




from graphs.minimum_spanning_tree_kruskal import kruskal




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						9
       __lowerCamelCase   =						[
           [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],
       ]

       __lowerCamelCase   =						kruskal(_lowercase  ,			_lowercase	)

       __lowerCamelCase   =						[
           [7, 6, 1],
           [2, 8, 2],
           [6, 5, 2],
           [0, 1, 4],
           [2, 5, 4],
           [2, 3, 7],
           [0, 7, 8],
           [3, 4, 9],
       ]

       assert sorted(_lowercase	) == sorted(_lowercase	)






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__a      =				{
    "configuration_mask2former": [
        "MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Mask2FormerConfig",
    ],
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				["Mask2FormerImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      =				[
						    "MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "Mask2FormerForUniversalSegmentation",
						    "Mask2FormerModel",
						    "Mask2FormerPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_maskaformer import MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskaFormerConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_maskaformer import MaskaFormerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_maskaformer import (
												    MASK2FORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MaskaFormerForUniversalSegmentation,
												    MaskaFormerModel,
												    MaskaFormerPreTrainedModel,
												)


else:
						import sys

						__a      =				_LazyModule(__name__, globals()["__file__"], _import_structure)
