("op_86_axes_0"), val = tensor([1])]; - tensor var_86_keep_dims_0 = const()[name = tensor("op_86_keep_dims_0"), val = tensor(true)]; - tensor var_86 = reduce_mean(axes = var_86_axes_0, keep_dims = var_86_keep_dims_0, x = frames_5)[name = tensor("op_86")]; - tensor frames_7 = sub(x = frames_5, y = var_86)[name = tensor("frames_7")]; - tensor input_1_axes_0 = const()[name = tensor("input_1_axes_0"), val = tensor([1])]; - tensor input_1 = expand_dims(axes = input_1_axes_0, x = frames_7)[name = tensor("input_1")]; - tensor const_0 = const()[name = tensor("const_0"), val = tensor(0x0p+0)]; - tensor var_90_pad_0 = const()[name = tensor("op_90_pad_0"), val = tensor([0, 0, 0, 0, 1, 0])]; - tensor var_90_mode_0 = const()[name = tensor("op_90_mode_0"), val = tensor("replicate")]; - tensor var_90 = pad(constant_val = const_0, mode = var_90_mode_0, pad = var_90_pad_0, x = input_1)[name = tensor("op_90")]; - tensor padded_axes_0 = const()[name = tensor("padded_axes_0"), val = tensor([1])]; - tensor padded = squeeze(axes = padded_axes_0, x = var_90)[name = tensor("padded")]; - tensor var_93_begin_0 = const()[name = tensor("op_93_begin_0"), val = tensor([0, 0])]; - tensor var_93_end_0 = const()[name = tensor("op_93_end_0"), val = tensor([0, 400])]; - tensor var_93_end_mask_0 = const()[name = tensor("op_93_end_mask_0"), val = tensor([true, false])]; - tensor var_93 = slice_by_index(begin = var_93_begin_0, end = var_93_end_0, end_mask = var_93_end_mask_0, x = padded)[name = tensor("op_93")]; - tensor var_94 = const()[name = tensor("op_94"), val = tensor(0x1.f0a3d8p-1)]; - tensor var_95 = mul(x = var_93, y = var_94)[name = tensor("op_95")]; - tensor frames_9 = sub(x = frames_7, y = var_95)[name = tensor("frames_9")]; - tensor frames_11 = mul(x = frames_9, y = _fbank_window)[name = tensor("frames_11")]; - tensor input_3_axes_0 = const()[name = tensor("input_3_axes_0"), val = tensor([1])]; - tensor input_3 = expand_dims(axes = input_3_axes_0, x = frames_11)[name = tensor("input_3")]; - tensor const_1 = const()[name = tensor("const_1"), val = tensor(0x0p+0)]; - tensor var_100_pad_0 = const()[name = tensor("op_100_pad_0"), val = tensor([0, 0, 0, 0, 0, 112])]; - tensor var_100_mode_0 = const()[name = tensor("op_100_mode_0"), val = tensor("constant")]; - tensor var_100 = pad(constant_val = const_1, mode = var_100_mode_0, pad = var_100_pad_0, x = input_3)[name = tensor("op_100")]; - tensor var_107_pad_type_0 = const()[name = tensor("op_107_pad_type_0"), val = tensor("valid")]; - tensor var_107_strides_0 = const()[name = tensor("op_107_strides_0"), val = tensor([1])]; - tensor var_107_pad_0 = const()[name = tensor("op_107_pad_0"), val = tensor([0, 0])]; - tensor var_107_dilations_0 = const()[name = tensor("op_107_dilations_0"), val = tensor([1])]; - tensor var_107_groups_0 = const()[name = tensor("op_107_groups_0"), val = tensor(1)]; - tensor var_107 = conv(dilations = var_107_dilations_0, groups = var_107_groups_0, pad = var_107_pad_0, pad_type = var_107_pad_type_0, strides = var_107_strides_0, weight = _fbank_dft_real_weight_quantized, x = var_100)[name = tensor("op_107")]; - tensor real_axes_0 = const()[name = tensor("real_axes_0"), val = tensor([-1])]; - tensor real = squeeze(axes = real_axes_0, x = var_107)[name = tensor("real")]; - tensor var_113_pad_type_0 = const()[name = tensor("op_113_pad_type_0"), val = tensor("valid")]; - tensor var_113_strides_0 = const()[name = tensor("op_113_strides_0"), val = tensor([1])]; - tensor var_113_pad_0 = const()[name = tensor("op_113_pad_0"), val = tensor([0, 0])]; - tensor var_113_dilations_0 = const()[name = tensor("op_113_dilations_0"), val = tensor([1])]; - tensor var_113_groups_0 = const()[name = tensor("op_113_groups_0"), val = tensor(1)]; - tensor var_113 = conv(dilations = var_113_dilations_0, groups = var_113_groups_0, pad = var_113_pad_0, pad_type = var_113_pad_type_0, strides = var_113_strides_0, weight = _fbank_dft_imag_weight_quantized, x = var_100)[name = tensor("op_113")]; - tensor imag_axes_0 = const()[name = tensor("imag_axes_0"), val = tensor([-1])]; - tensor imag = squeeze(axes = imag_axes_0, x = var_113)[name = tensor("imag")]; - tensor var_55_promoted = const()[name = tensor("op_55_promoted"), val = tensor(0x1p+1)]; - tensor var_115 = pow(x = real, y = var_55_promoted)[name = tensor("op_115")]; - tensor var_55_promoted_1 = const()[name = tensor("op_55_promoted_1"), val = tensor(0x1p+1)]; - tensor var_116 = pow(x = imag, y = var_55_promoted_1)[name = tensor("op_116")]; - tensor power = add(x = var_115, y = var_116)[name = tensor("power")]; - tensor var_118_axes_0 = const()[name = tensor("op_118_axes_0"), val = tensor([-1])]; - tensor var_118 = expand_dims(axes = var_118_axes_0, x = power)[name = tensor("op_118")]; - tensor var_123_pad_type_0 = const()[name = tensor("op_123_pad_type_0"), val = tensor("valid")]; - tensor var_123_strides_0 = const()[name = tensor("op_123_strides_0"), val = tensor([1])]; - tensor var_123_pad_0 = const()[name = tensor("op_123_pad_0"), val = tensor([0, 0])]; - tensor var_123_dilations_0 = const()[name = tensor("op_123_dilations_0"), val = tensor([1])]; - tensor var_123_groups_0 = const()[name = tensor("op_123_groups_0"), val = tensor(1)]; - tensor var_123 = conv(dilations = var_123_dilations_0, groups = var_123_groups_0, pad = var_123_pad_0, pad_type = var_123_pad_type_0, strides = var_123_strides_0, weight = _fbank_mel_weight_quantized, x = var_118)[name = tensor("op_123")]; - tensor mel_1_axes_0 = const()[name = tensor("mel_1_axes_0"), val = tensor([-1])]; - tensor mel_1 = squeeze(axes = mel_1_axes_0, x = var_123)[name = tensor("mel_1")]; - tensor const_2 = const()[name = tensor("const_2"), val = tensor(0x1.fffffep+127)]; - tensor clip_0 = clip(alpha = _fbank_eps, beta = const_2, x = mel_1)[name = tensor("clip_0")]; - tensor mel_epsilon_0 = const()[name = tensor("mel_epsilon_0"), val = tensor(0x1p-149)]; - tensor mel = log(epsilon = mel_epsilon_0, x = clip_0)[name = tensor("mel")]; - tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([-1, 998, 80])]; - tensor var_128 = reshape(shape = concat_3x, x = mel)[name = tensor("op_128")]; - tensor centered_axes_0 = const()[name = tensor("centered_axes_0"), val = tensor([1])]; - tensor centered_keep_dims_0 = const()[name = tensor("centered_keep_dims_0"), val = tensor(true)]; - tensor centered = reduce_mean(axes = centered_axes_0, keep_dims = centered_keep_dims_0, x = var_128)[name = tensor("centered")]; - tensor features_1 = sub(x = var_128, y = centered)[name = tensor("features_1")]; - tensor var_147 = const()[name = tensor("op_147"), val = tensor([0, 2, 1])]; - tensor input_5_axes_0 = const()[name = tensor("input_5_axes_0"), val = tensor([1])]; - tensor var_148 = transpose(perm = var_147, x = features_1)[name = tensor("transpose_0")]; - tensor input_5 = expand_dims(axes = input_5_axes_0, x = var_148)[name = tensor("input_5")]; - tensor left_batch_dims_0 = const()[name = tensor("left_batch_dims_0"), val = tensor(0)]; - tensor left_validate_indices_0 = const()[name = tensor("left_validate_indices_0"), val = tensor(false)]; - tensor select_0 = const()[name = tensor("select_0"), val = tensor([0, 4, 9, 14, 18, 23, 28, 33, 37, 42, 47, 52, 56, 61, 66, 71, 75, 80, 85, 90, 94, 99, 104, 109, 113, 118, 123, 128, 132, 137, 142, 147, 151, 156, 161, 165, 170, 175, 180, 184, 189, 194, 199, 203, 208, 213, 218, 222, 227, 232, 237, 241, 246, 251, 256, 260, 265, 270, 275, 279, 284, 289, 294, 298, 303, 308, 312, 317, 322, 327, 331, 336, 341, 346, 350, 355, 360, 365, 369, 374, 379, 384, 388, 393, 398, 403, 407, 412, 417, 422, 426, 431, 436, 441, 445, 450, 455, 459, 464, 469, 474, 478, 483, 488, 493, 497, 502, 507, 512, 516, 521, 526, 531, 535, 540, 545, 550, 554, 559, 564, 569, 573, 578, 583, 588])]; - tensor left_axis_0 = const()[name = tensor("left_axis_0"), val = tensor(1)]; - tensor left = gather(axis = left_axis_0, batch_dims = left_batch_dims_0, indices = select_0, validate_indices = left_validate_indices_0, x = weights_1)[name = tensor("left")]; - tensor right_batch_dims_0 = const()[name = tensor("right_batch_dims_0"), val = tensor(0)]; - tensor right_validate_indices_0 = const()[name = tensor("right_validate_indices_0"), val = tensor(false)]; - tensor select_1 = const()[name = tensor("select_1"), val = tensor([1, 5, 10, 15, 19, 24, 29, 34, 38, 43, 48, 53, 57, 62, 67, 72, 76, 81, 86, 91, 95, 100, 105, 110, 114, 119, 124, 129, 133, 138, 143, 148, 152, 157, 162, 166, 171, 176, 181, 185, 190, 195, 200, 204, 209, 214, 219, 223, 228, 233, 238, 242, 247, 252, 257, 261, 266, 271, 276, 280, 285, 290, 295, 299, 304, 309, 313, 318, 323, 328, 332, 337, 342, 347, 351, 356, 361, 366, 370, 375, 380, 385, 389, 394, 399, 404, 408, 413, 418, 423, 427, 432, 437, 442, 446, 451, 456, 460, 465, 470, 475, 479, 484, 489, 494, 498, 503, 508, 513, 517, 522, 527, 532, 536, 541, 546, 551, 555, 560, 565, 570, 574, 579, 584, 588])]; - tensor right_axis_0 = const()[name = tensor("right_axis_0"), val = tensor(1)]; - tensor right = gather(axis = right_axis_0, batch_dims = right_batch_dims_0, indices = select_1, validate_indices = right_validate_indices_0, x = weights_1)[name = tensor("right")]; - tensor var_171 = mul(x = left, y = _interp_left_weight)[name = tensor("op_171")]; - tensor var_172 = mul(x = right, y = _interp_right_weight)[name = tensor("op_172")]; - tensor weights_3 = add(x = var_171, y = var_172)[name = tensor("weights_3")]; - tensor var_176 = const()[name = tensor("op_176"), val = tensor(-1)]; - tensor var_177 = const()[name = tensor("op_177"), val = tensor(0x1.197998p-40)]; + func main(tensor fbank_features, tensor weights) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, list, ?