



_snake_case	=						{
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case	=						logging.get_logger(__name__)

_snake_case	=						{
    "facebook/data2vec-vision-base-ft": (
        "https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json"
    ),
}



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	'data2vec-vision'







							def __init__(     self,    __a=768,    __a=12,    __a=12,    __a=3072,    __a="gelu",    __a=0.0,    __a=0.0,    __a=0.02,    __a=1E-12,    __a=224,    __a=16,    __a=3,    __a=False,    __a=False,    __a=False,    __a=False,    __a=0.1,    __a=0.1,    __a=True,    __a=[3, 5, 7, 11],    __a=[1, 2, 3, 6],    __a=True,    __a=0.4,    __a=256,    __a=1,    __a=False,    __a=255,    **__a,    ):

														'''simple docstring'''

														super().__init__(**__a)

														_lowerCAmelCase  :							Dict				     =					hidden_size
														_lowerCAmelCase  :							List[Any]				     =					num_hidden_layers
														_lowerCAmelCase  :							Any				     =					num_attention_heads
														_lowerCAmelCase  :							str				     =					intermediate_size
														_lowerCAmelCase  :							Optional[Any]				     =					hidden_act
														_lowerCAmelCase  :							int				     =					hidden_dropout_prob
														_lowerCAmelCase  :							Dict				     =					attention_probs_dropout_prob
														_lowerCAmelCase  :							Dict				     =					initializer_range
														_lowerCAmelCase  :							List[str]				     =					layer_norm_eps

														_lowerCAmelCase  :							Optional[int]				     =					image_size
														_lowerCAmelCase  :							List[Any]				     =					patch_size
														_lowerCAmelCase  :							Optional[Any]				     =					num_channels
														_lowerCAmelCase  :							str				     =					use_mask_token
														_lowerCAmelCase  :							List[str]				     =					use_absolute_position_embeddings
														_lowerCAmelCase  :							str				     =					use_relative_position_bias
														_lowerCAmelCase  :							List[str]				     =					use_shared_relative_position_bias
														_lowerCAmelCase  :							List[str]				     =					layer_scale_init_value
														_lowerCAmelCase  :							List[Any]				     =					drop_path_rate
														_lowerCAmelCase  :							Union[str, Any]				     =					use_mean_pooling
														# decode head attributes (semantic segmentation)
														_lowerCAmelCase  :							Tuple				     =					out_indices
														_lowerCAmelCase  :							Tuple				     =					pool_scales
														# auxiliary head attributes (semantic segmentation)
														_lowerCAmelCase  :							Optional[int]				     =					use_auxiliary_head
														_lowerCAmelCase  :							Optional[Any]				     =					auxiliary_loss_weight
														_lowerCAmelCase  :							int				     =					auxiliary_channels
														_lowerCAmelCase  :							Optional[Any]				     =					auxiliary_num_convs
														_lowerCAmelCase  :							int				     =					auxiliary_concat_input
														_lowerCAmelCase  :							Dict				     =					semantic_loss_ignore_index



class 						UpperCAmelCase_					( a):
							lowerCamelCase__         =	version.parse('1.11')







							@property
							def      snake_case__   (     self):

														'''simple docstring'''

														return OrderedDict(
														    [
														        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
														    ])







							@property
							def      snake_case__   (     self):

														'''simple docstring'''

														return 1E-4
