





"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase_     :						str						=					logging.get_logger(__name__)

lowerCamelCase_     :						List[Any]						=					{
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}

class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''
      lowercase_      : Dict	    =   """roberta-prelayernorm"""

      def __init__(     self					,      snake_case_=5_0_2_6_5					,      snake_case_=7_6_8					,      snake_case_=1_2					,      snake_case_=1_2					,      snake_case_=3_0_7_2					,      snake_case_="gelu"					,      snake_case_=0.1					,      snake_case_=0.1					,      snake_case_=5_1_2					,      snake_case_=2					,      snake_case_=0.02					,      snake_case_=1E-12					,      snake_case_=1					,      snake_case_=0					,      snake_case_=2					,      snake_case_="absolute"					,      snake_case_=True					,      snake_case_=None					,      **snake_case_					,      ):

        """simple docstring"""

        super().__init__(pad_token_id=snake_case_					,      bos_token_id=snake_case_					,      eos_token_id=snake_case_					,      **snake_case_  )

        A_  :       List[Any]										=  vocab_size
        A_  :       Union[str, Any]										=  hidden_size
        A_  :       Union[str, Any]										=  num_hidden_layers
        A_  :       Dict										=  num_attention_heads
        A_  :       Tuple										=  hidden_act
        A_  :       Optional[int]										=  intermediate_size
        A_  :       Dict										=  hidden_dropout_prob
        A_  :       Optional[int]										=  attention_probs_dropout_prob
        A_  :       Any										=  max_position_embeddings
        A_  :       Dict										=  type_vocab_size
        A_  :       int										=  initializer_range
        A_  :       Tuple										=  layer_norm_eps
        A_  :       Any										=  position_embedding_type
        A_  :       Optional[Any]										=  use_cache
        A_  :       Tuple										=  classifier_dropout


class  _UpperCAmelCase  (   UpperCAmelCase__		):



      '''simple docstring'''

      @property
      def 					lowerCamelCase_			(     self  ):

        """simple docstring"""

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






"""simple docstring"""




def 						UpperCAmelCase__		(     _UpperCAmelCase					):






  """simple docstring"""





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

  if num == 0:
    return "0b0"

  A_  :       str										=  False

  if num < 0:
    A_  :       Dict										=  True
    A_  :       Union[str, Any]										=  -num

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

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

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


if __name__ == "__main__":
   import doctest

   doctest.testmod()