>>>>((("DefaultShapes", {{"fbank_features", [1, 1, 80, 998]}, {"weights", [1, 589]}}), ("RangeDims", {{"fbank_features", [[1, 32], [1, 1], [80, 80], [998, 998]]}, {"weights", [[1, 32], [589, 589]]}})))] { + tensor weights_1d_axes_0 = const()[name = tensor("weights_1d_axes_0"), val = tensor([1])]; + tensor weights_to_fp16_dtype_0 = const()[name = tensor("weights_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor weights_to_fp16 = cast(dtype = weights_to_fp16_dtype_0, x = weights)[name = tensor("cast_14")]; + tensor weights_1d_cast_fp16 = expand_dims(axes = weights_1d_axes_0, x = weights_to_fp16)[name = tensor("weights_1d_cast_fp16")]; + tensor interpolated_pad_type_0 = const()[name = tensor("interpolated_pad_type_0"), val = tensor("valid")]; + tensor interpolated_strides_0 = const()[name = tensor("interpolated_strides_0"), val = tensor([1])]; + tensor interpolated_pad_0 = const()[name = tensor("interpolated_pad_0"), val = tensor([0, 0])]; + tensor interpolated_dilations_0 = const()[name = tensor("interpolated_dilations_0"), val = tensor([1])]; + tensor interpolated_groups_0 = const()[name = tensor("interpolated_groups_0"), val = tensor(1)]; + tensor const_0_to_fp16 = const()[name = tensor("const_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor interpolated_cast_fp16 = conv(dilations = interpolated_dilations_0, groups = interpolated_groups_0, pad = interpolated_pad_0, pad_type = interpolated_pad_type_0, strides = interpolated_strides_0, weight = const_0_to_fp16, x = weights_1d_cast_fp16)[name = tensor("interpolated_cast_fp16")]; + tensor weights_3_axes_0 = const()[name = tensor("weights_3_axes_0"), val = tensor([-1])]; + tensor weights_3_cast_fp16 = squeeze(axes = weights_3_axes_0, x = interpolated_cast_fp16)[name = tensor("weights_3_cast_fp16")]; + tensor var_33 = const()[name = tensor("op_33"), val = tensor(-1)]; + tensor input_1_pad_type_0 = const()[name = tensor("input_1_pad_type_0"), val = tensor("custom")]; + tensor input_1_pad_0 = const()[name = tensor("input_1_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_1_strides_0 = const()[name = tensor("input_1_strides_0"), val = tensor([1, 1])]; + tensor input_1_dilations_0 = const()[name = tensor("input_1_dilations_0"), val = tensor([1, 1])]; + tensor input_1_groups_0 = const()[name = tensor("input_1_groups_0"), val = tensor(1)]; + tensor fbank_features_to_fp16_dtype_0 = const()[name = tensor("fbank_features_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor const_3_to_fp16 = const()[name = tensor("const_3_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(147392)))]; + tensor const_4_to_fp16 = const()[name = tensor("const_4_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148032)))]; + tensor fbank_features_to_fp16 = cast(dtype = fbank_features_to_fp16_dtype_0, x = fbank_features)[name = tensor("cast_13")]; + tensor input_3_cast_fp16 = conv(bias = const_4_to_fp16, dilations = input_1_dilations_0, groups = input_1_groups_0, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = input_1_strides_0, weight = const_3_to_fp16, x = fbank_features_to_fp16)[name = tensor("input_3_cast_fp16")]; + tensor input_5_cast_fp16 = relu(x = input_3_cast_fp16)[name = tensor("input_5_cast_fp16")]; tensor input_7_pad_type_0 = const()[name = tensor("input_7_pad_type_0"), val = tensor("custom")]; tensor input_7_pad_0 = const()[name = tensor("input_7_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_7_strides_0 = const()[name = tensor("input_7_strides_0"), val = tensor([1, 1])]; tensor input_7_dilations_0 = const()[name = tensor("input_7_dilations_0"), val = tensor([1, 1])]; tensor input_7_groups_0 = const()[name = tensor("input_7_groups_0"), val = tensor(1)]; - tensor const_5 = const()[name = tensor("const_5"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1765632)))]; - tensor const_6 = const()[name = tensor("const_6"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1766848)))]; - tensor input_9 = conv(bias = const_6, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_5, x = input_5)[name = tensor("input_9")]; - tensor input_11 = relu(x = input_9)[name = tensor("input_11")]; + tensor const_5_to_fp16 = const()[name = tensor("const_5_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148160)))]; + tensor const_6_to_fp16 = const()[name = tensor("const_6_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166656)))]; + tensor input_9_cast_fp16 = conv(bias = const_6_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_5_to_fp16, x = input_5_cast_fp16)[name = tensor("input_9_cast_fp16")]; + tensor input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = tensor("input_11_cast_fp16")]; tensor input_13_pad_type_0 = const()[name = tensor("input_13_pad_type_0"), val = tensor("custom")]; tensor input_13_pad_0 = const()[name = tensor("input_13_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_13_strides_0 = const()[name = tensor("input_13_strides_0"), val = tensor([1, 1])]; tensor input_13_dilations_0 = const()[name = tensor("input_13_dilations_0"), val = tensor([1, 1])]; tensor input_13_groups_0 = const()[name = tensor("input_13_groups_0"), val = tensor(1)]; - tensor const_7_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_7_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1767040))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1776448))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1776320)))]; - tensor const_8 = const()[name = tensor("const_8"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1776640)))]; - tensor input_15 = conv(bias = const_8, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_7_quantized, x = input_11)[name = tensor("input_15")]; - tensor input_17 = relu(x = input_15)[name = tensor("input_17")]; + tensor const_7_to_fp16 = const()[name = tensor("const_7_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166784)))]; + tensor const_8_to_fp16 = const()[name = tensor("const_8_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185280)))]; + tensor out_1_cast_fp16 = conv(bias = const_8_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_7_to_fp16, x = input_11_cast_fp16)[name = tensor("out_1_cast_fp16")]; + tensor input_15_cast_fp16 = add(x = out_1_cast_fp16, y = input_5_cast_fp16)[name = tensor("input_15_cast_fp16")]; + tensor input_17_cast_fp16 = relu(x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; tensor input_19_pad_type_0 = const()[name = tensor("input_19_pad_type_0"), val = tensor("custom")]; tensor input_19_pad_0 = const()[name = tensor("input_19_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_19_strides_0 = const()[name = tensor("input_19_strides_0"), val = tensor([1, 1])]; tensor input_19_dilations_0 = const()[name = tensor("input_19_dilations_0"), val = tensor([1, 1])]; tensor input_19_groups_0 = const()[name = tensor("input_19_groups_0"), val = tensor(1)]; - tensor const_9_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_9_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1776832))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1786240))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1786112)))]; - tensor const_10 = const()[name = tensor("const_10"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1786432)))]; - tensor out_1 = conv(bias = const_10, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = const_9_quantized, x = input_17)[name = tensor("out_1")]; - tensor input_21 = add(x = out_1, y = input_11)[name = tensor("input_21")]; - tensor input_23 = relu(x = input_21)[name = tensor("input_23")]; + tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(185408)))]; + tensor const_10_to_fp16 = const()[name = tensor("const_10_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203904)))]; + tensor input_21_cast_fp16 = conv(bias = const_10_to_fp16, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = const_9_to_fp16, x = input_17_cast_fp16)[name = tensor("input_21_cast_fp16")]; + tensor input_23_cast_fp16 = relu(x = input_21_cast_fp16)[name = tensor("input_23_cast_fp16")]; tensor input_25_pad_type_0 = const()[name = tensor("input_25_pad_type_0"), val = tensor("custom")]; tensor input_25_pad_0 = const()[name = tensor("input_25_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_25_strides_0 = const()[name = tensor("input_25_strides_0"), val = tensor([1, 1])]; tensor input_25_dilations_0 = const()[name = tensor("input_25_dilations_0"), val = tensor([1, 1])]; tensor input_25_groups_0 = const()[name = tensor("input_25_groups_0"), val = tensor(1)]; - tensor const_11_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_11_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1786624))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1796032))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1795904)))]; - tensor const_12 = const()[name = tensor("const_12"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1796224)))]; - tensor input_27 = conv(bias = const_12, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = const_11_quantized, x = input_23)[name = tensor("input_27")]; - tensor input_29 = relu(x = input_27)[name = tensor("input_29")]; + tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204032)))]; + tensor const_12_to_fp16 = const()[name = tensor("const_12_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222528)))]; + tensor out_3_cast_fp16 = conv(bias = const_12_to_fp16, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = const_11_to_fp16, x = input_23_cast_fp16)[name = tensor("out_3_cast_fp16")]; + tensor input_27_cast_fp16 = add(x = out_3_cast_fp16, y = input_17_cast_fp16)[name = tensor("input_27_cast_fp16")]; + tensor input_29_cast_fp16 = relu(x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; tensor input_31_pad_type_0 = const()[name = tensor("input_31_pad_type_0"), val = tensor("custom")]; tensor input_31_pad_0 = const()[name = tensor("input_31_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_31_strides_0 = const()[name = tensor("input_31_strides_0"), val = tensor([1, 1])]; tensor input_31_dilations_0 = const()[name = tensor("input_31_dilations_0"), val = tensor([1, 1])]; tensor input_31_groups_0 = const()[name = tensor("input_31_groups_0"), val = tensor(1)]; - tensor const_13_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_13_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1796416))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1805824))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1805696)))]; - tensor const_14 = const()[name = tensor("const_14"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1806016)))]; - tensor out_3 = conv(bias = const_14, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = const_13_quantized, x = input_29)[name = tensor("out_3")]; - tensor input_33 = add(x = out_3, y = input_23)[name = tensor("input_33")]; - tensor input_35 = relu(x = input_33)[name = tensor("input_35")]; + tensor const_13_to_fp16 = const()[name = tensor("const_13_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(222656)))]; + tensor const_14_to_fp16 = const()[name = tensor("const_14_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241152)))]; + tensor input_33_cast_fp16 = conv(bias = const_14_to_fp16, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = const_13_to_fp16, x = input_29_cast_fp16)[name = tensor("input_33_cast_fp16")]; + tensor input_35_cast_fp16 = relu(x = input_33_cast_fp16)[name = tensor("input_35_cast_fp16")]; tensor input_37_pad_type_0 = const()[name = tensor("input_37_pad_type_0"), val = tensor("custom")]; tensor input_37_pad_0 = const()[name = tensor("input_37_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_37_strides_0 = const()[name = tensor("input_37_strides_0"), val = tensor([1, 1])]; tensor input_37_dilations_0 = const()[name = tensor("input_37_dilations_0"), val = tensor([1, 1])]; tensor input_37_groups_0 = const()[name = tensor("input_37_groups_0"), val = tensor(1)]; - tensor const_15_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_15_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1806208))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1815616))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1815488)))]; - tensor const_16 = const()[name = tensor("const_16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1815808)))]; - tensor input_39 = conv(bias = const_16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = const_15_quantized, x = input_35)[name = tensor("input_39")]; - tensor input_41 = relu(x = input_39)[name = tensor("input_41")]; + tensor const_15_to_fp16 = const()[name = tensor("const_15_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241280)))]; + tensor const_16_to_fp16 = const()[name = tensor("const_16_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259776)))]; + tensor out_5_cast_fp16 = conv(bias = const_16_to_fp16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = const_15_to_fp16, x = input_35_cast_fp16)[name = tensor("out_5_cast_fp16")]; + tensor input_39_cast_fp16 = add(x = out_5_cast_fp16, y = input_29_cast_fp16)[name = tensor("input_39_cast_fp16")]; + tensor input_41_cast_fp16 = relu(x = input_39_cast_fp16)[name = tensor("input_41_cast_fp16")]; tensor input_43_pad_type_0 = const()[name = tensor("input_43_pad_type_0"), val = tensor("custom")]; tensor input_43_pad_0 = const()[name = tensor("input_43_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_43_strides_0 = const()[name = tensor("input_43_strides_0"), val = tensor([1, 1])]; + tensor input_43_strides_0 = const()[name = tensor("input_43_strides_0"), val = tensor([2, 2])]; tensor input_43_dilations_0 = const()[name = tensor("input_43_dilations_0"), val = tensor([1, 1])]; tensor input_43_groups_0 = const()[name = tensor("input_43_groups_0"), val = tensor(1)]; - tensor const_17_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_17_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1816000))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1825408))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1825280)))]; - tensor const_18 = const()[name = tensor("const_18"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1825600)))]; - tensor out_5 = conv(bias = const_18, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_17_quantized, x = input_41)[name = tensor("out_5")]; - tensor input_45 = add(x = out_5, y = input_35)[name = tensor("input_45")]; - tensor input_47 = relu(x = input_45)[name = tensor("input_47")]; + tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259904)))]; + tensor const_18_to_fp16 = const()[name = tensor("const_18_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(296832)))]; + tensor input_45_cast_fp16 = conv(bias = const_18_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_17_to_fp16, x = input_41_cast_fp16)[name = tensor("input_45_cast_fp16")]; + tensor input_47_cast_fp16 = relu(x = input_45_cast_fp16)[name = tensor("input_47_cast_fp16")]; tensor input_49_pad_type_0 = const()[name = tensor("input_49_pad_type_0"), val = tensor("custom")]; tensor input_49_pad_0 = const()[name = tensor("input_49_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_49_strides_0 = const()[name = tensor("input_49_strides_0"), val = tensor([2, 2])]; + tensor input_49_strides_0 = const()[name = tensor("input_49_strides_0"), val = tensor([1, 1])]; tensor input_49_dilations_0 = const()[name = tensor("input_49_dilations_0"), val = tensor([1, 1])]; tensor input_49_groups_0 = const()[name = tensor("input_49_groups_0"), val = tensor(1)]; - tensor const_19_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_19_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1825792))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1844416))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1844288)))]; - tensor const_20 = const()[name = tensor("const_20"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1844736)))]; - tensor input_51 = conv(bias = const_20, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_19_quantized, x = input_47)[name = tensor("input_51")]; - tensor input_53 = relu(x = input_51)[name = tensor("input_53")]; - tensor input_55_pad_type_0 = const()[name = tensor("input_55_pad_type_0"), val = tensor("custom")]; - tensor input_55_pad_0 = const()[name = tensor("input_55_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_55_strides_0 = const()[name = tensor("input_55_strides_0"), val = tensor([1, 1])]; - tensor input_55_dilations_0 = const()[name = tensor("input_55_dilations_0"), val = tensor([1, 1])]; - tensor input_55_groups_0 = const()[name = tensor("input_55_groups_0"), val = tensor(1)]; - tensor const_21_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_21_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1845056))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1882112))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1881984)))]; - tensor const_22 = const()[name = tensor("const_22"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1882432)))]; - tensor out_7 = conv(bias = const_22, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_21_quantized, x = input_53)[name = tensor("out_7")]; - tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("valid")]; - tensor input_57_strides_0 = const()[name = tensor("input_57_strides_0"), val = tensor([2, 2])]; - tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor const_19_to_fp16 = const()[name = tensor("const_19_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297024)))]; + tensor const_20_to_fp16 = const()[name = tensor("const_20_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(370816)))]; + tensor out_7_cast_fp16 = conv(bias = const_20_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_19_to_fp16, x = input_47_cast_fp16)[name = tensor("out_7_cast_fp16")]; + tensor input_51_pad_type_0 = const()[name = tensor("input_51_pad_type_0"), val = tensor("valid")]; + tensor input_51_strides_0 = const()[name = tensor("input_51_strides_0"), val = tensor([2, 2])]; + tensor input_51_pad_0 = const()[name = tensor("input_51_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_51_dilations_0 = const()[name = tensor("input_51_dilations_0"), val = tensor([1, 1])]; + tensor input_51_groups_0 = const()[name = tensor("input_51_groups_0"), val = tensor(1)]; + tensor const_21_to_fp16 = const()[name = tensor("const_21_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(371008)))]; + tensor const_22_to_fp16 = const()[name = tensor("const_22_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375168)))]; + tensor var_196_cast_fp16 = conv(bias = const_22_to_fp16, dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = const_21_to_fp16, x = input_41_cast_fp16)[name = tensor("op_196_cast_fp16")]; + tensor input_53_cast_fp16 = add(x = out_7_cast_fp16, y = var_196_cast_fp16)[name = tensor("input_53_cast_fp16")]; + tensor input_55_cast_fp16 = relu(x = input_53_cast_fp16)[name = tensor("input_55_cast_fp16")]; + tensor input_57_pad_type_0 = const()[name = tensor("input_57_pad_type_0"), val = tensor("custom")]; + tensor input_57_pad_0 = const()[name = tensor("input_57_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_57_strides_0 = const()[name = tensor("input_57_strides_0"), val = tensor([1, 1])]; tensor input_57_dilations_0 = const()[name = tensor("input_57_dilations_0"), val = tensor([1, 1])]; tensor input_57_groups_0 = const()[name = tensor("input_57_groups_0"), val = tensor(1)]; - tensor const_23_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_23_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1882752))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1884992))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1884864)))]; - tensor const_24 = const()[name = tensor("const_24"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1885312)))]; - tensor var_339 = conv(bias = const_24, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_23_quantized, x = input_47)[name = tensor("op_339")]; - tensor input_59 = add(x = out_7, y = var_339)[name = tensor("input_59")]; - tensor input_61 = relu(x = input_59)[name = tensor("input_61")]; + tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(375360)))]; + tensor const_24_to_fp16 = const()[name = tensor("const_24_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449152)))]; + tensor input_59_cast_fp16 = conv(bias = const_24_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_23_to_fp16, x = input_55_cast_fp16)[name = tensor("input_59_cast_fp16")]; + tensor input_61_cast_fp16 = relu(x = input_59_cast_fp16)[name = tensor("input_61_cast_fp16")]; tensor input_63_pad_type_0 = const()[name = tensor("input_63_pad_type_0"), val = tensor("custom")]; tensor input_63_pad_0 = const()[name = tensor("input_63_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_63_strides_0 = const()[name = tensor("input_63_strides_0"), val = tensor([1, 1])]; tensor input_63_dilations_0 = const()[name = tensor("input_63_dilations_0"), val = tensor([1, 1])]; tensor input_63_groups_0 = const()[name = tensor("input_63_groups_0"), val = tensor(1)]; - tensor const_25_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_25_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1885632))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1922688))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1922560)))]; - tensor const_26 = const()[name = tensor("const_26"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1923008)))]; - tensor input_65 = conv(bias = const_26, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = const_25_quantized, x = input_61)[name = tensor("input_65")]; - tensor input_67 = relu(x = input_65)[name = tensor("input_67")]; + tensor const_25_to_fp16 = const()[name = tensor("const_25_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(449344)))]; + tensor const_26_to_fp16 = const()[name = tensor("const_26_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(523136)))]; + tensor out_9_cast_fp16 = conv(bias = const_26_to_fp16, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = const_25_to_fp16, x = input_61_cast_fp16)[name = tensor("out_9_cast_fp16")]; + tensor input_65_cast_fp16 = add(x = out_9_cast_fp16, y = input_55_cast_fp16)[name = tensor("input_65_cast_fp16")]; + tensor input_67_cast_fp16 = relu(x = input_65_cast_fp16)[name = tensor("input_67_cast_fp16")]; tensor input_69_pad_type_0 = const()[name = tensor("input_69_pad_type_0"), val = tensor("custom")]; tensor input_69_pad_0 = const()[name = tensor("input_69_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_69_strides_0 = const()[name = tensor("input_69_strides_0"), val = tensor([1, 1])]; tensor input_69_dilations_0 = const()[name = tensor("input_69_dilations_0"), val = tensor([1, 1])]; tensor input_69_groups_0 = const()[name = tensor("input_69_groups_0"), val = tensor(1)]; - tensor const_27_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_27_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1923328))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1960384))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1960256)))]; - tensor const_28 = const()[name = tensor("const_28"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1960704)))]; - tensor out_9 = conv(bias = const_28, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = const_27_quantized, x = input_67)[name = tensor("out_9")]; - tensor