
class 		__lowerCamelCase     :



							def __init__(     self	,				__snake_case							)						->     None:






								"""simple docstring"""



								UpperCAmelCase:					Optional[Any] 						=     data
								UpperCAmelCase:					int
								UpperCAmelCase:					Node



def      __UpperCAmelCase    (  snake_case_							:		Node				):



	'''simple docstring'''



	UpperCAmelCase:					Union[str, Any] 						=     0
	UpperCAmelCase:					Optional[Any] 						=     x



def      __UpperCAmelCase    (  snake_case_							:		Node				,					snake_case_							:		Node				):



	'''simple docstring'''



	UpperCAmelCase:					List[Any] 						=     find_set(snake_case_				), find_set(snake_case_				)
	if x == y:
		return

	elif x.rank > y.rank:
		UpperCAmelCase:					Any 						=     x
	else:
		UpperCAmelCase:					str 						=     y
		if x.rank == y.rank:
			y.rank += 1



def      __UpperCAmelCase    (  snake_case_							:		Node				):



	'''simple docstring'''



	if x != x.parent:
		UpperCAmelCase:					Optional[int] 						=     find_set(x.parent				)
	return x.parent



def      __UpperCAmelCase    (  snake_case_							:		Node				):



	'''simple docstring'''



	UpperCAmelCase:					Any 						=     ({0, 1, 2}, {3, 4, 5})
	for s in sets:
		if node.data in s:
			return s
	UpperCAmelCase:					Any 						=     F'{node.data} is not in {sets}'
	raise ValueError(snake_case_				)



def      __UpperCAmelCase    (  ):



	'''simple docstring'''



	UpperCAmelCase:					List[Any] 						=     [Node(snake_case_				) for i in range(6				)]
	for v in vertex:
		make_set(snake_case_				)

	union_set(vertex[0]				,					vertex[1]				)
	union_set(vertex[1]				,					vertex[2]				)
	union_set(vertex[3]				,					vertex[4]				)
	union_set(vertex[3]				,					vertex[5]				)

	for nodea in vertex:
		for nodea in vertex:
			if find_python_set(snake_case_				).isdisjoint(find_python_set(snake_case_				)				):
				assert find_set(snake_case_				) != find_set(snake_case_				)
			else:
				assert find_set(snake_case_				) == find_set(snake_case_				)


if __name__ == "__main__":
	test_disjoint_set()




from typing import TYPE_CHECKING

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


__UpperCamelCase							:							Dict    							=					{
    "configuration_dpr": ["DPR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPRConfig"],
    "tokenization_dpr": [
        "DPRContextEncoderTokenizer",
        "DPRQuestionEncoderTokenizer",
        "DPRReaderOutput",
        "DPRReaderTokenizer",
    ],
}


try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							Any    							=					[
           "DPRContextEncoderTokenizerFast",
           "DPRQuestionEncoderTokenizerFast",
           "DPRReaderTokenizerFast",
       ]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							str    							=					[
           "DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DPRContextEncoder",
           "DPRPretrainedContextEncoder",
           "DPRPreTrainedModel",
           "DPRPretrainedQuestionEncoder",
           "DPRPretrainedReader",
           "DPRQuestionEncoder",
           "DPRReader",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __UpperCamelCase							:							int    							=					[
           "TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFDPRContextEncoder",
           "TFDPRPretrainedContextEncoder",
           "TFDPRPretrainedQuestionEncoder",
           "TFDPRPretrainedReader",
           "TFDPRQuestionEncoder",
           "TFDPRReader",
       ]


if TYPE_CHECKING:
       from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
       from .tokenization_dpr import (
           DPRContextEncoderTokenizer,
           DPRQuestionEncoderTokenizer,
           DPRReaderOutput,
           DPRReaderTokenizer,
       )

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_dpr_fast import (
                  DPRContextEncoderTokenizerFast,
                  DPRQuestionEncoderTokenizerFast,
                  DPRReaderTokenizerFast,
              )

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_dpr import (
                  DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DPRContextEncoder,
                  DPRPretrainedContextEncoder,
                  DPRPreTrainedModel,
                  DPRPretrainedQuestionEncoder,
                  DPRPretrainedReader,
                  DPRQuestionEncoder,
                  DPRReader,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_dpr import (
                  TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFDPRContextEncoder,
                  TFDPRPretrainedContextEncoder,
                  TFDPRPretrainedQuestionEncoder,
                  TFDPRPretrainedReader,
                  TFDPRQuestionEncoder,
                  TFDPRReader,
              )

else:
       import sys

       __UpperCamelCase							:							Dict    							=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


