





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_						       =	{
    """shi-labs/dinat-mini-in1k-224""": """https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json""",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}

class 		UpperCamelCase__			(				lowerCAmelCase_							,				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     str		     =      "dinat"

     __snake_case   :     Any		     =      {
         "num_attention_heads": "num_heads",
         "num_hidden_layers": "num_layers",
     }






     def __init__(							self						:   Dict						,lowerCamelCase__						:   Optional[Any]=4						,lowerCamelCase__						:   Any=3						,lowerCamelCase__						:   int=64						,lowerCamelCase__						:   Union[str, Any]=[3, 4, 6, 5]						,lowerCamelCase__						:   str=[2, 4, 8, 16]						,lowerCamelCase__						:   Tuple=7						,lowerCamelCase__						:   Optional[int]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]						,lowerCamelCase__						:   str=3.0						,lowerCamelCase__						:   str=True						,lowerCamelCase__						:   Union[str, Any]=0.0						,lowerCamelCase__						:   List[str]=0.0						,lowerCamelCase__						:   str=0.1						,lowerCamelCase__						:   str="gelu"						,lowerCamelCase__						:   Tuple=0.02						,lowerCamelCase__						:   List[Any]=1e-5						,lowerCamelCase__						:   str=0.0						,lowerCamelCase__						:   str=None						,lowerCamelCase__						:   str=None						,**lowerCamelCase__						:   Optional[Any]						,)					->		List[Any]:




           '''simple docstring'''


           super().__init__(**lowerCamelCase__	)

           SCREAMING_SNAKE_CASE		=						patch_size
           SCREAMING_SNAKE_CASE		=						num_channels
           SCREAMING_SNAKE_CASE		=						embed_dim
           SCREAMING_SNAKE_CASE		=						depths
           SCREAMING_SNAKE_CASE		=						len(lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						num_heads
           SCREAMING_SNAKE_CASE		=						kernel_size
           SCREAMING_SNAKE_CASE		=						dilations
           SCREAMING_SNAKE_CASE		=						mlp_ratio
           SCREAMING_SNAKE_CASE		=						qkv_bias
           SCREAMING_SNAKE_CASE		=						hidden_dropout_prob
           SCREAMING_SNAKE_CASE		=						attention_probs_dropout_prob
           SCREAMING_SNAKE_CASE		=						drop_path_rate
           SCREAMING_SNAKE_CASE		=						hidden_act
           SCREAMING_SNAKE_CASE		=						layer_norm_eps
           SCREAMING_SNAKE_CASE		=						initializer_range
           # we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
           # this indicates the channel dimension after the last stage of the model
           SCREAMING_SNAKE_CASE		=						int(embed_dim * 2 ** (len(lowerCamelCase__	) - 1)	)
           SCREAMING_SNAKE_CASE		=						layer_scale_init_value
           SCREAMING_SNAKE_CASE		=						["""stem"""] + [F"""stage{idx}""" for idx in range(1						,len(lowerCamelCase__	) + 1	)]
           SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE		=						get_aligned_output_features_output_indices(
               out_features=lowerCamelCase__						,out_indices=lowerCamelCase__						,stage_names=self.stage_names	)









class 		UpperCamelCase__			:



     '''simple docstring'''

     def __init__(							self						:   int	)					->		str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						{}






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]	)					->		None:




           '''simple docstring'''


           print(self.vertex	)
           for i in self.vertex:
                 print(lowerCamelCase__						,""" -> """						,""" -> """.join([str(lowerCamelCase__	) for j in self.vertex[i]]	)	)






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[Any]						,lowerCamelCase__						:   int						,lowerCamelCase__						:   int	)					->		None:




           '''simple docstring'''


           if from_vertex in self.vertex:
                 self.vertex[from_vertex].append(lowerCamelCase__	)
           else:
                 # else make a new vertex
                 SCREAMING_SNAKE_CASE		=						[to_vertex]






     def     SCREAMING_SNAKE_CASE__  (							self						:   str	)					->		None:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[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     SCREAMING_SNAKE_CASE__  (							self						:   Any						,lowerCamelCase__						:   int						,lowerCamelCase__						:   list	)					->		None:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						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__":
      SCREAMING_SNAKE_CASE_						       =	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


