




'''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`."""  )




'''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())


