




from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


lowerCamelCase       :	Dict									=     {
    "susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
    "susnato/ernie-m-large_pytorch": "https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json",
}







class 						A(		_UpperCAmelCase     ):



 '''simple docstring'''


 UpperCamelCase		     =		'''ernie_m'''
 UpperCamelCase		     =		{'''dropout''': '''classifier_dropout''', '''num_classes''': '''num_labels'''}

 def __init__(       self      :						Dict		,							A_      :						int = 250002		,							A_      :						int = 768		,							A_      :						int = 12		,							A_      :						int = 12		,							A_      :						int = 3072		,							A_      :						str = "gelu"		,							A_      :						float = 0.1		,							A_      :						float = 0.1		,							A_      :						int = 514		,							A_      :						float = 0.02		,							A_      :						int = 1		,							A_      :						float = 1E-05		,							A_      :						Any=None		,							A_      :						Any=False		,							A_      :						Dict=0.0		,							**A_      :						List[str]		,							)     ->			int:

       """simple docstring"""






       super().__init__(pad_token_id=lowerCamelCase_		,							**lowerCamelCase_						)
       lowerCamelCase_	  =					vocab_size
       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_	  =					max_position_embeddings
       lowerCamelCase_	  =					initializer_range
       lowerCamelCase_	  =					layer_norm_eps
       lowerCamelCase_	  =					classifier_dropout
       lowerCamelCase_	  =					is_decoder
       lowerCamelCase_	  =					act_dropout





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()



