




from typing import TYPE_CHECKING

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


__A						:		Union[str, Any]          =						{
    "configuration_led": ["LED_PRETRAINED_CONFIG_ARCHIVE_MAP", "LEDConfig"],
    "tokenization_led": ["LEDTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Optional[int]          =						["LEDTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Optional[int]          =						[
	    "LED_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "LEDForConditionalGeneration",
	    "LEDForQuestionAnswering",
	    "LEDForSequenceClassification",
	    "LEDModel",
	    "LEDPreTrainedModel",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A						:		Tuple          =						["TFLEDForConditionalGeneration", "TFLEDModel", "TFLEDPreTrainedModel"]


if TYPE_CHECKING:
	from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
	from .tokenization_led import LEDTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_led_fast import LEDTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_led import (
		    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LEDForConditionalGeneration,
		    LEDForQuestionAnswering,
		    LEDForSequenceClassification,
		    LEDModel,
		    LEDPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
	import sys

	__A						:		List[Any]          =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










'''simple docstring'''






class 	_lowerCAmelCase     :






		'''simple docstring'''
		def __init__(						self							:       int      ,		UpperCamelCase_							:       int		)      ->			None:







									'''simple docstring'''





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





def 				_SCREAMING_SNAKE_CASE(					snake_case_    :     Node  )		->None:






							'''simple docstring'''
							_lowercase							:		str				=   0
							_lowercase							:		List[Any]				=   x





def 				_SCREAMING_SNAKE_CASE(					snake_case_    :     Node ,       snake_case_    :     Node  )		->None:






							'''simple docstring'''
							_lowercase			, _lowercase							:		Union[str, Any]				=   find_set(snake_case_  ), find_set(snake_case_  )
							if x == y:
														return

							elif x.rank > y.rank:
														_lowercase							:		Optional[Any]				=   x
							else:
														_lowercase							:		Optional[int]				=   y
														if x.rank == y.rank:
																					y.rank += 1





def 				_SCREAMING_SNAKE_CASE(					snake_case_    :     Node  )		->Node:






							'''simple docstring'''
							if x != x.parent:
														_lowercase							:		str				=   find_set(x.parent  )
							return x.parent





def 				_SCREAMING_SNAKE_CASE(					snake_case_    :     Node  )		->set:






							'''simple docstring'''
							_lowercase							:		str				=   ({0, 1, 2}, {3, 4, 5})
							for s in sets:
														if node.data in s:
																					return s
							_lowercase							:		Optional[Any]				=   F"{node.data} is not in {sets}"
							raise ValueError(snake_case_  )





def 				_SCREAMING_SNAKE_CASE(					)		->None:






							'''simple docstring'''
							_lowercase							:		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()



