



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


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

__snake_case     :List[Any]			       ={
    'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}



class        lowerCAmelCase__					(  _lowerCamelCase       ):
				A_   :     Dict								=     'nllb-moe'
				A_   :     Optional[int]								=     ['past_key_values']
				A_   :     Any								=     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}


				def __init__(							self      :  int						, __UpperCamelCase      :  int=128_112						, __UpperCamelCase      :  str=1_024						, __UpperCamelCase      :  Optional[Any]=12						, __UpperCamelCase      :  str=4_096						, __UpperCamelCase      :  Tuple=16						, __UpperCamelCase      :  List[str]=12						, __UpperCamelCase      :  Optional[Any]=4_096						, __UpperCamelCase      :  int=16						, __UpperCamelCase      :  str=0.0_5						, __UpperCamelCase      :  Optional[Any]=0.0_5						, __UpperCamelCase      :  Dict=True						, __UpperCamelCase      :  List[Any]=True						, __UpperCamelCase      :  Any="relu"						, __UpperCamelCase      :  Any=1_024						, __UpperCamelCase      :  Dict=0.1						, __UpperCamelCase      :  Union[str, Any]=0.1						, __UpperCamelCase      :  int=0.0						, __UpperCamelCase      :  int=0.0_2						, __UpperCamelCase      :  str=2						, __UpperCamelCase      :  str=True						, __UpperCamelCase      :  Dict=False						, __UpperCamelCase      :  List[Any]="float32"						, __UpperCamelCase      :  Tuple=False						, __UpperCamelCase      :  Any=128						, __UpperCamelCase      :  Optional[int]=64						, __UpperCamelCase      :  List[str]=4						, __UpperCamelCase      :  Dict=4						, __UpperCamelCase      :  int=0.0_0_1						, __UpperCamelCase      :  Dict=0.0_0_1						, __UpperCamelCase      :  Optional[Any]="all"						, __UpperCamelCase      :  List[str]=False						, __UpperCamelCase      :  Tuple=False						, __UpperCamelCase      :  Any=1.0						, __UpperCamelCase      :  List[str]=0.2						, __UpperCamelCase      :  str=1						, __UpperCamelCase      :  Optional[int]=0						, __UpperCamelCase      :  Union[str, Any]=2						, __UpperCamelCase      :  Dict=False						, **__UpperCamelCase      :  Optional[Any]						, )		->     Optional[int]:
											A      						=    vocab_size
											A      						=    max_position_embeddings
											A      						=    d_model
											A      						=    encoder_ffn_dim
											A      						=    encoder_layers
											A      						=    encoder_attention_heads
											A      						=    decoder_ffn_dim
											A      						=    decoder_layers
											A      						=    decoder_attention_heads
											A      						=    dropout
											A      						=    attention_dropout
											A      						=    activation_dropout
											A      						=    activation_function
											A      						=    init_std
											A      						=    encoder_layerdrop
											A      						=    decoder_layerdrop
											A      						=    use_cache
											A      						=    encoder_layers
											A      						=    scale_embedding  # scale factor will be sqrt(d_model) if True
											A      						=    router_z_loss_coef
											A      						=    router_aux_loss_coef
											A      						=    decoder_sparse_step
											A      						=    encoder_sparse_step
											A      						=    num_experts
											A      						=    expert_capacity
											A      						=    router_bias
											if router_dtype not in ["float32", "float16", "bfloat16"]:
																		raise ValueError(f'''`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'''       )
											A      						=    router_dtype

											A      						=    router_ignore_padding_tokens
											A      						=    batch_prioritized_routing
											A      						=    second_expert_policy
											A      						=    normalize_router_prob_before_dropping
											A      						=    moe_eval_capacity_token_fraction
											A      						=    moe_token_dropout
											A      						=    output_router_logits
											super().__init__(
											    pad_token_id=__UpperCamelCase						, bos_token_id=__UpperCamelCase						, eos_token_id=__UpperCamelCase						, is_encoder_decoder=__UpperCamelCase						, decoder_start_token_id=__UpperCamelCase						, **__UpperCamelCase						, )


"""simple docstring"""


class lowerCamelCase__   :



    '''simple docstring'''




    def __init__( self    )    ->      Union[str, Any]:
          A				  =		{}




    def UpperCamelCase__		( self    )    ->      None:
          print(self.vertex    )
          for i in self.vertex:
                print(lowerCamelCase_ ,""" -> """ ,""" -> """.join([str(lowerCamelCase_    ) for j in self.vertex[i]]    )    )




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_    )    ->      None:
          # check if vertex is already present,
          if from_vertex in self.vertex:
                self.vertex[from_vertex].append(lowerCamelCase_    )
          else:
                # else make a new vertex
                A				  =		[to_vertex]




    def UpperCamelCase__		( self    )    ->      None:
          # visited array for storing already visited nodes
          A				  =		[False] * len(self.vertex    )

          # call the recursive helper function
          for i in range(len(self.vertex    )    ):
                if not visited[i]:
                      self.dfs_recursive(lowerCamelCase_ ,lowerCamelCase_    )




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_    )    ->      None:
          # mark start vertex as visited
          A				  =		True

          print(lowerCamelCase_ ,end=""" """    )

          # Recur for all the vertices that are adjacent to this node
          for i in self.vertex:
                if not visited[i]:
                      self.dfs_recursive(lowerCamelCase_ ,lowerCamelCase_    )


if __name__ == "__main__":
  UpperCAmelCase													=Graph()
  g.add_edge(0, 1)
  g.add_edge(0, 2)
  g.add_edge(1, 2)
  g.add_edge(2, 0)
  g.add_edge(2, 3)
  g.add_edge(3, 3)

  g.print_graph()
  print("DFS:")
  g.dfs()

  # OUTPUT:
  # 0  ->  1 -> 2
  # 1  ->  2
  # 2  ->  0 -> 3
  # 3  ->  3
  # DFS:
  #  0 1 2 3




