






"""simple docstring"""







class    __UpperCAmelCase:




						"""simple docstring"""




						def __init__(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Optional[int]=	set_counts
												lowercase__    :				Tuple=	max(snake_case__      )
												lowercase__    :				Dict=	len(snake_case__      )
												lowercase__    :				Dict=	[1] * num_sets
												lowercase__    :				Union[str, Any]=	list(range(snake_case__      )      )




						def 		UpperCAmelCase_	(       self	,  snake_case__	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				Any=	self.get_parent(snake_case__      )
												lowercase__    :				Optional[Any]=	self.get_parent(snake_case__      )

												if src_parent == dst_parent:
																		return False

												if self.ranks[dst_parent] >= self.ranks[src_parent]:
																		self.set_counts[dst_parent] += self.set_counts[src_parent]
																		lowercase__    :				Tuple=	0
																		lowercase__    :				Dict=	dst_parent
																		if self.ranks[dst_parent] == self.ranks[src_parent]:
																								self.ranks[dst_parent] += 1
																		lowercase__    :				Dict=	self.set_counts[dst_parent]
												else:
																		self.set_counts[src_parent] += self.set_counts[dst_parent]
																		lowercase__    :				Optional[Any]=	0
																		lowercase__    :				Union[str, Any]=	src_parent
																		lowercase__    :				List[str]=	self.set_counts[src_parent]

												lowercase__    :				Tuple=	max(self.max_set	,  snake_case__      )
												return True




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												if self.parents[disj_set] == disj_set:
																		return disj_set
												lowercase__    :				Union[str, Any]=	self.get_parent(self.parents[disj_set]      )
												return self.parents[disj_set]














"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a			:    List[str]				 =		{
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a			:    List[str]				 =		[
			    """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """XLMRobertaXLForCausalLM""",
			    """XLMRobertaXLForMaskedLM""",
			    """XLMRobertaXLForMultipleChoice""",
			    """XLMRobertaXLForQuestionAnswering""",
			    """XLMRobertaXLForSequenceClassification""",
			    """XLMRobertaXLForTokenClassification""",
			    """XLMRobertaXLModel""",
			    """XLMRobertaXLPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_xlm_roberta_xl import (
			    XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    XLMRobertaXLConfig,
			    XLMRobertaXLOnnxConfig,
			)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xlm_roberta_xl import (
						    XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    XLMRobertaXLForCausalLM,
						    XLMRobertaXLForMaskedLM,
						    XLMRobertaXLForMultipleChoice,
						    XLMRobertaXLForQuestionAnswering,
						    XLMRobertaXLForSequenceClassification,
						    XLMRobertaXLForTokenClassification,
						    XLMRobertaXLModel,
						    XLMRobertaXLPreTrainedModel,
						)

else:
			import sys

			a			:    List[str]				 =		_LazyModule(__name__, globals()["""__file__"""], _import_structure)






