


from typing import TYPE_CHECKING

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


snake_case__			 =						{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			pass

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			snake_case__			 =						[
			    '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''RoCBertForCausalLM''',
			    '''RoCBertForMaskedLM''',
			    '''RoCBertForMultipleChoice''',
			    '''RoCBertForPreTraining''',
			    '''RoCBertForQuestionAnswering''',
			    '''RoCBertForSequenceClassification''',
			    '''RoCBertForTokenClassification''',
			    '''RoCBertLayer''',
			    '''RoCBertModel''',
			    '''RoCBertPreTrainedModel''',
			    '''load_tf_weights_in_roc_bert''',
			]

if TYPE_CHECKING:
			from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
			from .tokenization_roc_bert import RoCBertTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						raise OptionalDependencyNotAvailable()

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_roc_bert import (
						    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    RoCBertForCausalLM,
						    RoCBertForMaskedLM,
						    RoCBertForMultipleChoice,
						    RoCBertForPreTraining,
						    RoCBertForQuestionAnswering,
						    RoCBertForSequenceClassification,
						    RoCBertForTokenClassification,
						    RoCBertLayer,
						    RoCBertModel,
						    RoCBertPreTrainedModel,
						    load_tf_weights_in_roc_bert,
						)


else:
			import sys

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






class 					lowerCAmelCase_ :




						def __init__(	self						:   Optional[int]						)      ->Optional[Any]:






									"""simple docstring"""






									a__ :Tuple						  =    {}




						def  _snake_case					(	self						:   Tuple						)      ->None:






									"""simple docstring"""






									print(self.vertex						)
									for i in self.vertex:
												print(__A   ,     " -> "   ,     " -> ".join([str(__A						) for j in self.vertex[i]]						)						)




						def  _snake_case					(	self						:   Optional[int]   ,     __A						:   int   ,     __A						:   int						)      ->None:






									"""simple docstring"""






									if from_vertex in self.vertex:
												self.vertex[from_vertex].append(__A						)
									else:
												# else make a new vertex
												a__ :Any						  =    [to_vertex]




						def  _snake_case					(	self						:   Optional[int]						)      ->None:






									"""simple docstring"""






									a__ :List[Any]						  =    [False] * len(self.vertex						)

									# call the recursive helper function
									for i in range(len(self.vertex						)						):
												if not visited[i]:
															self.dfs_recursive(__A   ,     __A						)






						def  _snake_case					(	self						:   Union[str, Any]   ,     __A						:   int   ,     __A						:   list						)      ->None:






									"""simple docstring"""






									a__ :Dict						  =    True

									print(__A   ,     end=" "						)

									# Recur for all the vertices that are adjacent to this node
									for i in self.vertex:
												if not visited[i]:
															self.dfs_recursive(__A   ,     __A						)


if __name__ == "__main__":
		snake_case__			 =						Graph()
		g.add_edge(0, 1)
		g.add_edge(0, 2)
		g.add_edge(1, 2)
		g.add_edge(2, 0)
		g.add_edge(2, 3)
		g.add_edge(3, 3)

		g.print_graph()
		print('''DFS:''')
		g.dfs()

		# OUTPUT:
		# 0  ->  1 -> 2
		# 1  ->  2
		# 2  ->  0 -> 3
		# 3  ->  3
		# DFS:
		#  0 1 2 3


