




'''simple docstring'''



def 			SCREAMING_SNAKE_CASE_			(							__A    :			str	,					__A    :			int  )			->			list:
   _SCREAMING_SNAKE_CASE	=				word.split()

   def justify(__A    :			list	,					__A    :			int	,					__A    :			int  ) -> str:
      _SCREAMING_SNAKE_CASE	=				max_width - width
      _SCREAMING_SNAKE_CASE	=				len(snake_case_  )
      if len(snake_case_  ) == 1:
         # if there is only word in line
         # just insert overall_spaces_count for the remainder of line
         return line[0] + " " * overall_spaces_count
      else:
         _SCREAMING_SNAKE_CASE	=				words_count - 1
         # num_spaces_between_words_list[i] : tells you to insert
         # num_spaces_between_words_list[i] spaces
         # after word on line[i]
         _SCREAMING_SNAKE_CASE	=				spaces_to_insert_between_words * [
             overall_spaces_count // spaces_to_insert_between_words
         ]
         _SCREAMING_SNAKE_CASE	=				(
             overall_spaces_count % spaces_to_insert_between_words
         )
         # distribute spaces via round robin to the left words
         for i in range(snake_case_  ):
            num_spaces_between_words_list[i] += 1
         _SCREAMING_SNAKE_CASE	=				[]
         for i in range(snake_case_  ):
            # add the word
            aligned_words_list.append(line[i]  )
            # add the spaces to insert
            aligned_words_list.append(num_spaces_between_words_list[i] * " "  )
         # just add the last word to the sentence
         aligned_words_list.append(line[-1]  )
         # join the aligned words list to form a justified line
         return "".join(snake_case_  )

   _SCREAMING_SNAKE_CASE	=				[]
   _SCREAMING_SNAKE_CASE	=				[]
   _SCREAMING_SNAKE_CASE	=				0
   for word in words:
      if width + len(snake_case_  ) + len(snake_case_  ) <= max_width:
         # keep adding words until we can fill out max_width
         # width = sum of length of all words (without overall_spaces_count)
         # len(word) = length of current word
         # len(line) = number of overall_spaces_count to insert between words
         line.append(snake_case_  )
         width += len(snake_case_  )
      else:
         # justify the line and add it to result
         answer.append(justify(snake_case_	,					snake_case_	,					snake_case_  )  )
         # reset new line and new width
         _SCREAMING_SNAKE_CASE,	_SCREAMING_SNAKE_CASE	=				[word], len(snake_case_  )
   _SCREAMING_SNAKE_CASE	=				max_width - width - len(snake_case_  )
   answer.append(" ".join(snake_case_  ) + (remaining_spaces + 1) * " "  )
   return answer


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

