from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase     :					Any				  =						logging.get_logger(__name__)

__lowerCamelCase     :					Union[str, Any]				  =						{
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}







class __snake_case							(		lowerCamelCase_						):
   lowerCAmelCase_								=				"rembert"




   def __init__(       self     :							Tuple			,      _lowercase     :							Union[str, Any]=25_03_00			,      _lowercase     :							List[str]=11_52			,      _lowercase     :							Optional[int]=32			,      _lowercase     :							Any=18			,      _lowercase     :							List[Any]=2_56			,      _lowercase     :							Any=16_64			,      _lowercase     :							Union[str, Any]=46_08			,      _lowercase     :							List[Any]="gelu"			,      _lowercase     :							Optional[int]=0.0			,      _lowercase     :							Optional[int]=0.0			,      _lowercase     :							Dict=0.1			,      _lowercase     :							Tuple=5_12			,      _lowercase     :							List[str]=2			,      _lowercase     :							Any=0.02			,      _lowercase     :							Tuple=1E-12			,      _lowercase     :							List[str]=True			,      _lowercase     :							int=0			,      _lowercase     :							Union[str, Any]=3_12			,      _lowercase     :							Dict=3_13			,      **_lowercase     :							Tuple			,      ):



     """simple docstring"""






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

     SCREAMING_SNAKE_CASE__     				= vocab_size
     SCREAMING_SNAKE_CASE__     				= input_embedding_size
     SCREAMING_SNAKE_CASE__     				= output_embedding_size
     SCREAMING_SNAKE_CASE__     				= max_position_embeddings
     SCREAMING_SNAKE_CASE__     				= hidden_size
     SCREAMING_SNAKE_CASE__     				= num_hidden_layers
     SCREAMING_SNAKE_CASE__     				= num_attention_heads
     SCREAMING_SNAKE_CASE__     				= intermediate_size
     SCREAMING_SNAKE_CASE__     				= hidden_act
     SCREAMING_SNAKE_CASE__     				= hidden_dropout_prob
     SCREAMING_SNAKE_CASE__     				= attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__     				= classifier_dropout_prob
     SCREAMING_SNAKE_CASE__     				= initializer_range
     SCREAMING_SNAKE_CASE__     				= type_vocab_size
     SCREAMING_SNAKE_CASE__     				= layer_norm_eps
     SCREAMING_SNAKE_CASE__     				= use_cache
     SCREAMING_SNAKE_CASE__     				= False







class __snake_case							(		lowerCamelCase_						):




   @property
   def       __a		(       self     :							int ):



     """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),
             ("""token_type_ids""", dynamic_axis),
         ] )




   @property
   def       __a		(       self     :							Optional[int] ):



     """simple docstring"""






     return 1E-4

from __future__ import annotations



def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			str      )				->   bool:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= 42
  SCREAMING_SNAKE_CASE__     				= list(__UpperCamelCase      )
  SCREAMING_SNAKE_CASE__				,	SCREAMING_SNAKE_CASE__     				= _vector[:-1], int(_vector[-1]      )
  SCREAMING_SNAKE_CASE__     				= [int(__UpperCamelCase      ) for digit in __vector]

  vector.reverse()
  for i, digit in enumerate(__UpperCamelCase      ):
    if i & 1 == 0:
      SCREAMING_SNAKE_CASE__     				= digit * 2
      if doubled > 9:
        doubled -= 9
      check_digit += doubled
    else:
      check_digit += digit

  return check_digit % 10 == 0


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   assert is_luhn('''79927398713''')
   assert not is_luhn('''79927398714''')
