





from typing import TYPE_CHECKING

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


lowerCAmelCase_        =							{
    '''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '''ResNetOnnxConfig''']
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_        =							[
	    '''RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''ResNetForImageClassification''',
	    '''ResNetModel''',
	    '''ResNetPreTrainedModel''',
	    '''ResNetBackbone''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_        =							[
	    '''TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFResNetForImageClassification''',
	    '''TFResNetModel''',
	    '''TFResNetPreTrainedModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase_        =							[
	    '''FlaxResNetForImageClassification''',
	    '''FlaxResNetModel''',
	    '''FlaxResNetPreTrainedModel''',
	]

if TYPE_CHECKING:
	from .configuration_resnet import RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP, ResNetConfig, ResNetOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_resnet import (
		    RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ResNetBackbone,
		    ResNetForImageClassification,
		    ResNetModel,
		    ResNetPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_resnet import (
		    TF_RESNET_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFResNetForImageClassification,
		    TFResNetModel,
		    TFResNetPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_resnet import FlaxResNetForImageClassification, FlaxResNetModel, FlaxResNetPreTrainedModel


else:
	import sys

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


"""simple docstring"""




from __future__ import annotations

a		:       str     						=       {
    'A': ['B', 'C', 'E'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F', 'G'],
    'D': ['B'],
    'E': ['A', 'B', 'D'],
    'F': ['C'],
    'G': ['C'],
}







class     lowercase:



     def __init__(							self     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   )		->     None:







         """simple docstring"""



         a__		=			graph
         # mapping node to its parent in resulting breadth first tree
         a__		=			{}
         a__		=			source_vertex



     def 			lowercase__  (							self   )		->     None:







         """simple docstring"""



         a__		=			{self.source_vertex}
         a__		=			None
         a__		=			[self.source_vertex]  # first in first out queue

         while queue:
             a__		=			queue.pop(0   )
             for adjacent_vertex in self.graph[vertex]:
                 if adjacent_vertex not in visited:
                     visited.add(__SCREAMING_SNAKE_CASE   )
                     a__		=			vertex
                     queue.append(__SCREAMING_SNAKE_CASE   )




     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     str:







         """simple docstring"""



         if target_vertex == self.source_vertex:
             return self.source_vertex

         a__		=			self.parent.get(__SCREAMING_SNAKE_CASE   )
         if target_vertex_parent is None:
             a__		=			(
                 f'No path from vertex: {self.source_vertex} to vertex: {target_vertex}'
             )
             raise ValueError(__SCREAMING_SNAKE_CASE   )

         return self.shortest_path(__SCREAMING_SNAKE_CASE   ) + f'->{target_vertex}'


if __name__ == "__main__":
    a		:       Optional[Any]     						=       Graph(graph, 'G')
    g.breath_first_search()
    print(g.shortest_path('D'))
    print(g.shortest_path('G'))
    print(g.shortest_path('Foo'))


