code: 
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCamelCase_	:    Tuple  					=       logging.get_logger(__name__)
  
  UpperCamelCase_	:    Union[str, Any]  					=       {
      "google/pegasus-x-base": "https://huggingface.co/google/pegasus-x-base/resolve/main/config.json",
      "google/pegasus-x-large": "https://huggingface.co/google/pegasus-x-large/resolve/main/config.json",
      # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
  }
  
  
  
  
  class      __lowercase	(	SCREAMING_SNAKE_CASE__					):
  	_A   			=      'pegasus_x'
  	_A   			=      ['past_key_values']
  	_A   			=      {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}
  
  
  
  
  
  
  	def __init__(self							:   Optional[int]			,  snake_case							:   Tuple=9_6103			,  snake_case							:   Any=1_6384			,  snake_case							:   Optional[int]=16			,  snake_case							:   List[str]=4096			,  snake_case							:   int=16			,  snake_case							:   Tuple=16			,  snake_case							:   Union[str, Any]=4096			,  snake_case							:   Optional[Any]=16			,  snake_case							:   int=0.0			,  snake_case							:   Dict=0.0			,  snake_case							:   Any=True			,  snake_case							:   Optional[int]=True			,  snake_case							:   Tuple="gelu"			,  snake_case							:   Union[str, Any]=1024			,  snake_case							:   Optional[Any]=0.1			,  snake_case							:   int=0.0			,  snake_case							:   int=0.0			,  snake_case							:   Optional[int]=0.02			,  snake_case							:   Union[str, Any]=0			,  snake_case							:   Optional[int]=True			,  snake_case							:   str=0			,  snake_case							:   Tuple=1			,  snake_case							:   Optional[Any]=1			,  snake_case							:   Tuple=32			,  snake_case							:   Dict=512			,  snake_case							:   Tuple=True			,  **snake_case							:   Tuple			,  )   -> Any:
  							_lowercase					:  int    			=      vocab_size
  							_lowercase					:  Union[str, Any]    			=      max_position_embeddings
  							_lowercase					:  Union[str, Any]    			=      d_model
  							_lowercase					:  str    			=      encoder_ffn_dim
  							_lowercase					:  Optional[Any]    			=      encoder_layers
  							_lowercase					:  Any    			=      encoder_attention_heads
  							_lowercase					:  List[Any]    			=      decoder_ffn_dim
  							_lowercase					:  Optional[Any]    			=      decoder_layers
  							_lowercase					:  Dict    			=      decoder_attention_heads
  							_lowercase					:  Dict    			=      dropout
  							_lowercase					:  Dict    			=      attention_dropout
  							_lowercase					:  List[Any]    			=      activation_dropout
  							_lowercase					:  str    			=      activation_function
  							_lowercase					:  Optional[int]    			=      init_std
  							_lowercase					:  List[Any]    			=      encoder_layerdrop
  							_lowercase					:  Tuple    			=      decoder_layerdrop
  							_lowercase					:  Union[str, Any]    			=      use_cache
  							_lowercase					:  List[Any]    			=      encoder_layers
  							_lowercase					:  Tuple    			=      scale_embedding  # scale factor will be sqrt(d_model) if True
  
  							_lowercase					:  Union[str, Any]    			=      num_global_tokens
  							_lowercase					:  List[Any]    			=      block_size
  							_lowercase					:  Union[str, Any]    			=      stagger_local_blocks
  
  							super().__init__(
  							    pad_token_id=a_			,  eos_token_id=a_			,  is_encoder_decoder=a_			,  decoder_start_token_id=a_			,  forced_eos_token_id=a_			,  **a_			,  )
  
  
  
  
  
  
  	@property
  	def 			_a(self							:   Dict						)   -> Optional[Any]:
  							return self.encoder_attention_heads
  
  
  
  
  
  
  	@property
  	def 			_a(self							:   List[str]						)   -> List[str]:
  							return self.d_model
  
  
  
  
  
  
  
style_context: 
  import os
  
  
  
  def 		UpperCamelCase    (					)      -> Optional[int]:
  
  
  
  
  
  
  						'''simple docstring'''
  
  						_lowercase					:  Tuple    			=      0
  						_lowercase					:  List[Any]    			=      0
  						with open(os.path.dirname(_UpperCAmelCase     ) + "/p022_names.txt"     ) as file:
  												_lowercase					:  Any    			=      str(file.readlines()[0]     )
  												_lowercase					:  int    			=      name.replace("\""   , ""     ).split(","     )
  
  						name.sort()
  						for i in range(len(_UpperCAmelCase     )     ):
  												for j in name[i]:
  																		temp_sum += ord(_UpperCAmelCase     ) - ord("A"     ) + 1
  												total_sum += (i + 1) * temp_sum
  												_lowercase					:  Tuple    			=      0
  						return total_sum
  
  
  if __name__ == "__main__":
  							print(solution())
  
  
  
  
  