
'''simple docstring'''

def 						_snake_case    (   A_							:     List[str] ):
  """simple docstring"""







  return [
      {
          0: [1, 2],
          1: [0, 2],
          2: [0, 1, 3, 5],
          3: [2, 4],
          4: [3],
          5: [2, 6, 8],
          6: [5, 7],
          7: [6, 8],
          8: [5, 7],
      },
      {
          0: [6],
          1: [9],
          2: [4, 5],
          3: [4],
          4: [2, 3],
          5: [2],
          6: [0, 7],
          7: [6],
          8: [],
          9: [1],
      },
      {
          0: [4],
          1: [6],
          2: [],
          3: [5, 6, 7],
          4: [0, 6],
          5: [3, 8, 9],
          6: [1, 3, 4, 7],
          7: [3, 6, 8, 9],
          8: [5, 7],
          9: [5, 7],
      },
      {
          0: [1, 3],
          1: [0, 2, 4],
          2: [1, 3, 4],
          3: [0, 2, 4],
          4: [1, 2, 3],
      },
  ][index]






def 						_snake_case    (   A_							:     dict[int, list[int]] ):
  """simple docstring"""







  a_   :						List[str]   =				0
  a_   :						Tuple   =				len(__A )  # No of vertices in graph
  a_   :						List[Any]   =				[0] * n
  a_   :						int   =				[False] * n

  def dfs(A_							:     Any  ,		A_							:     int  ,		A_							:     str  ,		A_							:     int ):
    a_   :						Union[str, Any]   =				True
    a_   :						Optional[int]   =				id_
    id_ += 1
    for to in graph[at]:
      if to == parent:
        pass
      elif not visited[to]:
        dfs(__A  ,		__A  ,		__A  ,		id_ )
        a_   :						Tuple   =				min(low[at]  ,		low[to] )
        if id_ <= low[to]:
          bridges.append((at, to) if at < to else (to, at) )
      else:
        # This edge is a back edge and cannot be a bridge
        a_   :						str   =				min(low[at]  ,		low[to] )

  a_   :						Dict   =				[]
  for i in range(__A ):
    if not visited[i]:
      dfs(__A  ,		-1  ,		__A  ,		id_ )
  return bridges


if __name__ == "__main__":
    import doctest

    doctest.testmod()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_lowerCamelCase      :					Tuple					    =      {
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase      :					List[str]					    =      ['''SqueezeBertTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase      :					Tuple					    =      [
       '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''SqueezeBertForMaskedLM''',
       '''SqueezeBertForMultipleChoice''',
       '''SqueezeBertForQuestionAnswering''',
       '''SqueezeBertForSequenceClassification''',
       '''SqueezeBertForTokenClassification''',
       '''SqueezeBertModel''',
       '''SqueezeBertModule''',
       '''SqueezeBertPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_squeezebert import (
       SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
       SqueezeBertConfig,
       SqueezeBertOnnxConfig,
   )
   from .tokenization_squeezebert import SqueezeBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_squeezebert import (
          SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          SqueezeBertForMaskedLM,
          SqueezeBertForMultipleChoice,
          SqueezeBertForQuestionAnswering,
          SqueezeBertForSequenceClassification,
          SqueezeBertForTokenClassification,
          SqueezeBertModel,
          SqueezeBertModule,
          SqueezeBertPreTrainedModel,
      )

else:
   import sys

   _lowerCamelCase      :					List[str]					    =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


