from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__		:					Tuple						=					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__		:					Optional[Any]						=					{
    "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       snake_case					(      UpperCamelCase_						):
		lowercase_			=     'xlm-roberta-xl'




		def __init__(      self     :	List[Any]     , a_     :	Optional[int]=25_0880     , a_     :	Optional[Any]=2560     , a_     :	List[Any]=36     , a_     :	Union[str, Any]=32     , a_     :	List[Any]=1_0240     , a_     :	Union[str, Any]="gelu"     , a_     :	Optional[Any]=0.1     , a_     :	int=0.1     , a_     :	List[str]=514     , a_     :	List[str]=1     , a_     :	Union[str, Any]=0.02     , a_     :	Union[str, Any]=1e-0_5     , a_     :	Any=1     , a_     :	int=0     , a_     :	List[Any]=2     , a_     :	Any="absolute"     , a_     :	str=True     , a_     :	Any=None     , **a_     :	Union[str, Any]     , )->       int:




							"""simple docstring"""
							super().__init__(pad_token_id=a_     , bos_token_id=a_     , eos_token_id=a_     , **a_				)
							SCREAMING_SNAKE_CASE__				:				str			=		vocab_size
							SCREAMING_SNAKE_CASE__				:				int			=		hidden_size
							SCREAMING_SNAKE_CASE__				:				str			=		num_hidden_layers
							SCREAMING_SNAKE_CASE__				:				List[str]			=		num_attention_heads
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		hidden_act
							SCREAMING_SNAKE_CASE__				:				Any			=		intermediate_size
							SCREAMING_SNAKE_CASE__				:				Tuple			=		hidden_dropout_prob
							SCREAMING_SNAKE_CASE__				:				Tuple			=		attention_probs_dropout_prob
							SCREAMING_SNAKE_CASE__				:				List[str]			=		max_position_embeddings
							SCREAMING_SNAKE_CASE__				:				List[Any]			=		type_vocab_size
							SCREAMING_SNAKE_CASE__				:				Tuple			=		initializer_range
							SCREAMING_SNAKE_CASE__				:				List[str]			=		layer_norm_eps
							SCREAMING_SNAKE_CASE__				:				str			=		position_embedding_type
							SCREAMING_SNAKE_CASE__				:				str			=		use_cache
							SCREAMING_SNAKE_CASE__				:				int			=		classifier_dropout




class       snake_case					(      UpperCamelCase_						):




		@property
		def 	__lowercase(      self     :	int				)->       Mapping[str, Mapping[int, str]]:




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




from __future__ import annotations







def     _a				(      lowercase__  :			list[int | float]     ,  lowercase__  :			int     ,  lowercase__  :			int ):







     '''simple docstring'''


     if len(lowercase__ ) == 0:
          raise ValueError('find_max() arg is an empty sequence' )
     if (
         left >= len(lowercase__ )
         or left < -len(lowercase__ )
         or right >= len(lowercase__ )
         or right < -len(lowercase__ )
     ):
          raise IndexError('list index out of range' )
     if left == right:
          return nums[left]
     SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		(left + right) >> 1  # the middle
     SCREAMING_SNAKE_CASE__				:				int			=		find_max(lowercase__     ,  lowercase__     ,  lowercase__ )  # find max in range[left, mid]
     SCREAMING_SNAKE_CASE__				:				Tuple			=		find_max(lowercase__     ,  mid + 1     ,  lowercase__ )  # find max in range[mid + 1, right]

     return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
      import doctest

      doctest.testmod(verbose=True)



