


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


_lowerCamelCase    :   List[str]	    =					logging.get_logger(__name__)

_lowerCamelCase    :   List[str]	    =					{
    '''google/pegasus-large''': '''https://huggingface.co/google/pegasus-large/resolve/main/config.json''',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}







class 		_snake_case  (				__lowercase							):
 SCREAMING_SNAKE_CASE__				=	'pegasus'
 SCREAMING_SNAKE_CASE__				=	['past_key_values']
 SCREAMING_SNAKE_CASE__				=	{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}




 def __init__(		self ,  _lowerCamelCase=5_0265 ,  _lowerCamelCase=1024 ,  _lowerCamelCase=12 ,  _lowerCamelCase=4096 ,  _lowerCamelCase=16 ,  _lowerCamelCase=12 ,  _lowerCamelCase=4096 ,  _lowerCamelCase=16 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=True ,  _lowerCamelCase=True ,  _lowerCamelCase="gelu" ,  _lowerCamelCase=1024 ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.0 ,  _lowerCamelCase=0.02 ,  _lowerCamelCase=0 ,  _lowerCamelCase=False ,  _lowerCamelCase=0 ,  _lowerCamelCase=1 ,  _lowerCamelCase=1 ,  **_lowerCamelCase ,  ):
       a						:int										=	vocab_size
       a						:Tuple										=	max_position_embeddings
       a						:Tuple										=	d_model
       a						:Dict										=	encoder_ffn_dim
       a						:Dict										=	encoder_layers
       a						:int										=	encoder_attention_heads
       a						:List[str]										=	decoder_ffn_dim
       a						:Any										=	decoder_layers
       a						:Optional[Any]										=	decoder_attention_heads
       a						:str										=	dropout
       a						:Optional[Any]										=	attention_dropout
       a						:List[str]										=	activation_dropout
       a						:List[str]										=	activation_function
       a						:Optional[int]										=	init_std
       a						:Any										=	encoder_layerdrop
       a						:List[str]										=	decoder_layerdrop
       a						:int										=	use_cache
       a						:int										=	encoder_layers
       a						:List[str]										=	scale_embedding  # scale factor will be sqrt(d_model) if True
       super().__init__(
           pad_token_id=_a ,  eos_token_id=_a ,  is_encoder_decoder=_a ,  decoder_start_token_id=_a ,  forced_eos_token_id=_a ,  **_a ,  )




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return self.encoder_attention_heads




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       return self.d_model









def     __lowerCamelCase						(			UpperCAmelCase_						:		str						):




      """simple docstring"""





      if n_term == "":
            return []
      a						:list										=	[]
      for temp in range(int(UpperCAmelCase_						)						):
            series.append(F'''1/{temp + 1}''' if series else '''1'''						)
      return series


if __name__ == "__main__":
     snake_case    :   Tuple	    =					input('''Enter the last number (nth term) of the Harmonic Series''')
     print('''Formula of Harmonic Series => 1+1/2+1/3 ..... 1/n''')
     print(harmonic_series(nth_term))





