
from __future__ import annotations

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





class       __A:

     def __init__(	self					:     List[Any]   ,					__UpperCamelCase					:     dict[str, list[str]]   ,					__UpperCamelCase					:     str   ):
            lowerCamelCase_							  =					graph
            # mapping node to its parent in resulting breadth first tree
            lowerCamelCase_							  =					{}
            lowerCamelCase_							  =					source_vertex

     def    lowercase__      (	self					:     Tuple   ):
            lowerCamelCase_							  =					{self.source_vertex}
            lowerCamelCase_							  =					None
            lowerCamelCase_							  =					[self.source_vertex]  # first in first out queue

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



     def    lowercase__      (	self					:     str   ,					__UpperCamelCase					:     str   ):


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

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

            return self.shortest_path(_snake_case   ) + F'''->{target_vertex}'''


if __name__ == "__main__":
  lowercase        =  Graph(graph, '''G''')
  g.breath_first_search()
  print(g.shortest_path('''D'''))
  print(g.shortest_path('''G'''))
  print(g.shortest_path('''Foo'''))







from typing import TYPE_CHECKING

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


lowercase        =  {
    '''configuration_rag''': ['''RagConfig'''],
    '''retrieval_rag''': ['''RagRetriever'''],
    '''tokenization_rag''': ['''RagTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  [
		    '''RagModel''',
		    '''RagPreTrainedModel''',
		    '''RagSequenceForGeneration''',
		    '''RagTokenForGeneration''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase        =  [
		    '''TFRagModel''',
		    '''TFRagPreTrainedModel''',
		    '''TFRagSequenceForGeneration''',
		    '''TFRagTokenForGeneration''',
		]


if TYPE_CHECKING:
		from .configuration_rag import RagConfig
		from .retrieval_rag import RagRetriever
		from .tokenization_rag import RagTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_rag import (
				    TFRagModel,
				    TFRagPreTrainedModel,
				    TFRagSequenceForGeneration,
				    TFRagTokenForGeneration,
				)

else:
		import sys

		lowercase        =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





