


'''simple docstring'''

class _lowerCamelCase       :



		'''simple docstring'''







		def __init__(					self		:						int			)  -> Any:
			__magic_name__       :    Any     	=     {}







		def    __lowerCAmelCase		(					self		:						int			)  -> None:
			print(self.vertex			)
			for i in self.vertex:
				print(lowercase_  ,     ' -> '  ,     ' -> '.join([str(lowercase_			) for j in self.vertex[i]]			)			)







		def    __lowerCAmelCase		(					self		:						Optional[Any]  ,     _A		:						int  ,     _A		:						int			)  -> None:




			if from_vertex in self.vertex:
				self.vertex[from_vertex].append(lowercase_			)
			else:
				# else make a new vertex
				__magic_name__       :    Dict     	=     [to_vertex]







		def    __lowerCAmelCase		(					self		:						List[Any]			)  -> None:
			__magic_name__       :    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(lowercase_  ,     lowercase_			)







		def    __lowerCAmelCase		(					self		:						Any  ,     _A		:						int  ,     _A		:						list			)  -> None:
			__magic_name__       :    List[str]     	=     True

			print(lowercase_  ,     end=' '			)

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


if __name__ == "__main__":
							lowerCAmelCase      :int    	=			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



from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
 from ..ta.tokenization_ta import TaTokenizer
else:
 from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCamelCase											=       TaTokenizer

if is_tokenizers_available():
 from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
 from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCamelCase											=       TaTokenizerFast

lowerCamelCase											=       {'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase											=       [
     'MT5EncoderModel',
     'MT5ForConditionalGeneration',
     'MT5ForQuestionAnswering',
     'MT5Model',
     'MT5PreTrainedModel',
     'MT5Stack',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase											=       ['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase											=       ['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
 from .configuration_mta import MTaConfig, MTaOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mta import (
      MTaEncoderModel,
      MTaForConditionalGeneration,
      MTaForQuestionAnswering,
      MTaModel,
      MTaPreTrainedModel,
      MTaStack,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
 import sys

 lowerCamelCase											=       _LazyModule(
     __name__,
     globals()['__file__'],
     _import_structure,
     extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
     module_spec=__spec__,
 )


