
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


_A     =  logging.get_logger(__name__)

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





class 			_lowerCAmelCase      (			__a ):
				_lowercase    	='''data2vec-vision'''




				def __init__(      self       ,       _UpperCamelCase=768       ,       _UpperCamelCase=12       ,       _UpperCamelCase=12       ,       _UpperCamelCase=3_072       ,       _UpperCamelCase="gelu"       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=0.0       ,       _UpperCamelCase=0.02       ,       _UpperCamelCase=1e-1_2       ,       _UpperCamelCase=224       ,       _UpperCamelCase=16       ,       _UpperCamelCase=3       ,       _UpperCamelCase=False       ,       _UpperCamelCase=False       ,       _UpperCamelCase=False       ,       _UpperCamelCase=False       ,       _UpperCamelCase=0.1       ,       _UpperCamelCase=0.1       ,       _UpperCamelCase=True       ,       _UpperCamelCase=[3, 5, 7, 11]       ,       _UpperCamelCase=[1, 2, 3, 6]       ,       _UpperCamelCase=True       ,       _UpperCamelCase=0.4       ,       _UpperCamelCase=256       ,       _UpperCamelCase=1       ,       _UpperCamelCase=False       ,       _UpperCamelCase=255       ,       **_UpperCamelCase       ,       )       ->   List[str]:
					super().__init__(**_UpperCamelCase  )

					lowerCAmelCase_      			=			hidden_size
					lowerCAmelCase_      			=			num_hidden_layers
					lowerCAmelCase_      			=			num_attention_heads
					lowerCAmelCase_      			=			intermediate_size
					lowerCAmelCase_      			=			hidden_act
					lowerCAmelCase_      			=			hidden_dropout_prob
					lowerCAmelCase_      			=			attention_probs_dropout_prob
					lowerCAmelCase_      			=			initializer_range
					lowerCAmelCase_      			=			layer_norm_eps

					lowerCAmelCase_      			=			image_size
					lowerCAmelCase_      			=			patch_size
					lowerCAmelCase_      			=			num_channels
					lowerCAmelCase_      			=			use_mask_token
					lowerCAmelCase_      			=			use_absolute_position_embeddings
					lowerCAmelCase_      			=			use_relative_position_bias
					lowerCAmelCase_      			=			use_shared_relative_position_bias
					lowerCAmelCase_      			=			layer_scale_init_value
					lowerCAmelCase_      			=			drop_path_rate
					lowerCAmelCase_      			=			use_mean_pooling
					# decode head attributes (semantic segmentation)
					lowerCAmelCase_      			=			out_indices
					lowerCAmelCase_      			=			pool_scales
					# auxiliary head attributes (semantic segmentation)
					lowerCAmelCase_      			=			use_auxiliary_head
					lowerCAmelCase_      			=			auxiliary_loss_weight
					lowerCAmelCase_      			=			auxiliary_channels
					lowerCAmelCase_      			=			auxiliary_num_convs
					lowerCAmelCase_      			=			auxiliary_concat_input
					lowerCAmelCase_      			=			semantic_loss_ignore_index





class 			_lowerCAmelCase      (			__a ):
				_lowercase    	=version.parse('''1.11''' )




				@property
				def   __a		(      self  )       ->   Mapping[str, Mapping[int, str]]:
					return OrderedDict(
					    [
					        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
					    ]  )




				@property
				def   __a		(      self  )       ->   float:
					return 1e-4





import functools






def      lowerCamelCase__       (       __lowerCAmelCase						:						str					,							__lowerCAmelCase						:						str       ):




			"""simple docstring"""


			lowerCAmelCase_      			=			len(__lowerCAmelCase       )
			lowerCAmelCase_      			=			len(__lowerCAmelCase       )

			@functools.cache
			def min_distance(__lowerCAmelCase						:						int					,							__lowerCAmelCase						:						int       ) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						lowerCAmelCase_      			=			int(worda[indexa] != worda[indexa]       )  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1					,							__lowerCAmelCase       )					,							1 + min_distance(__lowerCAmelCase					,							indexa + 1       )					,							diff + min_distance(indexa + 1					,							indexa + 1       )					,							)

			return min_distance(0					,							0       )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



