



'''simple docstring'''



from __future__ import annotations

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






class 					UpperCAmelCase__	:



					def __init__(    self			,				UpperCamelCase			,				UpperCamelCase     )     ->			Optional[Any]:
						__lowerCAmelCase												=  graph
						# mapping node to its parent in resulting breadth first tree
						__lowerCAmelCase												=  {}
						__lowerCAmelCase												=  source_vertex



					def        UpperCAmelCase_ (    self     )     ->			List[Any]:
						__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(_lowerCamelCase     )
									__lowerCAmelCase												=  vertex
									queue.append(_lowerCamelCase     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			Union[str, Any]:
						if target_vertex == self.source_vertex:
							return self.source_vertex

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

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


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




'''simple docstring'''



from typing import TYPE_CHECKING

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


lowerCAmelCase	:		Union[str, Any]				=   {
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   ['''DistilBertTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   [
	    '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DistilBertForMaskedLM''',
	    '''DistilBertForMultipleChoice''',
	    '''DistilBertForQuestionAnswering''',
	    '''DistilBertForSequenceClassification''',
	    '''DistilBertForTokenClassification''',
	    '''DistilBertModel''',
	    '''DistilBertPreTrainedModel''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		List[str]				=   [
	    '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFDistilBertForMaskedLM''',
	    '''TFDistilBertForMultipleChoice''',
	    '''TFDistilBertForQuestionAnswering''',
	    '''TFDistilBertForSequenceClassification''',
	    '''TFDistilBertForTokenClassification''',
	    '''TFDistilBertMainLayer''',
	    '''TFDistilBertModel''',
	    '''TFDistilBertPreTrainedModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Optional[int]				=   [
	    '''FlaxDistilBertForMaskedLM''',
	    '''FlaxDistilBertForMultipleChoice''',
	    '''FlaxDistilBertForQuestionAnswering''',
	    '''FlaxDistilBertForSequenceClassification''',
	    '''FlaxDistilBertForTokenClassification''',
	    '''FlaxDistilBertModel''',
	    '''FlaxDistilBertPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_distilbert import (
	    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DistilBertConfig,
	    DistilBertOnnxConfig,
	)
	from .tokenization_distilbert import DistilBertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_distilbert_fast import DistilBertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_distilbert import (
		    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DistilBertForMaskedLM,
		    DistilBertForMultipleChoice,
		    DistilBertForQuestionAnswering,
		    DistilBertForSequenceClassification,
		    DistilBertForTokenClassification,
		    DistilBertModel,
		    DistilBertPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_distilbert import (
		    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDistilBertForMaskedLM,
		    TFDistilBertForMultipleChoice,
		    TFDistilBertForQuestionAnswering,
		    TFDistilBertForSequenceClassification,
		    TFDistilBertForTokenClassification,
		    TFDistilBertMainLayer,
		    TFDistilBertModel,
		    TFDistilBertPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_distilbert import (
		    FlaxDistilBertForMaskedLM,
		    FlaxDistilBertForMultipleChoice,
		    FlaxDistilBertForQuestionAnswering,
		    FlaxDistilBertForSequenceClassification,
		    FlaxDistilBertForTokenClassification,
		    FlaxDistilBertModel,
		    FlaxDistilBertPreTrainedModel,
		)

else:
	import sys

	lowerCAmelCase	:		List[str]				=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)