



"""simple docstring"""







from __future__ import annotations

from typing import Generic, TypeVar

A    =			TypeVar('T')






class      UpperCAmelCase__		(      Generic[T]     ):



		def __init__( self  :    Union[str, Any]      ,							snake_case  :    T				)			->						None:






									'''simple docstring'''

									A         =					data
									A         =					self
									A         =					0






class      UpperCAmelCase__		(      Generic[T]     ):



		def __init__( self  :    str				)			->						None:






									'''simple docstring'''

									A         =					{}



		def 					A_		( self  :    List[str]      ,							snake_case  :    T				)			->						None:






									'''simple docstring'''

									A         =					DisjointSetTreeNode(snake_case				)



		def 					A_		( self  :    Dict      ,							snake_case  :    T				)			->						DisjointSetTreeNode[T]:






									'''simple docstring'''

									A         =					self.map[data]
									if elem_ref != elem_ref.parent:
																A         =					self.find_set(elem_ref.parent.data				)
									return elem_ref.parent



		def 					A_		( self  :    List[Any]      ,							snake_case  :    DisjointSetTreeNode[T]      ,							snake_case  :    DisjointSetTreeNode[T]				)			->						None:






									'''simple docstring'''

									if nodea.rank > nodea.rank:
																A         =					nodea
									else:
																A         =					nodea
																if nodea.rank == nodea.rank:
																							nodea.rank += 1



		def 					A_		( self  :    str      ,							snake_case  :    T      ,							snake_case  :    T				)			->						None:






									'''simple docstring'''

									self.link(self.find_set(snake_case				)      ,							self.find_set(snake_case				)				)






class      UpperCAmelCase__		(      Generic[T]     ):



		def __init__( self  :    Optional[int]				)			->						None:






									'''simple docstring'''

									A         =					{}



		def 					A_		( self  :    List[str]      ,							snake_case  :    T				)			->						None:






									'''simple docstring'''

									if node not in self.connections:
																A         =					{}



		def 					A_		( self  :    Optional[Any]      ,							snake_case  :    T      ,							snake_case  :    T      ,							snake_case  :    int				)			->						None:






									'''simple docstring'''

									self.add_node(snake_case				)
									self.add_node(snake_case				)
									A         =					weight
									A         =					weight



		def 					A_		( self  :    Optional[Any]				)			->						GraphUndirectedWeighted[T]:






									'''simple docstring'''

									A         =					[]
									A         =					set()
									for start in self.connections:
																for end in self.connections[start]:
																							if (start, end) not in seen:
																														seen.add((end, start)				)
																														edges.append((start, end, self.connections[start][end])				)
									edges.sort(key=lambda snake_case				: x[2]				)

									# creating the disjoint set
									A         =					DisjointSetTree[T]()
									for node in self.connections:
																disjoint_set.make_set(snake_case				)

									# MST generation
									A         =					0
									A         =					0
									A         =					GraphUndirectedWeighted[T]()
									while num_edges < len(self.connections				) - 1:
																A      ,  A      ,  A         =					edges[index]
																index += 1
																A         =					disjoint_set.find_set(snake_case				)
																A         =					disjoint_set.find_set(snake_case				)
																if parent_u != parent_v:
																							num_edges += 1
																							graph.add_edge(snake_case      ,							snake_case      ,							snake_case				)
																							disjoint_set.union(snake_case      ,							snake_case				)
									return graph








"""simple docstring"""







# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


A    =			{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A    =			[
							    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'MraForMaskedLM',
							    'MraForMultipleChoice',
							    'MraForQuestionAnswering',
							    'MraForSequenceClassification',
							    'MraForTokenClassification',
							    'MraLayer',
							    'MraModel',
							    'MraPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_mra import (
														    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
														    MraForMaskedLM,
														    MraForMultipleChoice,
														    MraForQuestionAnswering,
														    MraForSequenceClassification,
														    MraForTokenClassification,
														    MraLayer,
														    MraModel,
														    MraPreTrainedModel,
														)
else:
							import sys

							A    =			_LazyModule(__name__, globals()['__file__'], _import_structure)



