





def   lowerCAmelCase_				( __a	)  ->	int:







  """simple docstring"""





  if a < 0:
    raise ValueError("Input value must be a positive integer"	)
  elif isinstance(__a			,					__a	):
    raise TypeError("Input value must be a 'int' type"	)
  return bin(__a	).count("1"	)


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


__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      _SCREAMING_SNAKE_CASE		(			__SCREAMING_SNAKE_CASE					):







 '''simple docstring'''
 lowercase_	=    "xlm-roberta-xl"

 def __init__(self       :     Tuple ,				UpperCAmelCase_       :     Union[str, Any]=250_880 ,				UpperCAmelCase_       :     Optional[int]=2_560 ,				UpperCAmelCase_       :     Union[str, Any]=36 ,				UpperCAmelCase_       :     str=32 ,				UpperCAmelCase_       :     Dict=10_240 ,				UpperCAmelCase_       :     Optional[int]="gelu" ,				UpperCAmelCase_       :     Tuple=0.1 ,				UpperCAmelCase_       :     List[Any]=0.1 ,				UpperCAmelCase_       :     List[Any]=514 ,				UpperCAmelCase_       :     List[Any]=1 ,				UpperCAmelCase_       :     Dict=0.02 ,				UpperCAmelCase_       :     Dict=1E-0_5 ,				UpperCAmelCase_       :     int=1 ,				UpperCAmelCase_       :     Dict=0 ,				UpperCAmelCase_       :     Optional[Any]=2 ,				UpperCAmelCase_       :     Union[str, Any]="absolute" ,				UpperCAmelCase_       :     str=True ,				UpperCAmelCase_       :     str=None ,				**UpperCAmelCase_       :     List[str] ,				) ->int:



   '''simple docstring'''



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



class      _SCREAMING_SNAKE_CASE		(			__SCREAMING_SNAKE_CASE					):







 '''simple docstring'''

 @property
 def 							SCREAMING_SNAKE_CASE_      (self       :     List[Any]) ->Mapping[str, Mapping[int, str]]:



   '''simple docstring'''



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

