


from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass





@dataclass
class  _a							:
	_a  :  str				   =							42
	_a  :  Optional[Any]				   =							None
	_a  :  int				   =							None
lowerCamelCase						=		namedtuple('''CoinsDistribResult''', '''moves excess''')






def 					lowerCamelCase_   (	_a	):




		"""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(lowercase__	) != count_coins(lowercase__	):
				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	)

				lowerCAmelCase__       :      str   					= get_distrib(node.left	)
				lowerCAmelCase__       :      str   					= get_distrib(node.right	)

				lowerCAmelCase__       :      Optional[Any]   					= 1 - left_distrib_excess
				lowerCAmelCase__       :      Tuple   					= 1 - right_distrib_excess

				lowerCAmelCase__       :      Optional[Any]   					= (
				    left_distrib_moves
				    + right_distrib_moves
				    + abs(lowercase__	)
				    + abs(lowercase__	)
				)
				lowerCAmelCase__       :      Tuple   					= node.data - coins_to_left - coins_to_right

				return CoinsDistribResult(lowercase__     ,       lowercase__	)

		return get_distrib(lowercase__	)[0]


if __name__ == "__main__":
		import doctest

		doctest.testmod()








from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase						=		logging.get_logger(__name__)

lowerCamelCase						=		{
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}





class  _a							(    _lowercase):
	_a  :  Optional[int]				   =							'''xlm-roberta-xl'''




	def __init__( self						:		Any		, _SCREAMING_SNAKE_CASE						:		str=25_0880		, _SCREAMING_SNAKE_CASE						:		Optional[Any]=2560		, _SCREAMING_SNAKE_CASE						:		int=36		, _SCREAMING_SNAKE_CASE						:		Optional[int]=32		, _SCREAMING_SNAKE_CASE						:		Any=1_0240		, _SCREAMING_SNAKE_CASE						:		List[str]="gelu"		, _SCREAMING_SNAKE_CASE						:		Optional[Any]=0.1		, _SCREAMING_SNAKE_CASE						:		Dict=0.1		, _SCREAMING_SNAKE_CASE						:		Optional[int]=514		, _SCREAMING_SNAKE_CASE						:		Optional[int]=1		, _SCREAMING_SNAKE_CASE						:		Tuple=0.02		, _SCREAMING_SNAKE_CASE						:		Dict=1E-05		, _SCREAMING_SNAKE_CASE						:		Tuple=1		, _SCREAMING_SNAKE_CASE						:		Optional[int]=0		, _SCREAMING_SNAKE_CASE						:		Tuple=2		, _SCREAMING_SNAKE_CASE						:		Union[str, Any]="absolute"		, _SCREAMING_SNAKE_CASE						:		Any=True		, _SCREAMING_SNAKE_CASE						:		Any=None		, **_SCREAMING_SNAKE_CASE						:		Tuple		, )->	str:
			super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE		, bos_token_id=_SCREAMING_SNAKE_CASE		, eos_token_id=_SCREAMING_SNAKE_CASE		, **_SCREAMING_SNAKE_CASE		)
			lowerCAmelCase__       :      Any   					= vocab_size
			lowerCAmelCase__       :      List[Any]   					= hidden_size
			lowerCAmelCase__       :      int   					= num_hidden_layers
			lowerCAmelCase__       :      Dict   					= num_attention_heads
			lowerCAmelCase__       :      str   					= hidden_act
			lowerCAmelCase__       :      List[Any]   					= intermediate_size
			lowerCAmelCase__       :      Tuple   					= hidden_dropout_prob
			lowerCAmelCase__       :      str   					= attention_probs_dropout_prob
			lowerCAmelCase__       :      List[str]   					= max_position_embeddings
			lowerCAmelCase__       :      Any   					= type_vocab_size
			lowerCAmelCase__       :      Optional[Any]   					= initializer_range
			lowerCAmelCase__       :      Optional[int]   					= layer_norm_eps
			lowerCAmelCase__       :      Optional[int]   					= position_embedding_type
			lowerCAmelCase__       :      Any   					= use_cache
			lowerCAmelCase__       :      List[Any]   					= classifier_dropout





class  _a							(    _lowercase):




	@property
	def 							UpperCAmelCase__( self						:		Any		)->	Mapping[str, Mapping[int, str]]:
			if self.task == "multiple-choice":
					lowerCAmelCase__       :      int   					= {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
			else:
					lowerCAmelCase__       :      List[Any]   					= {0: '''batch''', 1: '''sequence'''}
			return OrderedDict(
			    [
			        ('''input_ids''', dynamic_axis),
			        ('''attention_mask''', dynamic_axis),
			    ]		)




