


"""simple docstring"""







from __future__ import annotations

lowerCAmelCase__      				=   '''#'''


class       SCREAMING_SNAKE_CASE__				:
       """simple docstring"""


       def __init__(						self						):






         """simple docstring"""





         lowerCAmelCase     :     dict								=							{}

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     List[str]								=							self._trie
         for char in text:
           if char not in trie:
             lowerCAmelCase     :     List[Any]								=							{}
           lowerCAmelCase     :     List[str]								=							trie[char]
         lowerCAmelCase     :     Optional[Any]								=							True

       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Any								=							self._trie
         for char in prefix:
           if char in trie:
             lowerCAmelCase     :     List[str]								=							trie[char]
           else:
             return []
         return self._elements(snake_case__						)







       def        lowercase__							(						self		,     snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[Any]								=							[]
         for c, v in d.items():
           lowerCAmelCase     :     Dict								=							[" "] if c == END else [(c + s) for s in self._elements(snake_case__						)]
           result.extend(snake_case__						)
         return tuple(snake_case__						)

lowerCAmelCase__      				=   Trie()
lowerCAmelCase__      				=   ('''depart''', '''detergent''', '''daring''', '''dog''', '''deer''', '''deal''')
for word in words:
     trie.insert_word(word)
def 					a__			(				SCREAMING_SNAKE_CASE    :    str				):


  '''simple docstring'''







  lowerCAmelCase     :     Union[str, Any]								=							trie.find_word(SCREAMING_SNAKE_CASE				)
  return tuple(string + word for word in suffixes				)
def 					a__			(				):


  '''simple docstring'''







  print(autocomplete_using_trie("de"				)				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()







from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCAmelCase			:     List[Any]           =   logging.get_logger(__name__)

__lowerCAmelCase			:     int           =   {
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}




class        UpperCAmelCase_			( _A     ):


  '''simple docstring'''







  a__           =		"""biogpt"""
  def __init__( self			: List[str]			,							UpperCamelCase__			: Optional[Any]=4_2384			,							UpperCamelCase__			: Union[str, Any]=1024			,							UpperCamelCase__			: Any=24			,							UpperCamelCase__			: Union[str, Any]=16			,							UpperCamelCase__			: Tuple=4096			,							UpperCamelCase__			: Tuple="gelu"			,							UpperCamelCase__			: Dict=0.1			,							UpperCamelCase__			: Dict=0.1			,							UpperCamelCase__			: str=1024			,							UpperCamelCase__			: Any=0.02			,							UpperCamelCase__			: List[str]=1E-12			,							UpperCamelCase__			: Dict=True			,							UpperCamelCase__			: Optional[int]=True			,							UpperCamelCase__			: Union[str, Any]=0.0			,							UpperCamelCase__			: Any=0.0			,							UpperCamelCase__			: List[str]=1			,							UpperCamelCase__			: Dict=0			,							UpperCamelCase__			: List[str]=2			,							**UpperCamelCase__			: Optional[int]			,							)			->	Tuple:







    """simple docstring"""






    __magic_name__				     =       vocab_size
    __magic_name__				     =       max_position_embeddings
    __magic_name__				     =       hidden_size
    __magic_name__				     =       num_hidden_layers
    __magic_name__				     =       num_attention_heads
    __magic_name__				     =       intermediate_size
    __magic_name__				     =       hidden_act
    __magic_name__				     =       hidden_dropout_prob
    __magic_name__				     =       attention_probs_dropout_prob
    __magic_name__				     =       initializer_range
    __magic_name__				     =       layer_norm_eps
    __magic_name__				     =       scale_embedding
    __magic_name__				     =       use_cache
    __magic_name__				     =       layerdrop
    __magic_name__				     =       activation_dropout
    super().__init__(pad_token_id=UpperCamelCase__			,							bos_token_id=UpperCamelCase__			,							eos_token_id=UpperCamelCase__			,							**UpperCamelCase__    )

