code: 
  
  
  
  
  '''simple docstring'''
  
  from typing import Callable, Optional, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCamelCase_     			=       logging.get_logger(__name__)
  
  UpperCamelCase_     			=       {
      """microsoft/prophetnet-large-uncased""": (
          """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
      ),
  }
  
  
  class   a_  (_a    ):
         __lowerCAmelCase    :				Optional[Any]    =      """prophetnet"""
         __lowerCAmelCase    :				Dict    =      ["""past_key_values"""]
         __lowerCAmelCase    :				str    =      {
             """num_attention_heads""": """num_encoder_attention_heads""",
         }
  
  
  
  
         def __init__(     self   ,   snake_case_ = 0.1   ,   snake_case_ = "gelu"   ,   snake_case_ = 3_0_5_2_2   ,   snake_case_ = 1_0_2_4   ,   snake_case_ = 4_0_9_6   ,   snake_case_ = 1_2   ,   snake_case_ = 1_6   ,   snake_case_ = 4_0_9_6   ,   snake_case_ = 1_2   ,   snake_case_ = 1_6   ,   snake_case_ = 0.1   ,   snake_case_ = 0.1   ,   snake_case_ = 5_1_2   ,   snake_case_ = 0.02   ,   snake_case_ = True   ,   snake_case_ = True   ,   snake_case_ = 0   ,   snake_case_ = 2   ,   snake_case_ = 3_2   ,   snake_case_ = 1_2_8   ,   snake_case_ = False   ,   snake_case_ = 0.0   ,   snake_case_ = True   ,   snake_case_ = 0   ,   snake_case_ = 1   ,   snake_case_ = 2   ,   **snake_case_   ,   ):
           _lowerCAmelCase       :  str   				=					vocab_size
           _lowerCAmelCase       :  Optional[Any]   				=					hidden_size
           _lowerCAmelCase       :  Optional[int]   				=					encoder_ffn_dim
           _lowerCAmelCase       :  int   				=					num_encoder_layers
           _lowerCAmelCase       :  str   				=					num_encoder_attention_heads
           _lowerCAmelCase       :  Optional[Any]   				=					decoder_ffn_dim
           _lowerCAmelCase       :  Tuple   				=					num_decoder_layers
           _lowerCAmelCase       :  Tuple   				=					num_decoder_attention_heads
           _lowerCAmelCase       :  int   				=					max_position_embeddings
           _lowerCAmelCase       :  List[Any]   				=					init_std  # Normal(0, this parameter)
           _lowerCAmelCase       :  Optional[Any]   				=					activation_function
  
           # parameters for prophetnet
           _lowerCAmelCase       :  Dict   				=					ngram
           _lowerCAmelCase       :  str   				=					num_buckets
           _lowerCAmelCase       :  Dict   				=					relative_max_distance
           _lowerCAmelCase       :  Dict   				=					disable_ngram_loss
           _lowerCAmelCase       :  List[str]   				=					eps
  
           # 3 Types of Dropout
           _lowerCAmelCase       :  Optional[Any]   				=					attention_dropout
           _lowerCAmelCase       :  Dict   				=					activation_dropout
           _lowerCAmelCase       :  Dict   				=					dropout
  
           _lowerCAmelCase       :  str   				=					use_cache
  
           super().__init__(
               pad_token_id=snake_case_   ,   bos_token_id=snake_case_   ,   eos_token_id=snake_case_   ,   is_encoder_decoder=snake_case_   ,   add_cross_attention=snake_case_   ,   decoder_start_token_id=snake_case_   ,   **snake_case_   ,   )
  
  
  
  
         @property
         def 							__UpperCamelCase       (     self  ):
           return self.num_encoder_layers + self.num_decoder_layers
  
  
  
  
  
  
  
         @num_hidden_layers.setter
         def 							__UpperCamelCase       (     self   ,   snake_case_  ):
           raise NotImplementedError(
               """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
               """ `num_decoder_layers`."""  )
  
  
  
style_context: 
  '''simple docstring'''
  
  import os
  
  
  def 	_UpperCAmelCase				(  )    ->						int:
    _lowerCAmelCase       :  Optional[int]   				=					os.path.dirname(os.path.realpath(_lowerCamelCase		)		)
    _lowerCAmelCase       :  Optional[Any]   				=					os.path.join(_lowerCamelCase  ,      """triangle.txt"""		)
  
    with open(_lowerCamelCase		) as in_file:
      _lowerCAmelCase       :  List[Any]   				=					[[int(_lowerCamelCase		) for i in line.split()] for line in in_file]
  
    while len(_lowerCamelCase		) != 1:
      _lowerCAmelCase       :  Any   				=					triangle.pop()
      _lowerCAmelCase       :  List[str]   				=					triangle[-1]
      for j in range(len(_lowerCamelCase		) - 1		):
        curr_row[j] += max(last_row[j]  ,      last_row[j + 1]		)
    return triangle[0][0]
  
  
  if __name__ == "__main__":
       print(solution())
  
  
  