
'''simple docstring'''



from __future__ import annotations

from typing import Any




class   UpperCAmelCase_					:






						'''simple docstring'''






						def __init__( self   ,       _lowercase				):

												"""simple docstring"""



												_lowerCAmelCase  						=			num_of_nodes
												_lowerCAmelCase  						=			[]
												_lowerCAmelCase  						=			{}




						def  _lowercase     ( self   ,       _lowercase   ,       _lowercase   ,       _lowercase				):

												"""simple docstring"""



												self.m_edges.append([u_node, v_node, weight]				)




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												if self.m_component[u_node] == u_node:
																		return u_node
												return self.find_component(self.m_component[u_node]				)




						def  _lowercase     ( self   ,       _lowercase				):

												"""simple docstring"""



												if self.m_component[u_node] != u_node:
																		for k in self.m_component:
																								_lowerCAmelCase  						=			self.find_component(_lowercase				)




						def  _lowercase     ( self   ,       _lowercase   ,       _lowercase   ,       _lowercase				):

												"""simple docstring"""



												if component_size[u_node] <= component_size[v_node]:
																		_lowerCAmelCase  						=			v_node
																		component_size[v_node] += component_size[u_node]
																		self.set_component(_lowercase				)

												elif component_size[u_node] >= component_size[v_node]:
																		_lowerCAmelCase  						=			self.find_component(_lowercase				)
																		component_size[u_node] += component_size[v_node]
																		self.set_component(_lowercase				)




						def  _lowercase     ( self				):

												"""simple docstring"""



												_lowerCAmelCase  						=			[]
												_lowerCAmelCase  						=			0

												_lowerCAmelCase  						=			[-1] * self.m_num_of_nodes

												# A list of components (initialized to all of the nodes)
												for node in range(self.m_num_of_nodes				):
																		self.m_component.update({node: node}				)
																		component_size.append(1				)

												_lowerCAmelCase  						=			self.m_num_of_nodes

												while num_of_components > 1:
																		for edge in self.m_edges:
																								_lowerCAmelCase						,   _lowerCAmelCase						,   _lowerCAmelCase  						=			edge

																								_lowerCAmelCase  						=			self.m_component[u]
																								_lowerCAmelCase  						=			self.m_component[v]

																								if u_component != v_component:

																														for component in (u_component, v_component):
																																				if (
																																				    minimum_weight_edge[component] == -1
																																				    or minimum_weight_edge[component][2] > w
																																				):
																																										_lowerCAmelCase  						=			[u, v, w]

																		for edge in minimum_weight_edge:
																								if isinstance(_lowercase   ,       _lowercase				):
																														_lowerCAmelCase						,   _lowerCAmelCase						,   _lowerCAmelCase  						=			edge

																														_lowerCAmelCase  						=			self.m_component[u]
																														_lowerCAmelCase  						=			self.m_component[v]

																														if u_component != v_component:
																																				mst_weight += w
																																				self.union(_lowercase   ,       _lowercase   ,       _lowercase				)
																																				print(F'Added edge [{u} - {v}]\nAdded weight: {w}\n'				)
																																				num_of_components -= 1

																		_lowerCAmelCase  						=			[-1] * self.m_num_of_nodes
												print(F'The total weight of the minimal spanning tree is: {mst_weight}'				)






def A				():
						pass


if __name__ == "__main__":
						import doctest

						doctest.testmod()


'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase    =		{"""configuration_deit""": ["""DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DeiTConfig""", """DeiTOnnxConfig"""]}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase    =		["""DeiTFeatureExtractor"""]
						_lowercase    =		["""DeiTImageProcessor"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase    =		[
						    """DEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """DeiTForImageClassification""",
						    """DeiTForImageClassificationWithTeacher""",
						    """DeiTForMaskedImageModeling""",
						    """DeiTModel""",
						    """DeiTPreTrainedModel""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_lowercase    =		[
						    """TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFDeiTForImageClassification""",
						    """TFDeiTForImageClassificationWithTeacher""",
						    """TFDeiTForMaskedImageModeling""",
						    """TFDeiTModel""",
						    """TFDeiTPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_deit import DeiTFeatureExtractor
												from .image_processing_deit import DeiTImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_deit import (
												    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DeiTForImageClassification,
												    DeiTForImageClassificationWithTeacher,
												    DeiTForMaskedImageModeling,
												    DeiTModel,
												    DeiTPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_deit import (
												    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFDeiTForImageClassification,
												    TFDeiTForImageClassificationWithTeacher,
												    TFDeiTForMaskedImageModeling,
												    TFDeiTModel,
												    TFDeiTPreTrainedModel,
												)


else:
						import sys

						_lowercase    =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
