'''simple docstring'''


class       _a    :


  """simple docstring"""

  def __init__(		self      :       Optional[Any]      ):







    '''simple docstring'''


    lowercase_     =       {}




  def 		lowerCamelCase__  (		self      :       Union[str, Any]      ):







    '''simple docstring'''


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




  def 		lowerCamelCase__  (		self      :       Dict   ,				lowercase_      :       int   ,				lowercase_      :       int      ):







    '''simple docstring'''


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




  def 		lowerCamelCase__  (		self      :       Tuple      ):







    '''simple docstring'''


    lowercase_     =       [False] * len(self.vertex      )

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





  def 		lowerCamelCase__  (		self      :       Union[str, Any]   ,				lowercase_      :       int   ,				lowercase_      :       list      ):







    '''simple docstring'''


    lowercase_     =       True

    print(lowercase_   ,				end=""" """      )

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


if __name__ == "__main__":
       __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


'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


__snake_case						  =		logging.get_logger(__name__)

__snake_case						  =		{
    """microsoft/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}





class       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''table-transformer'''
  A_    							=						['''past_key_values''']
  A_    							=						{
      '''hidden_size''': '''d_model''',
      '''num_attention_heads''': '''encoder_attention_heads''',
  }




  def __init__(		self      :       str   ,				lowercase_      :       str=True   ,				lowercase_      :       List[str]=None   ,				lowercase_      :       Dict=3   ,				lowercase_      :       Optional[Any]=100   ,				lowercase_      :       Optional[int]=6   ,				lowercase_      :       Optional[Any]=2_048   ,				lowercase_      :       List[Any]=8   ,				lowercase_      :       Optional[Any]=6   ,				lowercase_      :       int=2_048   ,				lowercase_      :       Any=8   ,				lowercase_      :       Optional[Any]=0.0   ,				lowercase_      :       int=0.0   ,				lowercase_      :       Dict=True   ,				lowercase_      :       int="relu"   ,				lowercase_      :       Tuple=256   ,				lowercase_      :       Dict=0.1   ,				lowercase_      :       List[str]=0.0   ,				lowercase_      :       List[str]=0.0   ,				lowercase_      :       int=0.0_2   ,				lowercase_      :       List[str]=1.0   ,				lowercase_      :       Optional[int]=False   ,				lowercase_      :       List[Any]="sine"   ,				lowercase_      :       Optional[int]="resnet50"   ,				lowercase_      :       Union[str, Any]=True   ,				lowercase_      :       Union[str, Any]=False   ,				lowercase_      :       List[str]=1   ,				lowercase_      :       Any=5   ,				lowercase_      :       Optional[int]=2   ,				lowercase_      :       Dict=1   ,				lowercase_      :       Optional[int]=1   ,				lowercase_      :       Dict=5   ,				lowercase_      :       Optional[int]=2   ,				lowercase_      :       Optional[Any]=0.1   ,				**lowercase_      :       List[str]   ,				):







    '''simple docstring'''


    if backbone_config is not None and use_timm_backbone:
      raise ValueError("""You can't specify both `backbone_config` and `use_timm_backbone`."""      )

    if not use_timm_backbone:
      if backbone_config is None:
        logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""      )
        lowercase_     =       CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]      )
      elif isinstance(lowercase_   ,				lowercase_      ):
        lowercase_     =       backbone_config.get("""model_type"""      )
        lowercase_     =       CONFIG_MAPPING[backbone_model_type]
        lowercase_     =       config_class.from_dict(lowercase_      )
      # set timm attributes to None
      lowercase_     ,	lowercase_     ,	lowercase_     =       None, None, None

    lowercase_     =       use_timm_backbone
    lowercase_     =       backbone_config
    lowercase_     =       num_channels
    lowercase_     =       num_queries
    lowercase_     =       d_model
    lowercase_     =       encoder_ffn_dim
    lowercase_     =       encoder_layers
    lowercase_     =       encoder_attention_heads
    lowercase_     =       decoder_ffn_dim
    lowercase_     =       decoder_layers
    lowercase_     =       decoder_attention_heads
    lowercase_     =       dropout
    lowercase_     =       attention_dropout
    lowercase_     =       activation_dropout
    lowercase_     =       activation_function
    lowercase_     =       init_std
    lowercase_     =       init_xavier_std
    lowercase_     =       encoder_layerdrop
    lowercase_     =       decoder_layerdrop
    lowercase_     =       encoder_layers
    lowercase_     =       auxiliary_loss
    lowercase_     =       position_embedding_type
    lowercase_     =       backbone
    lowercase_     =       use_pretrained_backbone
    lowercase_     =       dilation
    # Hungarian matcher
    lowercase_     =       class_cost
    lowercase_     =       bbox_cost
    lowercase_     =       giou_cost
    # Loss coefficients
    lowercase_     =       mask_loss_coefficient
    lowercase_     =       dice_loss_coefficient
    lowercase_     =       bbox_loss_coefficient
    lowercase_     =       giou_loss_coefficient
    lowercase_     =       eos_coefficient
    super().__init__(is_encoder_decoder=lowercase_   ,				**lowercase_      )




  @property
  def 		lowerCamelCase__  (		self      :       Tuple      ):







    '''simple docstring'''


    return self.encoder_attention_heads





  @property
  def 		lowerCamelCase__  (		self      :       Dict      ):







    '''simple docstring'''


    return self.d_model






class       _a    (		__a      ):


  """simple docstring"""

  A_    							=						version.parse('''1.11'''      )




  @property
  def 		lowerCamelCase__  (		self      :       int      ):







    '''simple docstring'''


    return OrderedDict(
        [
            ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
            ("""pixel_mask""", {0: """batch"""}),
        ]      )




  @property
  def 		lowerCamelCase__  (		self      :       List[Any]      ):







    '''simple docstring'''


    return 1e-5





  @property
  def 		lowerCamelCase__  (		self      :       Union[str, Any]      ):







    '''simple docstring'''


    return 12

