





class 				_UpperCAmelCase    :

  """simple docstring"""


  def __init__(				self :		List[Any]     )							->						List[Any]:
     __lowerCAmelCase								=	{}






  def 				lowercase		(				self :		List[str]     )							->						Union[str, Any]:
     print(self.vertex     )
     for i in self.vertex:
        print(_lowerCAmelCase					,  ' -> '					,  ' -> '.join([str(_lowerCAmelCase     ) for j in self.vertex[i]]     )     )






  def 				lowercase		(				self :		List[Any]					,  lowerCAmelCase_ :		int					,  lowerCAmelCase_ :		int     )							->						Tuple:
     # check if vertex is already present,
     if from_vertex in self.vertex:
        self.vertex[from_vertex].append(_lowerCAmelCase     )
     else:
        # else make a new vertex
        __lowerCAmelCase								=	[to_vertex]






  def 				lowercase		(				self :		Dict     )							->						Optional[Any]:
     # visited array for storing already visited nodes
     __lowerCAmelCase								=	[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 				lowercase		(				self :		Union[str, Any]					,  lowerCAmelCase_ :		int					,  lowerCAmelCase_ :		list     )							->						List[Any]:
     # mark start vertex as visited
     __lowerCAmelCase								=	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__":
     _snake_case  :    List[Any]						    =  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







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase__ :   Union[str, Any]					=							{
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__ :   Any					=							['LayoutLMv2TokenizerFast']

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__ :   Dict					=							['LayoutLMv2FeatureExtractor']
   lowerCamelCase__ :   Dict					=							['LayoutLMv2ImageProcessor']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__ :   Union[str, Any]					=							[
       'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
       'LayoutLMv2ForQuestionAnswering',
       'LayoutLMv2ForSequenceClassification',
       'LayoutLMv2ForTokenClassification',
       'LayoutLMv2Layer',
       'LayoutLMv2Model',
       'LayoutLMv2PreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
   from .processing_layoutlmva import LayoutLMvaProcessor
   from .tokenization_layoutlmva import LayoutLMvaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_layoutlmva import (
          LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
          LayoutLMvaForQuestionAnswering,
          LayoutLMvaForSequenceClassification,
          LayoutLMvaForTokenClassification,
          LayoutLMvaLayer,
          LayoutLMvaModel,
          LayoutLMvaPreTrainedModel,
      )
else:
   import sys

   lowerCamelCase__ :   Any					=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)