



"""simple docstring"""
from collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def    A_  (			):







						'''simple docstring'''


						snake_case_,       snake_case_ :Tuple						=			9, 14  # noqa: F841
						snake_case_ :Optional[Any]						=			[
						    [0, 1, 4],
						    [0, 7, 8],
						    [1, 2, 8],
						    [7, 8, 7],
						    [7, 6, 1],
						    [2, 8, 2],
						    [8, 6, 6],
						    [2, 3, 7],
						    [2, 5, 4],
						    [6, 5, 2],
						    [3, 5, 14],
						    [3, 4, 9],
						    [5, 4, 10],
						    [1, 7, 11],
						]

						snake_case_ :Any						=			defaultdict(_lowercase	)
						for nodea, nodea, cost in edges:
												adjancency[nodea].append([nodea, cost]	)
												adjancency[nodea].append([nodea, cost]	)

						snake_case_ :Union[str, Any]						=			mst(_lowercase	)

						snake_case_ :List[Any]						=			[
						    [7, 6, 1],
						    [2, 8, 2],
						    [6, 5, 2],
						    [0, 1, 4],
						    [2, 5, 4],
						    [2, 3, 7],
						    [0, 7, 8],
						    [3, 4, 9],
						]

						for answer in expected:
												snake_case_ :Optional[Any]						=			tuple(answer[:2]	)
												snake_case_ :Dict						=			tuple(edge[::-1]	)
												assert edge in result or reverse in result




"""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


UpperCAmelCase    :     Union[str, Any]   						=		{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase    :     int   						=		[
							    '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

							UpperCAmelCase    :     Tuple   						=		_LazyModule(__name__, globals()['__file__'], _import_structure)
