

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


_lowerCamelCase    :       Union[str, Any]        =							logging.get_logger(__name__)

_lowerCamelCase    :       List[str]        =							{
    "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}





class  __UpperCAmelCase					(	lowerCamelCase__						):
   UpperCamelCase       					=					"""biogpt"""



   def __init__(							self							:					Tuple,		__A							:					Optional[int]=4_2_3_8_4,		__A							:					List[str]=1_0_2_4,		__A							:					str=2_4,		__A							:					Dict=1_6,		__A							:					Optional[int]=4_0_9_6,		__A							:					str="gelu",		__A							:					int=0.1,		__A							:					Union[str, Any]=0.1,		__A							:					Union[str, Any]=1_0_2_4,		__A							:					List[str]=0.0_2,		__A							:					Tuple=1E-12,		__A							:					str=True,		__A							:					Union[str, Any]=True,		__A							:					int=0.0,		__A							:					str=0.0,		__A							:					Any=1,		__A							:					Optional[Any]=0,		__A							:					List[Any]=2,		**__A							:					Any,		):
     UpperCAmelCase	:							List[str]						=			vocab_size
     UpperCAmelCase	:							List[Any]						=			max_position_embeddings
     UpperCAmelCase	:							Tuple						=			hidden_size
     UpperCAmelCase	:							int						=			num_hidden_layers
     UpperCAmelCase	:							List[str]						=			num_attention_heads
     UpperCAmelCase	:							int						=			intermediate_size
     UpperCAmelCase	:							int						=			hidden_act
     UpperCAmelCase	:							int						=			hidden_dropout_prob
     UpperCAmelCase	:							str						=			attention_probs_dropout_prob
     UpperCAmelCase	:							List[Any]						=			initializer_range
     UpperCAmelCase	:							str						=			layer_norm_eps
     UpperCAmelCase	:							Union[str, Any]						=			scale_embedding
     UpperCAmelCase	:							Optional[Any]						=			use_cache
     UpperCAmelCase	:							Union[str, Any]						=			layerdrop
     UpperCAmelCase	:							Dict						=			activation_dropout
     super().__init__(pad_token_id=__A,		bos_token_id=__A,		eos_token_id=__A,		**__A						)








def       a__					(		UpperCAmelCase							:      int      )  ->						bool:
  if not isinstance(UpperCAmelCase    ,			UpperCAmelCase      ):
    UpperCAmelCase	:							List[str]						=			f'''Input value of [number={number}] must be an integer'''
    raise TypeError(UpperCAmelCase      )
  if number < 0:
    return False
  UpperCAmelCase	:							List[str]						=			number * number
  while number > 0:
    if number % 10 != number_square % 10:
      return False
    number //= 10
    number_square //= 10
  return True


if __name__ == "__main__":
     import doctest

     doctest.testmod()





