





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`.'		)










'''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)