input_71 = add(x = out_9, y = input_61)[name = tensor("input_71")]; - tensor input_73 = relu(x = input_71)[name = tensor("input_73")]; + tensor const_27_to_fp16 = const()[name = tensor("const_27_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(523328)))]; + tensor const_28_to_fp16 = const()[name = tensor("const_28_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597120)))]; + tensor input_71_cast_fp16 = conv(bias = const_28_to_fp16, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = const_27_to_fp16, x = input_67_cast_fp16)[name = tensor("input_71_cast_fp16")]; + tensor input_73_cast_fp16 = relu(x = input_71_cast_fp16)[name = tensor("input_73_cast_fp16")]; tensor input_75_pad_type_0 = const()[name = tensor("input_75_pad_type_0"), val = tensor("custom")]; tensor input_75_pad_0 = const()[name = tensor("input_75_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_75_strides_0 = const()[name = tensor("input_75_strides_0"), val = tensor([1, 1])]; tensor input_75_dilations_0 = const()[name = tensor("input_75_dilations_0"), val = tensor([1, 1])]; tensor input_75_groups_0 = const()[name = tensor("input_75_groups_0"), val = tensor(1)]; - tensor const_29_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_29_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1961024))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1998080))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1997952)))]; - tensor const_30 = const()[name = tensor("const_30"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1998400)))]; - tensor input_77 = conv(bias = const_30, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_29_quantized, x = input_73)[name = tensor("input_77")]; - tensor input_79 = relu(x = input_77)[name = tensor("input_79")]; + tensor const_29_to_fp16 = const()[name = tensor("const_29_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(597312)))]; + tensor const_30_to_fp16 = const()[name = tensor("const_30_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(671104)))]; + tensor out_11_cast_fp16 = conv(bias = const_30_to_fp16, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_29_to_fp16, x = input_73_cast_fp16)[name = tensor("out_11_cast_fp16")]; + tensor input_77_cast_fp16 = add(x = out_11_cast_fp16, y = input_67_cast_fp16)[name = tensor("input_77_cast_fp16")]; + tensor input_79_cast_fp16 = relu(x = input_77_cast_fp16)[name = tensor("input_79_cast_fp16")]; tensor input_81_pad_type_0 = const()[name = tensor("input_81_pad_type_0"), val = tensor("custom")]; tensor input_81_pad_0 = const()[name = tensor("input_81_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_81_strides_0 = const()[name = tensor("input_81_strides_0"), val = tensor([1, 1])]; tensor input_81_dilations_0 = const()[name = tensor("input_81_dilations_0"), val = tensor([1, 1])]; tensor input_81_groups_0 = const()[name = tensor("input_81_groups_0"), val = tensor(1)]; - tensor const_31_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_31_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1998720))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2035776))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2035648)))]; - tensor const_32 = const()[name = tensor("const_32"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2036096)))]; - tensor out_11 = conv(bias = const_32, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_31_quantized, x = input_79)[name = tensor("out_11")]; - tensor input_83 = add(x = out_11, y = input_73)[name = tensor("input_83")]; - tensor input_85 = relu(x = input_83)[name = tensor("input_85")]; + tensor const_31_to_fp16 = const()[name = tensor("const_31_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(671296)))]; + tensor const_32_to_fp16 = const()[name = tensor("const_32_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745088)))]; + tensor input_83_cast_fp16 = conv(bias = const_32_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_31_to_fp16, x = input_79_cast_fp16)[name = tensor("input_83_cast_fp16")]; + tensor input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = tensor("input_85_cast_fp16")]; tensor input_87_pad_type_0 = const()[name = tensor("input_87_pad_type_0"), val = tensor("custom")]; tensor input_87_pad_0 = const()[name = tensor("input_87_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_87_strides_0 = const()[name = tensor("input_87_strides_0"), val = tensor([1, 1])]; tensor input_87_dilations_0 = const()[name = tensor("input_87_dilations_0"), val = tensor([1, 1])]; tensor input_87_groups_0 = const()[name = tensor("input_87_groups_0"), val = tensor(1)]; - tensor const_33_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_33_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2036416))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2073472))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2073344)))]; - tensor const_34 = const()[name = tensor("const_34"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2073792)))]; - tensor input_89 = conv(bias = const_34, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_33_quantized, x = input_85)[name = tensor("input_89")]; - tensor input_91 = relu(x = input_89)[name = tensor("input_91")]; + tensor const_33_to_fp16 = const()[name = tensor("const_33_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(745280)))]; + tensor const_34_to_fp16 = const()[name = tensor("const_34_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(819072)))]; + tensor out_13_cast_fp16 = conv(bias = const_34_to_fp16, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_33_to_fp16, x = input_85_cast_fp16)[name = tensor("out_13_cast_fp16")]; + tensor input_89_cast_fp16 = add(x = out_13_cast_fp16, y = input_79_cast_fp16)[name = tensor("input_89_cast_fp16")]; + tensor input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = tensor("input_91_cast_fp16")]; tensor input_93_pad_type_0 = const()[name = tensor("input_93_pad_type_0"), val = tensor("custom")]; tensor input_93_pad_0 = const()[name = tensor("input_93_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_93_strides_0 = const()[name = tensor("input_93_strides_0"), val = tensor([1, 1])]; + tensor input_93_strides_0 = const()[name = tensor("input_93_strides_0"), val = tensor([2, 2])]; tensor input_93_dilations_0 = const()[name = tensor("input_93_dilations_0"), val = tensor([1, 1])]; tensor input_93_groups_0 = const()[name = tensor("input_93_groups_0"), val = tensor(1)]; - tensor const_35_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_35_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2074112))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2111168))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2111040)))]; - tensor const_36 = const()[name = tensor("const_36"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2111488)))]; - tensor out_13 = conv(bias = const_36, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_35_quantized, x = input_91)[name = tensor("out_13")]; - tensor input_95 = add(x = out_13, y = input_85)[name = tensor("input_95")]; - tensor input_97 = relu(x = input_95)[name = tensor("input_97")]; + tensor const_35_to_fp16 = const()[name = tensor("const_35_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(819264)))]; + tensor const_36_to_fp16 = const()[name = tensor("const_36_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(966784)))]; + tensor input_95_cast_fp16 = conv(bias = const_36_to_fp16, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_35_to_fp16, x = input_91_cast_fp16)[name = tensor("input_95_cast_fp16")]; + tensor input_97_cast_fp16 = relu(x = input_95_cast_fp16)[name = tensor("input_97_cast_fp16")]; tensor input_99_pad_type_0 = const()[name = tensor("input_99_pad_type_0"), val = tensor("custom")]; tensor input_99_pad_0 = const()[name = tensor("input_99_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_99_strides_0 = const()[name = tensor("input_99_strides_0"), val = tensor([2, 2])]; + tensor input_99_strides_0 = const()[name = tensor("input_99_strides_0"), val = tensor([1, 1])]; tensor input_99_dilations_0 = const()[name = tensor("input_99_dilations_0"), val = tensor([1, 1])]; tensor input_99_groups_0 = const()[name = tensor("input_99_groups_0"), val = tensor(1)]; - tensor const_37_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_37_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2111808))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185792))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_38 = const()[name = tensor("const_38"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2186368)))]; - tensor input_101 = conv(bias = const_38, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = const_37_quantized, x = input_97)[name = tensor("input_101")]; - tensor input_103 = relu(x = input_101)[name = tensor("input_103")]; - tensor input_105_pad_type_0 = const()[name = tensor("input_105_pad_type_0"), val = tensor("custom")]; - tensor input_105_pad_0 = const()[name = tensor("input_105_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_105_strides_0 = const()[name = tensor("input_105_strides_0"), val = tensor([1, 1])]; - tensor input_105_dilations_0 = const()[name = tensor("input_105_dilations_0"), val = tensor([1, 1])]; - tensor input_105_groups_0 = const()[name = tensor("input_105_groups_0"), val = tensor(1)]; - tensor const_39_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_39_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2186944))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2334464))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_40 = const()[name = tensor("const_40"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2335040)))]; - tensor out_15 = conv(bias = const_40, dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = const_39_quantized, x = input_103)[name = tensor("out_15")]; - tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("valid")]; - tensor input_107_strides_0 = const()[name = tensor("input_107_strides_0"), val = tensor([2, 2])]; - tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor const_37_to_fp16 = const()[name = tensor("const_37_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(967104)))]; + tensor const_38_to_fp16 = const()[name = tensor("const_38_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1262080)))]; + tensor out_15_cast_fp16 = conv(bias = const_38_to_fp16, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = const_37_to_fp16, x = input_97_cast_fp16)[name = tensor("out_15_cast_fp16")]; + tensor input_101_pad_type_0 = const()[name = tensor("input_101_pad_type_0"), val = tensor("valid")]; + tensor input_101_strides_0 = const()[name = tensor("input_101_strides_0"), val = tensor([2, 2])]; + tensor input_101_pad_0 = const()[name = tensor("input_101_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_101_dilations_0 = const()[name = tensor("input_101_dilations_0"), val = tensor([1, 1])]; + tensor input_101_groups_0 = const()[name = tensor("input_101_groups_0"), val = tensor(1)]; + tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1262400)))]; + tensor const_40_to_fp16 = const()[name = tensor("const_40_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1278848)))]; + tensor var_332_cast_fp16 = conv(bias = const_40_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = const_39_to_fp16, x = input_91_cast_fp16)[name = tensor("op_332_cast_fp16")]; + tensor input_103_cast_fp16 = add(x = out_15_cast_fp16, y = var_332_cast_fp16)[name = tensor("input_103_cast_fp16")]; + tensor input_105_cast_fp16 = relu(x = input_103_cast_fp16)[name = tensor("input_105_cast_fp16")]; + tensor input_107_pad_type_0 = const()[name = tensor("input_107_pad_type_0"), val = tensor("custom")]; + tensor input_107_pad_0 = const()[name = tensor("input_107_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_107_strides_0 = const()[name = tensor("input_107_strides_0"), val = tensor([1, 1])]; tensor input_107_dilations_0 = const()[name = tensor("input_107_dilations_0"), val = tensor([1, 1])]; tensor input_107_groups_0 = const()[name = tensor("input_107_groups_0"), val = tensor(1)]; - tensor const_41_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_41_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2335616))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2343872))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_42 = const()[name = tensor("const_42"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2344448)))]; - tensor var_475 = conv(bias = const_42, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_41_quantized, x = input_97)[name = tensor("op_475")]; - tensor input_109 = add(x = out_15, y = var_475)[name = tensor("input_109")]; - tensor input_111 = relu(x = input_109)[name = tensor("input_111")]; + tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1279168)))]; + tensor const_42_to_fp16 = const()[name = tensor("const_42_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1574144)))]; + tensor input_109_cast_fp16 = conv(bias = const_42_to_fp16, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_41_to_fp16, x = input_105_cast_fp16)[name = tensor("input_109_cast_fp16")]; + tensor input_111_cast_fp16 = relu(x = input_109_cast_fp16)[name = tensor("input_111_cast_fp16")]; tensor input_113_pad_type_0 = const()[name = tensor("input_113_pad_type_0"), val = tensor("custom")]; tensor input_113_pad_0 = const()[name = tensor("input_113_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_113_strides_0 = const()[name = tensor("input_113_strides_0"), val = tensor([1, 1])]; tensor input_113_dilations_0 = const()[name = tensor("input_113_dilations_0"), val = tensor([1, 1])]; tensor input_113_groups_0 = const()[name = tensor("input_113_groups_0"), val = tensor(1)]; - tensor const_43_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_43_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2345024))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2492544))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_44 = const()[name = tensor("const_44"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2493120)))]; - tensor input_115 = conv(bias = const_44, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_43_quantized, x = input_111)[name = tensor("input_115")]; - tensor input_117 = relu(x = input_115)[name = tensor("input_117")]; + tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1574464)))]; + tensor const_44_to_fp16 = const()[name = tensor("const_44_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1869440)))]; + tensor out_17_cast_fp16 = conv(bias = const_44_to_fp16, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_43_to_fp16, x = input_111_cast_fp16)[name = tensor("out_17_cast_fp16")]; + tensor input_115_cast_fp16 = add(x = out_17_cast_fp16, y = input_105_cast_fp16)[name = tensor("input_115_cast_fp16")]; + tensor input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = tensor("input_117_cast_fp16")]; tensor input_119_pad_type_0 = const()[name = tensor("input_119_pad_type_0"), val = tensor("custom")]; tensor input_119_pad_0 = const()[name = tensor("input_119_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_119_strides_0 = const()[name = tensor("input_119_strides_0"), val = tensor([1, 1])]; tensor input_119_dilations_0 = const()[name = tensor("input_119_dilations_0"), val = tensor([1, 1])]; tensor input_119_groups_0 = const()[name = tensor("input_119_groups_0"), val = tensor(1)]; - tensor const_45_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_45_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2493696))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2641216))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_46 = const()[name = tensor("const_46"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2641792)))]; - tensor out_17 = conv(bias = const_46, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_45_quantized, x = input_117)[name = tensor("out_17")]; - tensor input_121 = add(x = out_17, y = input_111)[name = tensor("input_121")]; - tensor input_123 = relu(x = input_121)[name = tensor("input_123")]; + tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1869760)))]; + tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2164736)))]; + tensor input_121_cast_fp16 = conv(bias = const_46_to_fp16, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_45_to_fp16, x = input_117_cast_fp16)[name = tensor("input_121_cast_fp16")]; + tensor input_123_cast_fp16 = relu(x = input_121_cast_fp16)[name = tensor("input_123_cast_fp16")]; tensor input_125_pad_type_0 = const()[name = tensor("input_125_pad_type_0"), val = tensor("custom")]; tensor input_125_pad_0 = const()[name = tensor("input_125_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_125_strides_0 = const()[name = tensor("input_125_strides_0"), val = tensor([1, 1])]; tensor input_125_dilations_0 = const()[name = tensor("input_125_dilations_0"), val = tensor([1, 1])]; tensor input_125_groups_0 = const()[name = tensor("input_125_groups_0"), val = tensor(1)]; - tensor const_47_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_47_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2642368))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2789888))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_48 = const()[name = tensor("const_48"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2790464)))]; - tensor input_127 = conv(bias = const_48, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = const_47_quantized, x = input_123)[name = tensor("input_127")]; - tensor input_129 = relu(x = input_127)[name = tensor("input_129")]; + tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2165056)))]; + tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2460032)))]; + tensor out_19_cast_fp16 = conv(bias = const_48_to_fp16, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = const_47_to_fp16, x = input_123_cast_fp16)[name = tensor("out_19_cast_fp16")]; + tensor input_127_cast_fp16 = add(x = out_19_cast_fp16, y = input_117_cast_fp16)[name = tensor("input_127_cast_fp16")]; + tensor input_129_cast_fp16 = relu(x = input_127_cast_fp16)[name = tensor("input_129_cast_fp16")]; tensor input_131_pad_type_0 = const()[name = tensor("input_131_pad_type_0"), val = tensor("custom")]; tensor input_131_pad_0 = const()[name = tensor("input_131_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_131_strides_0 = const()[name = tensor("input_131_strides_0"), val = tensor([1, 1])]; tensor input_131_dilations_0 = const()[name = tensor("input_131_dilations_0"), val = tensor([1, 1])]; tensor input_131_groups_0 = const()[name = tensor("input_131_groups_0"), val = tensor(1)]; - tensor const_49_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_49_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2791040))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2938560))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_50 = const()[name = tensor("const_50"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2939136)))]; - tensor out_19 = conv(bias = const_50, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = const_49_quantized, x = input_129)[name = tensor("out_19")]; - tensor input_133 = add(x = out_19, y = input_123)[name = tensor("input_133")]; - tensor input_135 = relu(x = input_133)[name = tensor("input_135")]; + tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2460352)))]; + tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2755328)))]; + tensor input_133_cast_fp16 = conv(bias = const_50_to_fp16, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = const_49_to_fp16, x = input_129_cast_fp16)[name = tensor("input_133_cast_fp16")]; + tensor input_135_cast_fp16 = relu(x = input_133_cast_fp16)[name = tensor("input_135_cast_fp16")]; tensor input_137_pad_type_0 = const()[name = tensor("input_137_pad_type_0"), val = tensor("custom")]; tensor input_137_pad_0 = const()[name = tensor("input_137_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_137_strides_0 = const()[name = tensor("input_137_strides_0"), val = tensor([1, 1])]; tensor input_137_dilations_0 = const()[name = tensor("input_137_dilations_0"), val = tensor([1, 1])]; tensor input_137_groups_0 = const()[name = tensor("input_137_groups_0"), val = tensor(1)]; - tensor const_51_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_51_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2939712))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3087232))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_52 = const()[name = tensor("const_52"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3087808)))]; - tensor input_139 = conv(bias = const_52, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = const_51_quantized, x = input_135)[name = tensor("input_139")]; - tensor input_141 = relu(x = input_139)[name = tensor("input_141")]; + tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2755648)))]; + tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3050624)))]; + tensor out_21_cast_fp16 = conv(bias = const_52_to_fp16, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = const_51_to_fp16, x = input_135_cast_fp16)[name = tensor("out_21_cast_fp16")]; + tensor input_139_cast_fp16 = add(x = out_21_cast_fp16, y = input_129_cast_fp16)[name = tensor("input_139_cast_fp16")]; + tensor input_141_cast_fp16 = relu(x = input_139_cast_fp16)[name = tensor("input_141_cast_fp16")]; tensor input_143_pad_type_0 = const()[name = tensor("input_143_pad_type_0"), val = tensor("custom")]; tensor input_143_pad_0 = const()[name = tensor("input_143_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_143_strides_0 = const()[name = tensor("input_143_strides_0"), val = tensor([1, 1])]; tensor input_143_dilations_0 = const()[name = tensor("input_143_dilations_0"), val = tensor([1, 1])]; tensor input_143_groups_0 = const()[name = tensor("input_143_groups_0"), val = tensor(1)]; - tensor