






"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase    :   List[Any]   			=						logging.get_logger(__name__)

_UpperCamelCase    :   Optional[int]   			=						{
    '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  (  a__	):
    __magic_name__   					=					"xlm-roberta-xl"





    def __init__(							self     : List[Any]    ,		A     : Dict=2_5_0_8_8_0    ,		A     : Dict=2_5_6_0    ,		A     : Dict=3_6    ,		A     : Optional[int]=3_2    ,		A     : str=1_0_2_4_0    ,		A     : int="gelu"    ,		A     : Optional[int]=0.1    ,		A     : Dict=0.1    ,		A     : Dict=5_1_4    ,		A     : Tuple=1    ,		A     : Dict=0.02    ,		A     : int=1E-05    ,		A     : Tuple=1    ,		A     : Any=0    ,		A     : Union[str, Any]=2    ,		A     : Any="absolute"    ,		A     : Dict=True    ,		A     : int=None    ,		**A     : List[str]    ,		):


      '''simple docstring'''




      super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_    ,		bos_token_id=SCREAMING_SNAKE_CASE_    ,		eos_token_id=SCREAMING_SNAKE_CASE_    ,		**SCREAMING_SNAKE_CASE_      )
      a					:      str    =       vocab_size
      a					:      List[Any]    =       hidden_size
      a					:      Tuple    =       num_hidden_layers
      a					:      Tuple    =       num_attention_heads
      a					:      str    =       hidden_act
      a					:      str    =       intermediate_size
      a					:      Dict    =       hidden_dropout_prob
      a					:      str    =       attention_probs_dropout_prob
      a					:      Tuple    =       max_position_embeddings
      a					:      List[str]    =       type_vocab_size
      a					:      Union[str, Any]    =       initializer_range
      a					:      Any    =       layer_norm_eps
      a					:      Tuple    =       position_embedding_type
      a					:      Any    =       use_cache
      a					:      Optional[int]    =       classifier_dropout






class 						snake_case  (  a__	):





    @property
    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




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












"""simple docstring"""


def       snake_case  (A_				:int				):







  '''simple docstring'''

  if isinstance(A_     ,      A_				):
    raise TypeError('\'float\' object cannot be interpreted as an integer'				)
  if isinstance(A_     ,      A_				):
    raise TypeError('\'str\' object cannot be interpreted as an integer'				)

  if num == 0:
    return "0b0"

  a					:      List[Any]    =       False

  if num < 0:
    a					:      Optional[int]    =       True
    a					:      Dict    =       -num

  a					:      list[int]    =       []
  while num > 0:
    binary.insert(0     ,      num % 2				)
    num >>= 1

  if negative:
    return "-0b" + "".join(str(A_				) for e in binary				)

  return "0b" + "".join(str(A_				) for e in binary				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()




