




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


lowerCamelCase       :	List[Any]									=     logging.get_logger(__name__)

lowerCamelCase       :	Optional[int]									=     {
    "shi-labs/nat-mini-in1k-224": "https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json",
    # See all Nat models at https://huggingface.co/models?filter=nat
}







class 						A(		UpperCamelCase							,   UpperCamelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		'''nat'''

 UpperCamelCase		     =		{
     '''num_attention_heads''': '''num_heads''',
     '''num_hidden_layers''': '''num_layers''',
 }

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

       """simple docstring"""






       super().__init__(**A_						)

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









from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass







@dataclass
class 						A:



 '''simple docstring'''


 UpperCamelCase		     =		42
 UpperCamelCase		     =		None
 UpperCamelCase		     =		None

lowerCamelCase       :	str									=     namedtuple("CoinsDistribResult", "moves excess")

def     _SCREAMING_SNAKE_CASE    (							lowercase			: TreeNode | None  ):


      '''simple docstring'''



      if root is None:
            return 0

      # Validation
      def count_nodes(lowercase			: TreeNode | None  ) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left  ) + count_nodes(node.right  ) + 1

      def count_coins(lowercase			: TreeNode | None  ) -> int:
            if node is None:
                  return 0

            return count_coins(node.left  ) + count_coins(node.right  ) + node.data

      if count_nodes(lowercase  ) != count_coins(lowercase  ):
            raise ValueError('The nodes number should be same as the number of coins'  )

      # Main calculation
      def get_distrib(lowercase			: TreeNode | None  ) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0			,							1  )

            lowerCamelCase_  ,       lowerCamelCase_	  =					get_distrib(node.left  )
            lowerCamelCase_  ,       lowerCamelCase_	  =					get_distrib(node.right  )

            lowerCamelCase_	  =					1 - left_distrib_excess
            lowerCamelCase_	  =					1 - right_distrib_excess

            lowerCamelCase_	  =					(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowercase  )
                + abs(lowercase  )
            )
            lowerCamelCase_	  =					node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowercase			,							lowercase  )

      return get_distrib(lowercase  )[0]


if __name__ == "__main__":
 import doctest

 doctest.testmod()



