

lowerCamelCase_    =					{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

lowerCamelCase_    =					{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}



def    UpperCamelCase(					lowercase_			,					lowercase_			,					lowercase_							)	->				list:





  '''simple docstring'''





  snake_case_       						=      True
  snake_case_       						=      []

  for neighbour in graph[vert]:
    if not visited[neighbour]:
      connected_verts += dfs(lowercase_			,					lowercase_			,					lowercase_							)

  return [vert, *connected_verts]



def    UpperCamelCase(					lowercase_							)	->				list:





  '''simple docstring'''





  snake_case_       						=      len(lowercase_							)
  snake_case_       						=      graph_size * [False]
  snake_case_       						=      []

  for i in range(lowercase_							):
    if not visited[i]:
      snake_case_       						=      dfs(lowercase_			,					lowercase_			,					lowercase_							)
      components_list.append(lowercase_							)

  return components_list


if __name__ == "__main__":
    import doctest

    doctest.testmod()


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCamelCase_    =					{
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					['''MPNetTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MPNetForMaskedLM''',
        '''MPNetForMultipleChoice''',
        '''MPNetForQuestionAnswering''',
        '''MPNetForSequenceClassification''',
        '''MPNetForTokenClassification''',
        '''MPNetLayer''',
        '''MPNetModel''',
        '''MPNetPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFMPNetEmbeddings''',
        '''TFMPNetForMaskedLM''',
        '''TFMPNetForMultipleChoice''',
        '''TFMPNetForQuestionAnswering''',
        '''TFMPNetForSequenceClassification''',
        '''TFMPNetForTokenClassification''',
        '''TFMPNetMainLayer''',
        '''TFMPNetModel''',
        '''TFMPNetPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
    from .tokenization_mpnet import MPNetTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mpnet_fast import MPNetTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mpnet import (
            MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            MPNetForMaskedLM,
            MPNetForMultipleChoice,
            MPNetForQuestionAnswering,
            MPNetForSequenceClassification,
            MPNetForTokenClassification,
            MPNetLayer,
            MPNetModel,
            MPNetPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mpnet import (
            TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFMPNetEmbeddings,
            TFMPNetForMaskedLM,
            TFMPNetForMultipleChoice,
            TFMPNetForQuestionAnswering,
            TFMPNetForSequenceClassification,
            TFMPNetForTokenClassification,
            TFMPNetMainLayer,
            TFMPNetModel,
            TFMPNetPreTrainedModel,
        )

else:
    import sys

    lowerCamelCase_    =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)