code: 
  
  
  UpperCamelCase__				       =			{
      0: 'underwear',
      1: 'pants',
      2: 'belt',
      3: 'suit',
      4: 'shoe',
      5: 'socks',
      6: 'shirt',
      7: 'tie',
      8: 'watch',
  }
  
  UpperCamelCase__				       =			[[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]
  
  UpperCamelCase__				       =			[0 for x in range(len(graph))]
  UpperCamelCase__				       =			[]
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_			)						->							Union[str, Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Dict           =			1
         while stack:
                _lowercase					:				Tuple           =			stack.pop()
                print(UpperCAmelCase_    ,     clothes[current_clothing]			)
                order += 1
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_    ,     UpperCAmelCase_			)						->							Dict:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				int           =			1
         for v in graph[u]:
                if not visited[v]:
                       depth_first_search(UpperCAmelCase_    ,     UpperCAmelCase_    ,     UpperCAmelCase_			)
  
         stack.append(UpperCAmelCase_			)
  
  def   UpperCamelCase__   (    UpperCAmelCase_    ,     UpperCAmelCase_			)						->							List[Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         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)
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  UpperCamelCase__				       =			{
      'configuration_realm': ['REALM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RealmConfig'],
      'tokenization_realm': ['RealmTokenizer'],
  }
  
  try:
     if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			['RealmTokenizerFast']
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			[
         'REALM_PRETRAINED_MODEL_ARCHIVE_LIST',
         'RealmEmbedder',
         'RealmForOpenQA',
         'RealmKnowledgeAugEncoder',
         'RealmPreTrainedModel',
         'RealmReader',
         'RealmScorer',
         'load_tf_weights_in_realm',
     ]
     UpperCamelCase__				       =			['RealmRetriever']
  
  
  if TYPE_CHECKING:
     from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
     from .tokenization_realm import RealmTokenizer
  
     try:
        if not is_tokenizers_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .tokenization_realm import RealmTokenizerFast
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_realm import (
            REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
            RealmEmbedder,
            RealmForOpenQA,
            RealmKnowledgeAugEncoder,
            RealmPreTrainedModel,
            RealmReader,
            RealmScorer,
            load_tf_weights_in_realm,
        )
        from .retrieval_realm import RealmRetriever
  
  
  else:
     import sys
  
     UpperCamelCase__				       =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)