
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__lowerCamelCase				=			logging.get_logger(__name__)

__lowerCamelCase				=			{
    """shi-labs/dinat-mini-in1k-224""": """https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json""",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}






class     UpperCAmelCase						(		A_			,A_					):
   A__   :						Optional[Any]			=	"dinat"

   A__   :						List[str]			=	{
       "num_attention_heads": "num_heads",
       "num_hidden_layers": "num_layers",
   }



   def __init__(self						:   List[str]       ,		snake_case__						:   Optional[int]=4       ,		snake_case__						:   List[Any]=3       ,		snake_case__						:   Optional[Any]=64       ,		snake_case__						:   List[Any]=[3, 4, 6, 5]       ,		snake_case__						:   Dict=[2, 4, 8, 16]       ,		snake_case__						:   Dict=7       ,		snake_case__						:   Optional[int]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]       ,		snake_case__						:   Tuple=3.0       ,		snake_case__						:   Optional[int]=True       ,		snake_case__						:   List[str]=0.0       ,		snake_case__						:   List[str]=0.0       ,		snake_case__						:   Dict=0.1       ,		snake_case__						:   Any="gelu"       ,		snake_case__						:   Optional[Any]=0.02       ,		snake_case__						:   int=1e-5       ,		snake_case__						:   Optional[Any]=0.0       ,		snake_case__						:   List[Any]=None       ,		snake_case__						:   str=None       ,		**snake_case__						:   List[Any]       ,		)						->      int:


          '''simple docstring'''


          super().__init__(**snake_case__					)

          snake_case			:  List[Any]     							= patch_size
          snake_case			:  Union[str, Any]     							= num_channels
          snake_case			:  List[Any]     							= embed_dim
          snake_case			:  int     							= depths
          snake_case			:  Dict     							= len(snake_case__					)
          snake_case			:  Optional[int]     							= num_heads
          snake_case			:  int     							= kernel_size
          snake_case			:  int     							= dilations
          snake_case			:  Optional[Any]     							= mlp_ratio
          snake_case			:  List[Any]     							= qkv_bias
          snake_case			:  Optional[Any]     							= hidden_dropout_prob
          snake_case			:  Tuple     							= attention_probs_dropout_prob
          snake_case			:  Dict     							= drop_path_rate
          snake_case			:  List[str]     							= hidden_act
          snake_case			:  Tuple     							= layer_norm_eps
          snake_case			:  Union[str, Any]     							= initializer_range
          # we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          snake_case			:  Dict     							= int(embed_dim * 2 ** (len(snake_case__					) - 1)					)
          snake_case			:  int     							= layer_scale_init_value
          snake_case			:  List[str]     							= ["stem"] + [f"""stage{idx}""" for idx in range(1       ,		len(snake_case__					) + 1					)]
          snake_case							,   snake_case			:  Dict     							= get_aligned_output_features_output_indices(
              out_features=snake_case__       ,		out_indices=snake_case__       ,		stage_names=self.stage_names					)







def      UpperCamelCase   (       __lowerCamelCase	:					str = "The quick brown fox jumps over the lazy dog"							,   ):
       snake_case			:  Dict     							= set()

       # Replace all the whitespace in our sentence
       snake_case			:  List[Any]     							= input_str.replace(" "							,   ""       )
       for alpha in input_str:
              if "a" <= alpha.lower() <= "z":
                     frequency.add(alpha.lower()       )
       return len(__lowerCamelCase       ) == 26


def      UpperCamelCase   (       __lowerCamelCase	:					str = "The quick brown fox jumps over the lazy dog"							,   ):
       snake_case			:  Optional[int]     							= [False] * 26
       for char in input_str:
              if char.islower():
                     snake_case			:  Dict     							= True
              elif char.isupper():
                     snake_case			:  Optional[Any]     							= True
       return all(__lowerCamelCase       )


def      UpperCamelCase   (       __lowerCamelCase	:					str = "The quick brown fox jumps over the lazy dog"							,   ):
       return len({char for char in input_str.lower() if char.isalpha()}       ) == 26


def      UpperCamelCase   (       ):
       from timeit import timeit

       snake_case			:  Tuple     							= "from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"
       print(timeit("is_pangram()"							,   setup=__lowerCamelCase       )       )
       print(timeit("is_pangram_faster()"							,   setup=__lowerCamelCase       )       )
       print(timeit("is_pangram_fastest()"							,   setup=__lowerCamelCase       )       )
       # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
       # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   benchmark()





