





'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


a        =						logging.get_logger(__name__)

a        =						{
    "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 (   __lowerCAmelCase			):
   __UpperCamelCase   : Any	      =	"xlm-roberta-xl"





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

      '''simple docstring'''

      super().__init__(pad_token_id=lowerCamelCase__				,bos_token_id=lowerCamelCase__				,eos_token_id=lowerCamelCase__				,**lowerCamelCase__    )
      __SCREAMING_SNAKE_CASE      							=       vocab_size
      __SCREAMING_SNAKE_CASE      							=       hidden_size
      __SCREAMING_SNAKE_CASE      							=       num_hidden_layers
      __SCREAMING_SNAKE_CASE      							=       num_attention_heads
      __SCREAMING_SNAKE_CASE      							=       hidden_act
      __SCREAMING_SNAKE_CASE      							=       intermediate_size
      __SCREAMING_SNAKE_CASE      							=       hidden_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE      							=       max_position_embeddings
      __SCREAMING_SNAKE_CASE      							=       type_vocab_size
      __SCREAMING_SNAKE_CASE      							=       initializer_range
      __SCREAMING_SNAKE_CASE      							=       layer_norm_eps
      __SCREAMING_SNAKE_CASE      							=       position_embedding_type
      __SCREAMING_SNAKE_CASE      							=       use_cache
      __SCREAMING_SNAKE_CASE      							=       classifier_dropout







class __a (   __lowerCAmelCase			):





   @property
   def      UpperCAmelCase__     (					self				:			Tuple    ):

      '''simple docstring'''

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







'''simple docstring'''

def 						__magic_name__       (							__UpperCAmelCase = 1							,	__UpperCAmelCase = 1000      )						->					int:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE      							=       1
   __SCREAMING_SNAKE_CASE      							=       0

   for divide_by_number in range(__UpperCAmelCase							,	digit + 1      ):
      __SCREAMING_SNAKE_CASE      							=       []
      __SCREAMING_SNAKE_CASE      							=       numerator
      for _ in range(1							,	digit + 1      ):
         if now_divide in has_been_divided:
            if longest_list_length < len(__UpperCAmelCase      ):
               __SCREAMING_SNAKE_CASE      							=       len(__UpperCAmelCase      )
               __SCREAMING_SNAKE_CASE      							=       divide_by_number
         else:
            has_been_divided.append(__UpperCAmelCase      )
            __SCREAMING_SNAKE_CASE      							=       now_divide * 10 % divide_by_number

   return the_digit


# Tests
if __name__ == "__main__":
    import doctest

    doctest.testmod()