const_53_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_53_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3088384))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3235904))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_54 = const()[name = tensor("const_54"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3236480)))]; - tensor out_21 = conv(bias = const_54, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = const_53_quantized, x = input_141)[name = tensor("out_21")]; - tensor input_145 = add(x = out_21, y = input_135)[name = tensor("input_145")]; - tensor input_147 = relu(x = input_145)[name = tensor("input_147")]; + tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3050944)))]; + tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3345920)))]; + tensor input_145_cast_fp16 = conv(bias = const_54_to_fp16, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = const_53_to_fp16, x = input_141_cast_fp16)[name = tensor("input_145_cast_fp16")]; + tensor input_147_cast_fp16 = relu(x = input_145_cast_fp16)[name = tensor("input_147_cast_fp16")]; tensor input_149_pad_type_0 = const()[name = tensor("input_149_pad_type_0"), val = tensor("custom")]; tensor input_149_pad_0 = const()[name = tensor("input_149_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_149_strides_0 = const()[name = tensor("input_149_strides_0"), val = tensor([1, 1])]; tensor input_149_dilations_0 = const()[name = tensor("input_149_dilations_0"), val = tensor([1, 1])]; tensor input_149_groups_0 = const()[name = tensor("input_149_groups_0"), val = tensor(1)]; - tensor const_55_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_55_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3237056))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3384576))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_56 = const()[name = tensor("const_56"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3385152)))]; - tensor input_151 = conv(bias = const_56, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = const_55_quantized, x = input_147)[name = tensor("input_151")]; - tensor input_153 = relu(x = input_151)[name = tensor("input_153")]; + tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3346240)))]; + tensor const_56_to_fp16 = const()[name = tensor("const_56_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3641216)))]; + tensor out_23_cast_fp16 = conv(bias = const_56_to_fp16, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = const_55_to_fp16, x = input_147_cast_fp16)[name = tensor("out_23_cast_fp16")]; + tensor input_151_cast_fp16 = add(x = out_23_cast_fp16, y = input_141_cast_fp16)[name = tensor("input_151_cast_fp16")]; + tensor input_153_cast_fp16 = relu(x = input_151_cast_fp16)[name = tensor("input_153_cast_fp16")]; tensor input_155_pad_type_0 = const()[name = tensor("input_155_pad_type_0"), val = tensor("custom")]; tensor input_155_pad_0 = const()[name = tensor("input_155_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_155_strides_0 = const()[name = tensor("input_155_strides_0"), val = tensor([1, 1])]; tensor input_155_dilations_0 = const()[name = tensor("input_155_dilations_0"), val = tensor([1, 1])]; tensor input_155_groups_0 = const()[name = tensor("input_155_groups_0"), val = tensor(1)]; - tensor const_57_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_57_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3385728))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3533248))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_58 = const()[name = tensor("const_58"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3533824)))]; - tensor out_23 = conv(bias = const_58, dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = const_57_quantized, x = input_153)[name = tensor("out_23")]; - tensor input_157 = add(x = out_23, y = input_147)[name = tensor("input_157")]; - tensor input_159 = relu(x = input_157)[name = tensor("input_159")]; + tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3641536)))]; + tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3936512)))]; + tensor input_157_cast_fp16 = conv(bias = const_58_to_fp16, dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = const_57_to_fp16, x = input_153_cast_fp16)[name = tensor("input_157_cast_fp16")]; + tensor input_159_cast_fp16 = relu(x = input_157_cast_fp16)[name = tensor("input_159_cast_fp16")]; tensor input_161_pad_type_0 = const()[name = tensor("input_161_pad_type_0"), val = tensor("custom")]; tensor input_161_pad_0 = const()[name = tensor("input_161_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_161_strides_0 = const()[name = tensor("input_161_strides_0"), val = tensor([1, 1])]; tensor input_161_dilations_0 = const()[name = tensor("input_161_dilations_0"), val = tensor([1, 1])]; tensor input_161_groups_0 = const()[name = tensor("input_161_groups_0"), val = tensor(1)]; - tensor const_59_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_59_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3534400))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3681920))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_60 = const()[name = tensor("const_60"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3682496)))]; - tensor input_163 = conv(bias = const_60, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_59_quantized, x = input_159)[name = tensor("input_163")]; - tensor input_165 = relu(x = input_163)[name = tensor("input_165")]; + tensor const_59_to_fp16 = const()[name = tensor("const_59_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3936832)))]; + tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4231808)))]; + tensor out_25_cast_fp16 = conv(bias = const_60_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_59_to_fp16, x = input_159_cast_fp16)[name = tensor("out_25_cast_fp16")]; + tensor input_163_cast_fp16 = add(x = out_25_cast_fp16, y = input_153_cast_fp16)[name = tensor("input_163_cast_fp16")]; + tensor input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = tensor("input_165_cast_fp16")]; tensor input_167_pad_type_0 = const()[name = tensor("input_167_pad_type_0"), val = tensor("custom")]; tensor input_167_pad_0 = const()[name = tensor("input_167_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_167_strides_0 = const()[name = tensor("input_167_strides_0"), val = tensor([1, 1])]; + tensor input_167_strides_0 = const()[name = tensor("input_167_strides_0"), val = tensor([2, 2])]; tensor input_167_dilations_0 = const()[name = tensor("input_167_dilations_0"), val = tensor([1, 1])]; tensor input_167_groups_0 = const()[name = tensor("input_167_groups_0"), val = tensor(1)]; - tensor const_61_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_61_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3683072))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3830592))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2185600)))]; - tensor const_62 = const()[name = tensor("const_62"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3831168)))]; - tensor out_25 = conv(bias = const_62, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_61_quantized, x = input_165)[name = tensor("out_25")]; - tensor input_169 = add(x = out_25, y = input_159)[name = tensor("input_169")]; - tensor input_171 = relu(x = input_169)[name = tensor("input_171")]; + tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4232128)))]; + tensor const_62_to_fp16 = const()[name = tensor("const_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4822016)))]; + tensor input_169_cast_fp16 = conv(bias = const_62_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_61_to_fp16, x = input_165_cast_fp16)[name = tensor("input_169_cast_fp16")]; + tensor input_171_cast_fp16 = relu(x = input_169_cast_fp16)[name = tensor("input_171_cast_fp16")]; tensor input_173_pad_type_0 = const()[name = tensor("input_173_pad_type_0"), val = tensor("custom")]; tensor input_173_pad_0 = const()[name = tensor("input_173_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_173_strides_0 = const()[name = tensor("input_173_strides_0"), val = tensor([2, 2])]; + tensor input_173_strides_0 = const()[name = tensor("input_173_strides_0"), val = tensor([1, 1])]; tensor input_173_dilations_0 = const()[name = tensor("input_173_dilations_0"), val = tensor([1, 1])]; tensor input_173_groups_0 = const()[name = tensor("input_173_groups_0"), val = tensor(1)]; - tensor const_63_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_63_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3831744))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4126720))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_64 = const()[name = tensor("const_64"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4127808)))]; - tensor input_175 = conv(bias = const_64, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = const_63_quantized, x = input_171)[name = tensor("input_175")]; - tensor input_177 = relu(x = input_175)[name = tensor("input_177")]; - tensor input_179_pad_type_0 = const()[name = tensor("input_179_pad_type_0"), val = tensor("custom")]; - tensor input_179_pad_0 = const()[name = tensor("input_179_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_179_strides_0 = const()[name = tensor("input_179_strides_0"), val = tensor([1, 1])]; - tensor input_179_dilations_0 = const()[name = tensor("input_179_dilations_0"), val = tensor([1, 1])]; - tensor input_179_groups_0 = const()[name = tensor("input_179_groups_0"), val = tensor(1)]; - tensor const_65_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_65_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4128896))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4718784))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_66 = const()[name = tensor("const_66"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4719872)))]; - tensor out_27 = conv(bias = const_66, dilations = input_179_dilations_0, groups = input_179_groups_0, pad = input_179_pad_0, pad_type = input_179_pad_type_0, strides = input_179_strides_0, weight = const_65_quantized, x = input_177)[name = tensor("out_27")]; - tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("valid")]; - tensor input_181_strides_0 = const()[name = tensor("input_181_strides_0"), val = tensor([2, 2])]; - tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor const_63_to_fp16 = const()[name = tensor("const_63_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4822592)))]; + tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6002304)))]; + tensor out_27_cast_fp16 = conv(bias = const_64_to_fp16, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = const_63_to_fp16, x = input_171_cast_fp16)[name = tensor("out_27_cast_fp16")]; + tensor input_175_pad_type_0 = const()[name = tensor("input_175_pad_type_0"), val = tensor("valid")]; + tensor input_175_strides_0 = const()[name = tensor("input_175_strides_0"), val = tensor([2, 2])]; + tensor input_175_pad_0 = const()[name = tensor("input_175_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor input_175_dilations_0 = const()[name = tensor("input_175_dilations_0"), val = tensor([1, 1])]; + tensor input_175_groups_0 = const()[name = tensor("input_175_groups_0"), val = tensor(1)]; + tensor const_65_to_fp16 = const()[name = tensor("const_65_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6002880)))]; + tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6068480)))]; + tensor var_523_cast_fp16 = conv(bias = const_66_to_fp16, dilations = input_175_dilations_0, groups = input_175_groups_0, pad = input_175_pad_0, pad_type = input_175_pad_type_0, strides = input_175_strides_0, weight = const_65_to_fp16, x = input_165_cast_fp16)[name = tensor("op_523_cast_fp16")]; + tensor input_177_cast_fp16 = add(x = out_27_cast_fp16, y = var_523_cast_fp16)[name = tensor("input_177_cast_fp16")]; + tensor input_179_cast_fp16 = relu(x = input_177_cast_fp16)[name = tensor("input_179_cast_fp16")]; + tensor input_181_pad_type_0 = const()[name = tensor("input_181_pad_type_0"), val = tensor("custom")]; + tensor input_181_pad_0 = const()[name = tensor("input_181_pad_0"), val = tensor([1, 1, 1, 1])]; + tensor input_181_strides_0 = const()[name = tensor("input_181_strides_0"), val = tensor([1, 1])]; tensor input_181_dilations_0 = const()[name = tensor("input_181_dilations_0"), val = tensor([1, 1])]; tensor input_181_groups_0 = const()[name = tensor("input_181_groups_0"), val = tensor(1)]; - tensor const_67_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_67_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4720960))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4753792))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_68 = const()[name = tensor("const_68"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4754880)))]; - tensor var_666 = conv(bias = const_68, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = const_67_quantized, x = input_171)[name = tensor("op_666")]; - tensor input_183 = add(x = out_27, y = var_666)[name = tensor("input_183")]; - tensor input_185 = relu(x = input_183)[name = tensor("input_185")]; + tensor const_67_to_fp16 = const()[name = tensor("const_67_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6069056)))]; + tensor const_68_to_fp16 = const()[name = tensor("const_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7248768)))]; + tensor input_183_cast_fp16 = conv(bias = const_68_to_fp16, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = const_67_to_fp16, x = input_179_cast_fp16)[name = tensor("input_183_cast_fp16")]; + tensor input_185_cast_fp16 = relu(x = input_183_cast_fp16)[name = tensor("input_185_cast_fp16")]; tensor input_187_pad_type_0 = const()[name = tensor("input_187_pad_type_0"), val = tensor("custom")]; tensor input_187_pad_0 = const()[name = tensor("input_187_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_187_strides_0 = const()[name = tensor("input_187_strides_0"), val = tensor([1, 1])]; tensor input_187_dilations_0 = const()[name = tensor("input_187_dilations_0"), val = tensor([1, 1])]; tensor input_187_groups_0 = const()[name = tensor("input_187_groups_0"), val = tensor(1)]; - tensor const_69_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_69_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4755968))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5345856))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_70 = const()[name = tensor("const_70"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5346944)))]; - tensor input_189 = conv(bias = const_70, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_69_quantized, x = input_185)[name = tensor("input_189")]; - tensor input_191 = relu(x = input_189)[name = tensor("input_191")]; + tensor const_69_to_fp16 = const()[name = tensor("const_69_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7249344)))]; + tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8429056)))]; + tensor out_29_cast_fp16 = conv(bias = const_70_to_fp16, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_69_to_fp16, x = input_185_cast_fp16)[name = tensor("out_29_cast_fp16")]; + tensor input_189_cast_fp16 = add(x = out_29_cast_fp16, y = input_179_cast_fp16)[name = tensor("input_189_cast_fp16")]; + tensor input_191_cast_fp16 = relu(x = input_189_cast_fp16)[name = tensor("input_191_cast_fp16")]; tensor input_193_pad_type_0 = const()[name = tensor("input_193_pad_type_0"), val = tensor("custom")]; tensor input_193_pad_0 = const()[name = tensor("input_193_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_193_strides_0 = const()[name = tensor("input_193_strides_0"), val = tensor([1, 1])]; tensor input_193_dilations_0 = const()[name = tensor("input_193_dilations_0"), val = tensor([1, 1])]; tensor input_193_groups_0 = const()[name = tensor("input_193_groups_0"), val = tensor(1)]; - tensor const_71_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_71_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5348032))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5937920))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_72 = const()[name = tensor("const_72"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5939008)))]; - tensor out_29 = conv(bias = const_72, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_71_quantized, x = input_191)[name = tensor("out_29")]; - tensor input_195 = add(x = out_29, y = input_185)[name = tensor("input_195")]; - tensor input_197 = relu(x = input_195)[name = tensor("input_197")]; + tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8429632)))]; + tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9609344)))]; + tensor input_195_cast_fp16 = conv(bias = const_72_to_fp16, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_71_to_fp16, x = input_191_cast_fp16)[name = tensor("input_195_cast_fp16")]; + tensor input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = tensor("input_197_cast_fp16")]; tensor input_199_pad_type_0 = const()[name = tensor("input_199_pad_type_0"), val = tensor("custom")]; tensor input_199_pad_0 = const()[name = tensor("input_199_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_199_strides_0 = const()[name = tensor("input_199_strides_0"), val = tensor([1, 1])]; tensor input_199_dilations_0 = const()[name = tensor("input_199_dilations_0"), val = tensor([1, 1])]; tensor input_199_groups_0 = const()[name = tensor("input_199_groups_0"), val = tensor(1)]; - tensor const_73_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_73_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5940096))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6529984))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_74 = const()[name = tensor("const_74"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6531072)))]; - tensor input_201 = conv(bias = const_74, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_73_quantized, x = input_197)[name = tensor("input_201")]; - tensor input_203 = relu(x = input_201)[name = tensor("input_203")]; - tensor input_205_pad_type_0 = const()[name = tensor("input_205_pad_type_0"), val = tensor("custom")]; - tensor input_205_pad_0 = const()[name = tensor("input_205_pad_0"), val = tensor([1, 1, 1, 1])]; - tensor input_205_strides_0 = const()[name = tensor("input_205_strides_0"), val = tensor([1, 1])]; - tensor input_205_dilations_0 = const()[name = tensor("input_205_dilations_0"), val = tensor([1, 1])]; - tensor input_205_groups_0 = const()[name = tensor("input_205_groups_0"), val = tensor(1)]; - tensor const_75_quantized = constexpr_affine_dequantize()[axis = tensor(0), name = tensor("const_75_quantized"), quantized_data = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6532160))), scale = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7122048))), zero_point = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1764224)))]; - tensor const_76 = const()[name = tensor("const_76"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7123136)))]; - tensor out = conv(bias = const_76, dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = const_75_quantized, x = input_203)[name = tensor("out")]; - tensor input_207 = add(x = out, y = input_197)[name = tensor("input_207")]; - tensor features = relu(x = input_207)[name = tensor("features")]; - tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([-1, 2560, 125])]; - tensor sequences = reshape(shape = concat_4x, x = features)[name = tensor("sequences")]; - tensor weights_5_axes_0 = const()[name = tensor("weights_5_axes_0"), val = tensor([1])]; - tensor weights_5 = expand_dims(axes = weights_5_axes_0, x = weights_3)[name = tensor("weights_5")]; - tensor weights_axes_0 = const()[name = tensor("weights_axes_0"), val = tensor([2])]; - tensor weights = expand_dims(axes = weights_axes_0, x = weights_5)[name = tensor("weights")]; - tensor var_740_axes_0 = const()[name = tensor("op_740_axes_0"), val = tensor([-1])]; - tensor var_740_keep_dims_0 = const()[name = tensor("op_740_keep_dims_0"), val = tensor(false)]; - tensor var_740 = reduce_sum(axes = var_740_axes_0, keep_dims = var_740_keep_dims_0, x = weights)[name = tensor("op_740")]; - tensor var_741 = const()[name = tensor("op_741"), val = tensor(0x1.5798eep-27)]; - tensor v1 = add(x = var_740, y = var_741)[name = tensor("v1")]; - tensor var_743_axes_0 = const()[name = tensor("op_743_axes_0"), val = tensor([1])]; - tensor var_743 = expand_dims(axes = var_743_axes_0, x = sequences)[name = tensor("op_743")]; - tensor weighted = mul(x = var_743, y = weights)[name = tensor("weighted")]; - tensor var_746_axes_0 = const()[name = tensor("op_746_axes_0"), val = tensor([-1])]; - tensor var_746_keep_dims_0 = const()[name = tensor("op_746_keep_dims_0"), val = tensor(false)]; - tensor var_746 = reduce_sum(axes = var_746_axes_0, keep_dims = var_746_keep_dims_0, x = weighted)[name = tensor("op_746")]; - tensor mean = real_div(x = var_746, y = v1)[name = tensor("mean")]; - tensor var_749_axes_0 = const()[name = tensor("op_749_axes_0"), val = tensor([-1])]; - tensor var_749 = expand_dims(axes = var_749_axes_0, x = mean)[name = tensor("op_749")]; - tensor diff = sub(x = var_743, y = var_749)[name = tensor("diff")]; - tensor var_751 = mul(x = weights, y = weights)[name = tensor("op_751")]; + tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9609920)))]; + tensor const_74_to_fp16 = const()[name = tensor("const_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10789632)))]; + tensor out_cast_fp16 = conv(bias = const_74_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_73_to_fp16, x = input_197_cast_fp16)[name = tensor("out_cast_fp16")]; + tensor input_201_cast_fp16 = add(x = out_cast_fp16, y = input_191_cast_fp16)[name = tensor("input_201_cast_fp16")]; + tensor features_cast_fp16 = relu(x = input_201_cast_fp16)[name = tensor("features_cast_fp16")]; + tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([-1, 2560, 125])]; + tensor sequences_1_cast_fp16 = reshape(shape = concat_0x, x = features_cast_fp16)[name = tensor("sequences_1_cast_fp16")]; + tensor weights_fp32_axes_0 = const()[name = tensor("weights_fp32_axes_0"), val = tensor([1])]; + tensor weights_fp32_cast_fp16 = expand_dims(axes = weights_fp32_axes_0, x = weights_3_cast_fp16)[name = tensor("weights_fp32_cast_fp16")]; + tensor weights_expanded_axes_0 = const()[name = tensor("weights_expanded_axes_0"), val = tensor([2])]; + tensor weights_expanded_cast_fp16 = expand_dims(axes = weights_expanded_axes_0, x = weights_fp32_cast_fp16)[name = tensor("weights_expanded_cast_fp16")]; + tensor var_599_axes_0 = const()[name = tensor("op_599_axes_0"), val = tensor([-1])]; + tensor var_599_keep_dims_0 = const()[name = tensor("op_599_keep_dims_0"), val = tensor(false)]; + tensor var_599_cast_fp16 = reduce_sum(axes = var_599_axes_0, keep_dims = var_599_keep_dims_0, x = weights_expanded_cast_fp16)[name = tensor("op_599_cast_fp16")]; + tensor var_600_to_fp16 = const()[name = tensor("op_600_to_fp16"), val = tensor(0x1.a38p-14)]; + tensor v1_cast_fp16 = add(x = var_599_cast_fp16, y = var_600_to_fp16)[name = tensor("v1_cast_fp16")]; + tensor var_602_axes_0 = const()[name = tensor("op_602_axes_0"), val = tensor([1])]; + tensor var_602_cast_fp16 = expand_dims(axes = var_602_axes_0, x = sequences_1_cast_fp16)[name = tensor("op_602_cast_fp16")]; + tensor weighted_cast_fp16 = mul(x = var_602_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor("weighted_cast_fp16")]; + tensor var_605_axes_0 = const()[name = tensor("op_605_axes_0"), val = tensor([-1])]; + tensor var_605_keep_dims_0 = const()[name = tensor("op_605_keep_dims_0"), val = tensor(false)]; + tensor var_605_cast_fp16 = reduce_sum(axes = var_605_axes_0, keep_dims = var_605_keep_dims_0, x = weighted_cast_fp16)[name = tensor("op_605_cast_fp16")]; + tensor mean_cast_fp16 = real_div(x = var_605_cast_fp16, y = v1_cast_fp16)[name = tensor("mean_cast_fp16")]; + tensor var_608_axes_0 = const()[name = tensor("op_608_axes_0"), val = tensor([-1])]; + tensor var_608_cast_fp16 = expand_dims(axes = var_608_axes_0, x = mean_cast_fp16)[name = tensor("op_608_cast_fp16")]; + tensor diff_cast_fp16 = sub(x = var_602_cast_fp16, y = var_608_cast_fp16)[name = tensor("diff_cast_fp16")]; + tensor var_610_cast_fp16 = mul(x = weights_expanded_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor("op_610_cast_fp16")]; tensor v2_axes_0 = const()[name = tensor("v2_axes_0"), val = tensor([-1])]; tensor v2_keep_dims_0 = const()[name = tensor("v2_keep_dims_0"), val = tensor(false)]; - tensor v2 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_751)[name = tensor("v2")]; - tensor var_754 = real_div(x = v2, y = v1)[name = tensor("op_754")]; - tensor var_755 = sub(x = v1, y = var_754)[name = tensor("op_755")]; - tensor var_756 = const()[name = tensor("op_756"), val = tensor(0x1.5798eep-27)]; - tensor denom = add(x = var_755, y = var_756)[name = tensor("denom")]; - tensor var_758 = mul(x = diff, y = diff)[name = tensor("op_758")]; - tensor var_759 = mul(x = var_758, y = weights)[name = tensor("op_759")]; - tensor var_761_axes_0 = const()[name = tensor("op_761_axes_0"), val = tensor([-1])]; - tensor var_761_keep_dims_0 = const()[name = tensor("op_761_keep_dims_0"), val = tensor(false)]; - tensor var_761 = reduce_sum(axes = var_761_axes_0, keep_dims = var_761_keep_dims_0, x = var_759)[name = tensor("op_761")]; - tensor var = real_div(x = var_761, y = denom)[name = tensor("var")]; - tensor const_3 = const()[name = tensor("const_3"), val = tensor(0x1.fffffep+127)]; - tensor clip_1 = clip(alpha = var_177, beta = const_3, x = var)[name = tensor("clip_1")]; - tensor std = sqrt(x = clip_1)[name = tensor("std")]; + tensor v2_cast_fp16 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_610_cast_fp16)[name = tensor("v2_cast_fp16")]; + tensor var_613_cast_fp16 = real_div(x = v2_cast_fp16, y = v1_cast_fp16)[name = tensor("op_613_cast_fp16")]; + tensor var_614_cast_fp16 = sub(x = v1_cast_fp16, y = var_613_cast_fp16)[name = tensor("op_614_cast_fp16")]; + tensor var_615_to_fp16 = const()[name = tensor("op_615_to_fp16"), val = tensor(0x1.a38p-14)]; + tensor denom_cast_fp16 = add(x = var_614_cast_fp16, y = var_615_to_fp16)[name = tensor("denom_cast_fp16")]; + tensor var_617_cast_fp16 = mul(x = diff_cast_fp16, y = diff_cast_fp16)[name = tensor("op_617_cast_fp16")]; + tensor var_618_cast_fp16 = mul(x = var_617_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor("op_618_cast_fp16")]; + tensor var_620_axes_0 = const()[name = tensor("op_620_axes_0"), val = tensor([-1])]; + tensor var_620_keep_dims_0 = const()[name = tensor("op_620_keep_dims_0"), val = tensor(false)]; + tensor var_620_cast_fp16 = reduce_sum(axes = var_620_axes_0, keep_dims = var_620_keep_dims_0, x = var_618_cast_fp16)[name = tensor("op_620_cast_fp16")]; + tensor var_cast_fp16 = real_div(x = var_620_cast_fp16, y = denom_cast_fp16)[name = tensor("var_cast_fp16")]; + tensor var_34_to_fp16 = const()[name = tensor("op_34_to_fp16"), val = tensor(0x1.1p-20)]; + tensor const_1_to_fp16 = const()[name = tensor("const_1_to_fp16"), val = tensor(inf)]; + tensor clip_0_cast_fp16 = clip(alpha = var_34_to_fp16, beta = const_1_to_fp16, x = var_cast_fp16)[name = tensor("clip_0_cast_fp16")]; + tensor std_cast_fp16 = sqrt(x = clip_0_cast_fp16)[name = tensor("std_cast_fp16")]; tensor output_interleave_0 = const()[name = tensor("output_interleave_0"), val = tensor(false)]; - tensor output = concat(axis = var_176, interleave = output_interleave_0, values = (mean, std))[name = tensor("output")]; - tensor stats_axes_0 = const()[name = tensor("stats_axes_0"), val = tensor([1])]; - tensor stats = squeeze(axes = stats_axes_0, x = output)[name = tensor("stats")]; - tensor var_768_axes_0 = const()[name = tensor("op_768_axes_0"), val = tensor([-1])]; - tensor var_768 = expand_dims(axes = var_768_axes_0, x = stats)[name = tensor("op_768")]; - tensor input_209_axes_0 = const()[name = tensor("input_209_axes_0"), val = tensor([-1])]; - tensor input_209 = expand_dims(axes = input_209_axes_0, x = var_768)[name = tensor("input_209")]; - tensor var_776_pad_type_0 = const()[name = tensor("op_776_pad_type_0"), val = tensor("valid")]; - tensor var_776_strides_0 = const()[name = tensor("op_776_strides_0"), val = tensor([1, 1])]; - tensor var_776_pad_0 = const()[name = tensor("op_776_pad_0"), val = tensor([0, 0, 0, 0])]; - tensor var_776_dilations_0 = const()[name = tensor("op_776_dilations_0"), val = tensor([1, 1])]; - tensor var_776_groups_0 = const()[name = tensor("op_776_groups_0"), val = tensor(1)]; - tensor var_776 = conv(bias = resnet_seg_1_bias, dilations = var_776_dilations_0, groups = var_776_groups_0, pad = var_776_pad_0, pad_type = var_776_pad_type_0, strides = var_776_strides_0, weight = resnet_seg_1_weight_quantized, x = input_209)[name = tensor("op_776")]; - tensor concat_5x = const()[name = tensor("concat_5x"), val = tensor([-1, 256])]; - tensor input = reshape(shape = concat_5x, x = var_776)[name = tensor("input")]; - tensor var_780 = const()[name = tensor("op_780"), val = tensor([-1])]; - tensor var_781 = const()[name = tensor("op_781"), val = tensor(true)]; - tensor norms_1 = reduce_l2_norm(axes = var_780, keep_dims = var_781, x = input)[name = tensor("norms_1")]; - tensor var_784 = const()[name = tensor("op_784"), val = tensor(0x1.197998p-40)]; - tensor const_4 = const()[name = tensor("const_4"), val = tensor(0x1.fffffep+127)]; - tensor clip_2 = clip(alpha = var_784, beta = const_4, x = norms_1)[name = tensor("clip_2")]; - tensor embedding = real_div(x = input, y = clip_2)[name = tensor("op_787")]; + tensor output_cast_fp16 = concat(axis = var_33, interleave = output_interleave_0, values = (mean_cast_fp16, std_cast_fp16))[name = tensor("output_cast_fp16")]; + tensor var_626_axes_0 = const()[name = tensor("op_626_axes_0"), val = tensor([1])]; + tensor var_626_cast_fp16 = squeeze(axes = var_626_axes_0, x = output_cast_fp16)[name = tensor("op_626_cast_fp16")]; + tensor var_628_axes_0 = const()[name = tensor("op_628_axes_0"), val = tensor([-1])]; + tensor var_628_cast_fp16 = expand_dims(axes = var_628_axes_0, x = var_626_cast_fp16)[name = tensor("op_628_cast_fp16")]; + tensor input_203_axes_0 = const()[name = tensor("input_203_axes_0"), val = tensor([-1])]; + tensor input_203_cast_fp16 = expand_dims(axes = input_203_axes_0, x = var_628_cast_fp16)[name = tensor("input_203_cast_fp16")]; + tensor var_636_pad_type_0 = const()[name = tensor("op_636_pad_type_0"), val = tensor("valid")]; + tensor var_636_strides_0 = const()[name = tensor("op_636_strides_0"), val = tensor([1, 1])]; + tensor var_636_pad_0 = const()[name = tensor("op_636_pad_0"), val = tensor([0, 0, 0, 0])]; + tensor var_636_dilations_0 = const()[name = tensor("op_636_dilations_0"), val = tensor([1, 1])]; + tensor var_636_groups_0 = const()[name = tensor("op_636_groups_0"), val = tensor(1)]; + tensor resnet_seg_1_weight_to_fp16 = const()[name = tensor("resnet_seg_1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10790208)))]; + tensor resnet_seg_1_bias_to_fp16 = const()[name = tensor("resnet_seg_1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13411712)))]; + tensor var_636_cast_fp16 = conv(bias = resnet_seg_1_bias_to_fp16, dilations = var_636_dilations_0, groups = var_636_groups_0, pad = var_636_pad_0, pad_type = var_636_pad_type_0, strides = var_636_strides_0, weight = resnet_seg_1_weight_to_fp16, x = input_203_cast_fp16)[name = tensor("op_636_cast_fp16")]; + tensor concat_1x = const()[name = tensor("concat_1x"), val = tensor([-1, 256])]; + tensor input_cast_fp16 = reshape(shape = concat_1x, x = var_636_cast_fp16)[name = tensor("input_cast_fp16")]; + tensor input_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("input_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor var_640 = const()[name = tensor("op_640"), val = tensor([-1])]; + tensor var_641 = const()[name = tensor("op_641"), val = tensor(true)]; + tensor input_cast_fp16_to_fp32 = cast(dtype = input_cast_fp16_to_fp32_dtype_0, x = input_cast_fp16)[name = tensor("cast_12")]; + tensor norms_1 = reduce_l2_norm(axes = var_640, keep_dims = var_641, x = input_cast_fp16_to_fp32)[name = tensor("norms_1")]; + tensor norms_1_to_fp16_dtype_0 = const()[name = tensor("norms_1_to_fp16_dtype_0"), val = tensor("fp16")]; + tensor var_644_to_fp16 = const()[name = tensor("op_644_to_fp16"), val = tensor(0x1.a38p-14)]; + tensor const_2_to_fp16 = const()[name = tensor("const_2_to_fp16"), val = tensor(inf)]; + tensor norms_1_to_fp16 = cast(dtype = norms_1_to_fp16_dtype_0, x = norms_1)[name = tensor("cast_11")]; + tensor clip_1_cast_fp16 = clip(alpha = var_644_to_fp16, beta = const_2_to_fp16, x = norms_1_to_fp16)[name = tensor("clip_1_cast_fp16")]; + tensor var_647_cast_fp16 = real_div(x = input_cast_fp16, y = clip_1_cast_fp16)[name = tensor("op_647_cast_fp16")]; + tensor var_647_cast_fp16_to_fp32_dtype_0 = const()[name = tensor("op_647_cast_fp16_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor embedding = cast(dtype = var_647_cast_fp16_to_fp32_dtype_0, x = var_647_cast_fp16)[name = tensor("cast_10")]; } -> (embedding); } \ No newline at end of file