


"""simple docstring"""





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


def   _snake_case    (    _snake_case					:      list			, _snake_case					:      int      ):
      lowerCAmelCase       :						Dict							= []  # type: list[int]
      lowerCAmelCase       :						Optional[int]							= []  # type: list[int]
      backtrack(_snake_case			, _snake_case			, _snake_case			, _snake_case			, 0      )
      return answer


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


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()






"""simple docstring"""





from typing import Callable, Optional, Union

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


snake_case__		:  Optional[Any]     					=					logging.get_logger(__name__)

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



class 		snake_case_(							a__      ):
     __UpperCamelCase	=       '''prophetnet'''
     __UpperCamelCase	=       ['''past_key_values''']
     __UpperCamelCase	=       {
         '''num_attention_heads''': '''num_encoder_attention_heads''',
     }






     def __init__(						self	:       Union[str, Any]       ,					UpperCamelCase_	:       Optional[float] = 0.1       ,					UpperCamelCase_	:       Optional[Union[str, Callable]] = "gelu"       ,					UpperCamelCase_	:       Optional[int] = 3_0_5_2_2       ,					UpperCamelCase_	:       Optional[int] = 1_0_2_4       ,					UpperCamelCase_	:       Optional[int] = 4_0_9_6       ,					UpperCamelCase_	:       Optional[int] = 1_2       ,					UpperCamelCase_	:       Optional[int] = 1_6       ,					UpperCamelCase_	:       Optional[int] = 4_0_9_6       ,					UpperCamelCase_	:       Optional[int] = 1_2       ,					UpperCamelCase_	:       Optional[int] = 1_6       ,					UpperCamelCase_	:       Optional[float] = 0.1       ,					UpperCamelCase_	:       Optional[float] = 0.1       ,					UpperCamelCase_	:       Optional[int] = 5_1_2       ,					UpperCamelCase_	:       Optional[float] = 0.02       ,					UpperCamelCase_	:       Optional[bool] = True       ,					UpperCamelCase_	:       Optional[bool] = True       ,					UpperCamelCase_	:       Optional[int] = 0       ,					UpperCamelCase_	:       Optional[int] = 2       ,					UpperCamelCase_	:       Optional[int] = 3_2       ,					UpperCamelCase_	:       Optional[int] = 1_2_8       ,					UpperCamelCase_	:       Optional[bool] = False       ,					UpperCamelCase_	:       Optional[float] = 0.0       ,					UpperCamelCase_	:       Optional[bool] = True       ,					UpperCamelCase_	:       Optional[int] = 0       ,					UpperCamelCase_	:       Optional[int] = 1       ,					UpperCamelCase_	:       Optional[int] = 2       ,					**UpperCamelCase_	:       List[Any]       ,					):
           lowerCAmelCase       :						Union[str, Any]							= vocab_size
           lowerCAmelCase       :						Any							= hidden_size
           lowerCAmelCase       :						Tuple							= encoder_ffn_dim
           lowerCAmelCase       :						str							= num_encoder_layers
           lowerCAmelCase       :						int							= num_encoder_attention_heads
           lowerCAmelCase       :						Optional[Any]							= decoder_ffn_dim
           lowerCAmelCase       :						Union[str, Any]							= num_decoder_layers
           lowerCAmelCase       :						Union[str, Any]							= num_decoder_attention_heads
           lowerCAmelCase       :						List[Any]							= max_position_embeddings
           lowerCAmelCase       :						Dict							= init_std  # Normal(0, this parameter)
           lowerCAmelCase       :						Optional[int]							= activation_function

           # parameters for prophetnet
           lowerCAmelCase       :						Tuple							= ngram
           lowerCAmelCase       :						List[Any]							= num_buckets
           lowerCAmelCase       :						Optional[Any]							= relative_max_distance
           lowerCAmelCase       :						Dict							= disable_ngram_loss
           lowerCAmelCase       :						Optional[int]							= eps

           # 3 Types of Dropout
           lowerCAmelCase       :						Any							= attention_dropout
           lowerCAmelCase       :						List[Any]							= activation_dropout
           lowerCAmelCase       :						Tuple							= dropout

           lowerCAmelCase       :						Optional[int]							= 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	:       str					):
           return self.num_encoder_layers + self.num_decoder_layers






     @num_hidden_layers.setter
     def   lowerCamelCase__  (						self	:       Optional[Any]       ,					UpperCamelCase_	:       int					):
           raise NotImplementedError(
               '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
               ''' `num_decoder_layers`.'''					)


