




'''simple docstring'''



lowerCamelCase_			=						{
    "a": "AAAAA",
    "b": "AAAAB",
    "c": "AAABA",
    "d": "AAABB",
    "e": "AABAA",
    "f": "AABAB",
    "g": "AABBA",
    "h": "AABBB",
    "i": "ABAAA",
    "j": "BBBAA",
    "k": "ABAAB",
    "l": "ABABA",
    "m": "ABABB",
    "n": "ABBAA",
    "o": "ABBAB",
    "p": "ABBBA",
    "q": "ABBBB",
    "r": "BAAAA",
    "s": "BAAAB",
    "t": "BAABA",
    "u": "BAABB",
    "v": "BBBAB",
    "w": "BABAA",
    "x": "BABAB",
    "y": "BABBA",
    "z": "BABBB",
    " ": " ",
}


lowerCamelCase_			=						{value: key for key, value in encode_dict.items()}
def 			SCREAMING_SNAKE_CASE_			(							__A    :			Union[str, Any]  )			->			str:
   _SCREAMING_SNAKE_CASE	=				''
   for letter in word.lower():
      if letter.isalpha() or letter == " ":
         encoded += encode_dict[letter]
      else:
         raise Exception("encode() accepts only letters of the alphabet and spaces"  )
   return encoded
def 			SCREAMING_SNAKE_CASE_			(							__A    :			Dict  )			->			str:
   if set(lowerCamelCase_  ) - {"A", "B", " "} != set():
      raise Exception("decode() accepts only \'A\', \'B\' and spaces"  )
   _SCREAMING_SNAKE_CASE	=				''
   for word in coded.split():
      while len(lowerCamelCase_  ) != 0:
         decoded += decode_dict[word[:5]]
         _SCREAMING_SNAKE_CASE	=				word[5:]
      decoded += " "
   return decoded.strip()


if __name__ == "__main__":
 from doctest import testmod

 testmod()







'''simple docstring'''



from ...configuration_utils import PretrainedConfig







class 		lowercase_   (			A       ):


   """simple docstring"""

   lowerCamelCase_      =						'''bert-generation'''



   def __init__(   self :     int  ,				__lowerCamelCase :     int=5_0_3_5_8  ,				__lowerCamelCase :     Union[str, Any]=1_0_2_4  ,				__lowerCamelCase :     str=2_4  ,				__lowerCamelCase :     int=1_6  ,				__lowerCamelCase :     Union[str, Any]=4_0_9_6  ,				__lowerCamelCase :     Optional[Any]="gelu"  ,				__lowerCamelCase :     Tuple=0.1  ,				__lowerCamelCase :     str=0.1  ,				__lowerCamelCase :     Optional[Any]=5_1_2  ,				__lowerCamelCase :     List[Any]=0.0_2  ,				__lowerCamelCase :     Union[str, Any]=1e-12  ,				__lowerCamelCase :     List[Any]=0  ,				__lowerCamelCase :     List[Any]=2  ,				__lowerCamelCase :     Dict=1  ,				__lowerCamelCase :     Tuple="absolute"  ,				__lowerCamelCase :     Union[str, Any]=True  ,				**__lowerCamelCase :     Optional[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	=				initializer_range
      _SCREAMING_SNAKE_CASE	=				layer_norm_eps
      _SCREAMING_SNAKE_CASE	=				position_embedding_type
      _SCREAMING_SNAKE_CASE	=				use_cache

