File size: 5,865 Bytes
43a4a81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 |
"""
configuration_prismatic.py
HuggingFace-style configuration definition for Prismatic VLMs, inheriting from `transformers.PretrainedConfig`.
Default configuration specifies `siglip-224px+7b`.
"""
from typing import Any, Dict, List, Optional
from transformers import PretrainedConfig
from transformers.models.auto import CONFIG_MAPPING
# === Utilities for Mapping Prismatic names to HF names ===
# fmt: off
VISION_BACKBONE_TO_RESOLUTION: Dict[str, List[int]] = {
"clip-vit-l": [224], "siglip-vit-so400m": [224], "dinov2-vit-l": [224], "in1k-vit-l": [224],
"clip-vit-l-336px": [336],
"siglip-vit-so400m-384px": [384],
"dinoclip-vit-l-336px": [336, 336],
"dinosiglip-vit-so-224px": [224, 224],
"dinosiglip-vit-so-384px": [384, 384],
}
VISION_BACKBONE_TO_TIMM_ID: Dict[str, List[str]] = {
"clip-vit-l": ["vit_large_patch14_clip_224.openai"],
"clip-vit-l-336px": ["vit_large_patch14_clip_336.openai"],
"dinov2-vit-l": ["vit_large_patch14_reg4_dinov2.lvd142m"],
"in1k-vit-l": ["vit_large_patch16_224.augreg_in21k_ft_in1k"],
"siglip-vit-so400m": ["vit_so400m_patch14_siglip_224"],
"siglip-vit-so400m-384px": ["vit_so400m_patch14_siglip_384"],
"dinoclip-vit-l-336px": ["vit_large_patch14_reg4_dinov2.lvd142m", "vit_large_patch14_clip_336.openai"],
"dinosiglip-vit-so-224px": ["vit_large_patch14_reg4_dinov2.lvd142m", "vit_so400m_patch14_siglip_224"],
"dinosiglip-vit-so-384px": ["vit_large_patch14_reg4_dinov2.lvd142m", "vit_so400m_patch14_siglip_384"],
}
TIMM_OVERRIDE_ACT_LAYER: Dict[str, List[Optional[str]]] = {
"clip-vit-l": ["quick_gelu"], "clip-vit-l-336px": ["quick_gelu"],
"dinov2-vit-l": [None], "in1k-vit-l": [None],
"siglip-vit-so400m": [None], "siglip-vit-so400m-384px": [None],
"dinoclip-vit-l-336px": [None, "quick_gelu"],
"dinosiglip-vit-so-224px": [None, None], "dinosiglip-vit-so-384px": [None, None]
}
LLM_BACKBONE_TO_HF_PATH = {
"llama2-7b-pure": "meta-llama/Llama-2-7b-hf", "llama2-13b-pure": "meta-llama/Llama-2-13b-hf",
"llama2-7b-chat": "meta-llama/Llama-2-7b-chat-hf", "llama2-13b-chat": "meta-llama/Llama-2-13b-chat-hf",
"vicuna-v15-7b": "lmsys/vicuna-7b-v1.5", "vicuna-v15-13b": "lmsys/vicuna-13b-v1.5",
"mistral-v0.1-7b-pure": "mistralai/Mistral-7B-v0.1",
"mistral-v0.1-7b-instruct": "mistralai/Mistral-7B-Instruct-v0.1",
"phi-2-3b": "microsoft/phi-2",
}
LLM_BACKBONE_TO_HF_METACLASS = {
"llama2-7b-pure": "llama", "llama2-13b-pure": "llama", "llama2-7b-chat": "llama", "llama2-13b-chat": "llama",
"vicuna-v15-7b": "llama", "vicuna-v15-13b": "llama",
"mistral-v0.1-7b-pure": "mistral", "mistral-v0.1-7b-instruct": "mistral",
"phi-2-3b": "phi",
}
VALID_VISION_BACKBONES = set(VISION_BACKBONE_TO_RESOLUTION.keys())
VALID_LLM_BACKBONES = set(LLM_BACKBONE_TO_HF_PATH)
# fmt: on
class PrismaticConfig(PretrainedConfig):
model_type: str = "prismatic"
is_composition: bool = False
def __init__(
self,
vision_backbone_id: str = "siglip-vit-so400m",
llm_backbone_id: str = "vicuna-v15-7b",
arch_specifier: str = "no-align+gelu-mlp",
use_fused_vision_backbone: Optional[bool] = None,
image_resize_strategy: str = "letterbox",
text_config: Optional[Dict[str, Any]] = None,
llm_max_length: int = 2048,
pad_token_id: int = 32000,
pad_to_multiple_of: int = 64,
output_projector_states: bool = False,
**kwargs: str,
) -> None:
if vision_backbone_id not in VALID_VISION_BACKBONES:
raise ValueError(f"Vision backbone `{vision_backbone_id}` not in {VALID_VISION_BACKBONES = }")
if llm_backbone_id not in VALID_LLM_BACKBONES:
raise ValueError(f"LLM backbone `{llm_backbone_id}` not in {VALID_LLM_BACKBONES = }")
# Set Prismatic Configuration Fields
self.vision_backbone_id = vision_backbone_id
self.llm_backbone_id = llm_backbone_id
self.arch_specifier = arch_specifier
self.output_projector_states = output_projector_states
# [Contract] All vision backbone parameters are lists =>> supports fused backbones with different preprocessing
self.use_fused_vision_backbone = (
use_fused_vision_backbone
if use_fused_vision_backbone is not None
else any(self.vision_backbone_id.startswith(v) for v in ["dinoclip", "dinosiglip"])
)
self.timm_model_ids = VISION_BACKBONE_TO_TIMM_ID[self.vision_backbone_id]
self.timm_override_act_layers = TIMM_OVERRIDE_ACT_LAYER[self.vision_backbone_id]
self.image_sizes = VISION_BACKBONE_TO_RESOLUTION[self.vision_backbone_id]
self.image_resize_strategy = image_resize_strategy
self.hf_llm_id = LLM_BACKBONE_TO_HF_PATH[self.llm_backbone_id]
self.llm_max_length = llm_max_length
self.pad_token_id, self.pad_to_multiple_of = pad_token_id, pad_to_multiple_of
# [IMPORTANT] HF Utilities actually look for a `text_config` field... we need to use that specific naming!
self.text_config = (
CONFIG_MAPPING[LLM_BACKBONE_TO_HF_METACLASS[self.llm_backbone_id]](**text_config)
if text_config is not None
else CONFIG_MAPPING[LLM_BACKBONE_TO_HF_METACLASS[self.llm_backbone_id]]()
)
# Dispatch **kwargs to super() =>> note that `pad_token_id` collides, so we pass it in here as well...
super().__init__(pad_token_id=pad_token_id, **kwargs)
class OpenVLAConfig(PrismaticConfig):
model_type: str = "openvla"
def __init__(
self,
norm_stats: Optional[Dict[str, Dict[str, Dict[str, Dict[str, List[float]]]]]] = None,
n_action_bins: int = 256,
**kwargs: str,
) -> None:
self.norm_stats, self.n_action_bins = norm_stats, n_action_bins
super().__init__(**kwargs)
|