





"""simple docstring"""


from typing import Callable, Optional, Union

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


a__					:     Union[str, Any]							=				logging.get_logger(__name__)

a__					:     Union[str, Any]							=				{
    """microsoft/prophetnet-large-uncased""": (
        """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
    ),
}



class      lowercase_				(     __lowerCAmelCase							):
       snake_case__				:							Tuple											=     """prophetnet"""
       snake_case__				:							Optional[int]											=     ["""past_key_values"""]
       snake_case__				:							int											=     {
           """num_attention_heads""": """num_encoder_attention_heads""",
       }

       def __init__(			self   ,					__SCREAMING_SNAKE_CASE = 0.1   ,					__SCREAMING_SNAKE_CASE = "gelu"   ,					__SCREAMING_SNAKE_CASE = 3_0522   ,					__SCREAMING_SNAKE_CASE = 1024   ,					__SCREAMING_SNAKE_CASE = 4096   ,					__SCREAMING_SNAKE_CASE = 12   ,					__SCREAMING_SNAKE_CASE = 16   ,					__SCREAMING_SNAKE_CASE = 4096   ,					__SCREAMING_SNAKE_CASE = 12   ,					__SCREAMING_SNAKE_CASE = 16   ,					__SCREAMING_SNAKE_CASE = 0.1   ,					__SCREAMING_SNAKE_CASE = 0.1   ,					__SCREAMING_SNAKE_CASE = 512   ,					__SCREAMING_SNAKE_CASE = 0.02   ,					__SCREAMING_SNAKE_CASE = True   ,					__SCREAMING_SNAKE_CASE = True   ,					__SCREAMING_SNAKE_CASE = 0   ,					__SCREAMING_SNAKE_CASE = 2   ,					__SCREAMING_SNAKE_CASE = 32   ,					__SCREAMING_SNAKE_CASE = 128   ,					__SCREAMING_SNAKE_CASE = False   ,					__SCREAMING_SNAKE_CASE = 0.0   ,					__SCREAMING_SNAKE_CASE = True   ,					__SCREAMING_SNAKE_CASE = 0   ,					__SCREAMING_SNAKE_CASE = 1   ,					__SCREAMING_SNAKE_CASE = 2   ,					**__SCREAMING_SNAKE_CASE   ,					):






        '''simple docstring'''

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

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

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

        snake_case__    							=				use_cache

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

       @property
       def 		_SCREAMING_SNAKE_CASE(			self     ):






        '''simple docstring'''

        return self.num_encoder_layers + self.num_decoder_layers

       @num_hidden_layers.setter
       def 		_SCREAMING_SNAKE_CASE(			self   ,					__SCREAMING_SNAKE_CASE     ):






        '''simple docstring'''

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








"""simple docstring"""


def 							a__			(  _UpperCAmelCase = 1_0_0_0	)    ->  int:

 '''simple docstring'''






 snake_case__    							=				[]
 snake_case__    							=				[]
 snake_case__    							=				3
 snake_case__    							=				5
 snake_case__    							=				1
 while True:
  snake_case__    							=				z * temp
  if result < n:
   zmulti.append(_UpperCAmelCase	)
   temp += 1
  else:
   snake_case__    							=				1
   break
 while True:
  snake_case__    							=				x * temp
  if result < n:
   xmulti.append(_UpperCAmelCase	)
   temp += 1
  else:
   break
 snake_case__    							=				list(set(xmulti + zmulti	)	)
 return sum(_UpperCAmelCase	)


if __name__ == "__main__":
   print(f'''{solution() = }''')

