



from typing import Callable, Optional, Union

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


a_								=   logging.get_logger(__name__)

a_								=   {
    """microsoft/prophetnet-large-uncased""": (
        """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
    ),
}



class 	__lowerCAmelCase       (		lowerCAmelCase__				):
 lowerCAmelCase__       =					"""prophetnet"""
 lowerCAmelCase__       =					["""past_key_values"""]
 lowerCAmelCase__       =					{
     """num_attention_heads""": """num_encoder_attention_heads""",
 }




 def __init__(  self		,			__UpperCAmelCase = 0.1		,			__UpperCAmelCase = "gelu"		,			__UpperCAmelCase = 30522		,			__UpperCAmelCase = 1024		,			__UpperCAmelCase = 4096		,			__UpperCAmelCase = 12		,			__UpperCAmelCase = 16		,			__UpperCAmelCase = 4096		,			__UpperCAmelCase = 12		,			__UpperCAmelCase = 16		,			__UpperCAmelCase = 0.1		,			__UpperCAmelCase = 0.1		,			__UpperCAmelCase = 512		,			__UpperCAmelCase = 0.02		,			__UpperCAmelCase = True		,			__UpperCAmelCase = True		,			__UpperCAmelCase = 0		,			__UpperCAmelCase = 2		,			__UpperCAmelCase = 32		,			__UpperCAmelCase = 128		,			__UpperCAmelCase = False		,			__UpperCAmelCase = 0.0		,			__UpperCAmelCase = True		,			__UpperCAmelCase = 0		,			__UpperCAmelCase = 1		,			__UpperCAmelCase = 2		,			**__UpperCAmelCase		,			):



    '''simple docstring'''
    __lowerCamelCase  							=      vocab_size
    __lowerCamelCase  							=      hidden_size
    __lowerCamelCase  							=      encoder_ffn_dim
    __lowerCamelCase  							=      num_encoder_layers
    __lowerCamelCase  							=      num_encoder_attention_heads
    __lowerCamelCase  							=      decoder_ffn_dim
    __lowerCamelCase  							=      num_decoder_layers
    __lowerCamelCase  							=      num_decoder_attention_heads
    __lowerCamelCase  							=      max_position_embeddings
    __lowerCamelCase  							=      init_std  # Normal(0, this parameter)
    __lowerCamelCase  							=      activation_function

    # parameters for prophetnet
    __lowerCamelCase  							=      ngram
    __lowerCamelCase  							=      num_buckets
    __lowerCamelCase  							=      relative_max_distance
    __lowerCamelCase  							=      disable_ngram_loss
    __lowerCamelCase  							=      eps

    # 3 Types of Dropout
    __lowerCamelCase  							=      attention_dropout
    __lowerCamelCase  							=      activation_dropout
    __lowerCamelCase  							=      dropout

    __lowerCamelCase  							=      use_cache

    super().__init__(
        pad_token_id=__UpperCAmelCase		,			bos_token_id=__UpperCAmelCase		,			eos_token_id=__UpperCAmelCase		,			is_encoder_decoder=__UpperCAmelCase		,			add_cross_attention=__UpperCAmelCase		,			decoder_start_token_id=__UpperCAmelCase		,			**__UpperCAmelCase		,			)




 @property
 def     lowerCamelCase (  self			):



    '''simple docstring'''
    return self.num_encoder_layers + self.num_decoder_layers




 @num_hidden_layers.setter
 def     lowerCamelCase (  self		,			__UpperCAmelCase			):



    '''simple docstring'''
    raise NotImplementedError(
        '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
        ''' `num_decoder_layers`.'''			)











def 						a__     (						_UpperCamelCase     :	list	,_UpperCamelCase     :	list	,_UpperCamelCase     :	list	,_UpperCamelCase     :	int	,_UpperCamelCase     :	int							):
   if target == 0:
      answer.append(path.copy()							)
   else:
      for index in range(_UpperCamelCase	,len(_UpperCamelCase							)							):
         if target >= candidates[index]:
            path.append(candidates[index]							)
            backtrack(_UpperCamelCase	,_UpperCamelCase	,_UpperCamelCase	,target - candidates[index]	,_UpperCamelCase							)
            path.pop(len(_UpperCamelCase							) - 1							)





def 						a__     (						_UpperCamelCase     :	list	,_UpperCamelCase     :	int							):
   __lowerCamelCase  							=      []  # type: list[int]
   __lowerCamelCase  							=      []  # type: list[int]
   backtrack(_UpperCamelCase	,_UpperCamelCase	,_UpperCamelCase	,_UpperCamelCase	,0							)
   return answer





def 						a__     (						):
   print(combination_sum([-8, 2.3, 0]	,1							)							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()






