





from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase_							=				logging.get_logger(__name__)

UpperCAmelCase_							=				{
    'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json',
    'google/bigbird-roberta-large': 'https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json',
    'google/bigbird-base-trivia-itc': 'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}
class     UpperCamelCase__					(     lowercase_				):






		'''simple docstring'''






		__a       :       Any       =	"""big_bird"""






		def __init__(							self,   snake_case__=5_03_58,   snake_case__=7_68,   snake_case__=12,   snake_case__=12,   snake_case__=30_72,   snake_case__="gelu_new",   snake_case__=0.1,   snake_case__=0.1,   snake_case__=40_96,   snake_case__=2,   snake_case__=0.02,   snake_case__=1E-12,   snake_case__=True,   snake_case__=0,   snake_case__=1,   snake_case__=2,   snake_case__=66,   snake_case__="block_sparse",   snake_case__=True,   snake_case__=False,   snake_case__=64,   snake_case__=3,   snake_case__=None,   **snake_case__,   )       -> str:






									"""simple docstring"""
									super().__init__(
									    pad_token_id=snake_case__,   bos_token_id=snake_case__,   eos_token_id=snake_case__,   sep_token_id=snake_case__,   **snake_case__,   )

									lowercase_	:   Optional[Any]  				=     vocab_size
									lowercase_	:   str  				=     max_position_embeddings
									lowercase_	:   Any  				=     hidden_size
									lowercase_	:   Dict  				=     num_hidden_layers
									lowercase_	:   int  				=     num_attention_heads
									lowercase_	:   List[str]  				=     intermediate_size
									lowercase_	:   int  				=     hidden_act
									lowercase_	:   int  				=     hidden_dropout_prob
									lowercase_	:   Tuple  				=     attention_probs_dropout_prob
									lowercase_	:   int  				=     initializer_range
									lowercase_	:   Union[str, Any]  				=     type_vocab_size
									lowercase_	:   Tuple  				=     layer_norm_eps
									lowercase_	:   Any  				=     use_cache

									lowercase_	:   Union[str, Any]  				=     rescale_embeddings
									lowercase_	:   Dict  				=     attention_type
									lowercase_	:   Optional[Any]  				=     use_bias
									lowercase_	:   str  				=     block_size
									lowercase_	:   Tuple  				=     num_random_blocks
									lowercase_	:   Optional[int]  				=     classifier_dropout




class     UpperCamelCase__					(     lowercase_				):






		'''simple docstring'''






		@property
		def 						snake_case__				(							self  )       -> List[Any]:






									"""simple docstring"""







									if self.task == "multiple-choice":
																lowercase_	:   List[Any]  				=     {0: """batch""", 1: """choice""", 2: """sequence"""}
									else:
																lowercase_	:   Any  				=     {0: """batch""", 1: """sequence"""}
									return OrderedDict(
									    [
									        ("""input_ids""", dynamic_axis),
									        ("""attention_mask""", dynamic_axis),
									    ]  )



'''simple docstring'''

from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class     __lowerCAmelCase		:





      '''simple docstring'''






      lowerCAmelCase__   :	int
      lowerCAmelCase__   :	TreeNode | None       =				None
      lowerCAmelCase__   :	TreeNode | None       =				None






lowerCamelCase				:  Optional[Any]    		=      namedtuple('CoinsDistribResult', 'moves excess')

def _SCREAMING_SNAKE_CASE (A			)			->			int:






       """simple docstring"""







       if root is None:
              return 0

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

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

       def count_coins(A			) -> int:
              if node is None:
                     return 0

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

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

       # Main calculation
       def get_distrib(A			) -> CoinsDistribResult:

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

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

              lowercase__      =					1 - left_distrib_excess
              lowercase__      =					1 - right_distrib_excess

              lowercase__      =					(
                  left_distrib_moves
                  + right_distrib_moves
                  + abs(A			)
                  + abs(A			)
              )
              lowercase__      =					node.data - coins_to_left - coins_to_right

              return CoinsDistribResult(A    ,					A			)

       return get_distrib(A			)[0]


if __name__ == "__main__":
 import doctest

 doctest.testmod()




