





'''simple docstring'''




import copy

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


a__				: List[Any]									=    logging.get_logger(__name__)

a__				: Union[str, Any]									=    {}






class 							__snake_case    (				__magic_name__       ):
	__lowerCAmelCase						=     '''fsmt_decoder'''





	def __init__(		self			,					UpperCamelCase_=0			,					UpperCamelCase_=0		)			->		int:
		super().__init__()
		snake_case__  					=      vocab_size
		snake_case__  					=      bos_token_id






class 							__snake_case    (				__magic_name__       ):
	__lowerCAmelCase						=     '''fsmt'''
	__lowerCAmelCase						=     {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}





	def __init__(		self			,					UpperCamelCase_=["en", "de"]			,					UpperCamelCase_=4_2024			,					UpperCamelCase_=4_2024			,					UpperCamelCase_="relu"			,					UpperCamelCase_=1024			,					UpperCamelCase_=200			,					UpperCamelCase_=1024			,					UpperCamelCase_=4096			,					UpperCamelCase_=12			,					UpperCamelCase_=16			,					UpperCamelCase_=0.0			,					UpperCamelCase_=4096			,					UpperCamelCase_=12			,					UpperCamelCase_=16			,					UpperCamelCase_=0.0			,					UpperCamelCase_=0.0			,					UpperCamelCase_=0.1			,					UpperCamelCase_=0.0			,					UpperCamelCase_=0.0_2			,					UpperCamelCase_=2			,					UpperCamelCase_=True			,					UpperCamelCase_=True			,					UpperCamelCase_=False			,					UpperCamelCase_=5			,					UpperCamelCase_=1.0			,					UpperCamelCase_=False			,					UpperCamelCase_=True			,					UpperCamelCase_=1			,					UpperCamelCase_=0			,					UpperCamelCase_=2			,					UpperCamelCase_=2			,					**UpperCamelCase_			,					)			->		str:
		snake_case__  					=      langs
		snake_case__  					=      src_vocab_size
		snake_case__  					=      tgt_vocab_size
		snake_case__  					=      d_model  # encoder_embed_dim and decoder_embed_dim

		snake_case__  					=      encoder_ffn_dim
		snake_case__  					=      snake_case__  					=      encoder_layers
		snake_case__  					=      encoder_attention_heads
		snake_case__  					=      encoder_layerdrop
		snake_case__  					=      decoder_layerdrop
		snake_case__  					=      decoder_ffn_dim
		snake_case__  					=      decoder_layers
		snake_case__  					=      decoder_attention_heads
		snake_case__  					=      max_position_embeddings
		snake_case__  					=      init_std  # Normal(0, this parameter)
		snake_case__  					=      activation_function

		snake_case__  					=      DecoderConfig(vocab_size=UpperCamelCase_			,					bos_token_id=UpperCamelCase_		)
		if "decoder" in common_kwargs:
			del common_kwargs["decoder"]

		snake_case__  					=      scale_embedding  # scale factor will be sqrt(d_model) if True

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

		snake_case__  					=      use_cache
		super().__init__(
		    pad_token_id=UpperCamelCase_			,					bos_token_id=UpperCamelCase_			,					eos_token_id=UpperCamelCase_			,					decoder_start_token_id=UpperCamelCase_			,					is_encoder_decoder=UpperCamelCase_			,					tie_word_embeddings=UpperCamelCase_			,					forced_eos_token_id=UpperCamelCase_			,					max_length=UpperCamelCase_			,					num_beams=UpperCamelCase_			,					length_penalty=UpperCamelCase_			,					early_stopping=UpperCamelCase_			,					**UpperCamelCase_			,					)





	def      _snake_case      (		self		)			->		int:
		snake_case__  					=      copy.deepcopy(self.__dict__		)
		snake_case__  					=      self.decoder.to_dict()
		snake_case__  					=      self.__class__.model_type
		return output










'''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)



