code: 
  
  
  
  
  
  from typing import Callable, Optional, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  a__				: Optional[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 							__snake_case    (				UpperCamelCase_       ):
  	__lowerCAmelCase						=     """prophetnet"""
  	__lowerCAmelCase						=     ["""past_key_values"""]
  	__lowerCAmelCase						=     {
  	    """num_attention_heads""": """num_encoder_attention_heads""",
  	}
  
  
  
  
  
  	def __init__(		self			,					UpperCamelCase_ = 0.1			,					UpperCamelCase_ = "gelu"			,					UpperCamelCase_ = 3_0522			,					UpperCamelCase_ = 1024			,					UpperCamelCase_ = 4096			,					UpperCamelCase_ = 12			,					UpperCamelCase_ = 16			,					UpperCamelCase_ = 4096			,					UpperCamelCase_ = 12			,					UpperCamelCase_ = 16			,					UpperCamelCase_ = 0.1			,					UpperCamelCase_ = 0.1			,					UpperCamelCase_ = 512			,					UpperCamelCase_ = 0.0_2			,					UpperCamelCase_ = True			,					UpperCamelCase_ = True			,					UpperCamelCase_ = 0			,					UpperCamelCase_ = 2			,					UpperCamelCase_ = 32			,					UpperCamelCase_ = 128			,					UpperCamelCase_ = False			,					UpperCamelCase_ = 0.0			,					UpperCamelCase_ = True			,					UpperCamelCase_ = 0			,					UpperCamelCase_ = 1			,					UpperCamelCase_ = 2			,					**UpperCamelCase_			,					)			->		int:
  		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      _snake_case      (		self		)			->		int:
  		return self.num_encoder_layers + self.num_decoder_layers
  
  
  
  
  
  	@num_hidden_layers.setter
  	def      _snake_case      (		self			,					UpperCamelCase_		)			->		Union[str, Any]:
  		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'''
  
  
  
  
  a__				: Any									=    {
      0: '''underwear''',
      1: '''pants''',
      2: '''belt''',
      3: '''suit''',
      4: '''shoe''',
      5: '''socks''',
      6: '''shirt''',
      7: '''tie''',
      8: '''watch''',
  }
  
  a__				: Optional[Any]									=    [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]
  
  a__				: List[str]									=    [0 for x in range(len(graph))]
  a__				: List[Any]									=    []
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_				,							UpperCAmelCase_       )      ->Dict:
  	snake_case__  					=      1
  	while stack:
  		snake_case__  					=      stack.pop()
  		print(UpperCAmelCase_				,							clothes[current_clothing]       )
  		order += 1
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_				,							UpperCAmelCase_				,							UpperCAmelCase_       )      ->Dict:
  	snake_case__  					=      1
  	for v in graph[u]:
  		if not visited[v]:
  			depth_first_search(UpperCAmelCase_				,							UpperCAmelCase_				,							UpperCAmelCase_       )
  
  	stack.append(UpperCAmelCase_       )
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_				,							UpperCAmelCase_       )      ->Union[str, Any]:
  	for v in range(len(UpperCAmelCase_       )       ):
  		if not visited[v]:
  			depth_first_search(UpperCAmelCase_				,							UpperCAmelCase_				,							UpperCAmelCase_       )
  
  
  if __name__ == "__main__":
  			topological_sort(graph, visited)
  			print(stack)
  			print_stack(stack, clothes)
  
  
  
  