


from __future__ import annotations

from queue import Queue



class 							lowercase__:






      '''simple docstring'''







      def __init__(		self)					->						None:







         """simple docstring"""







         UpperCamelCase__ :			dict[int, list[int]] 						={}




      def    UpperCAmelCase							(		self)					->						None:







         """simple docstring"""







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




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







         """simple docstring"""







         if from_vertex in self.vertices:
            self.vertices[from_vertex].append(__SCREAMING_SNAKE_CASE)
         else:
            UpperCamelCase__ :			Union[str, Any] 						=[to_vertex]




      def    UpperCAmelCase							(		self   ,			__SCREAMING_SNAKE_CASE)					->						set[int]:







         """simple docstring"""







         UpperCamelCase__ :			List[str] 						=set()

         # create a first in first out queue to store all the vertices for BFS
         UpperCamelCase__ :			Queue 						=Queue()

         # mark the source node as visited and enqueue it
         visited.add(__SCREAMING_SNAKE_CASE)
         queue.put(__SCREAMING_SNAKE_CASE)

         while not queue.empty():
            UpperCamelCase__ :			Any 						=queue.get()

            # loop through all adjacent vertex and enqueue it if not yet visited
            for adjacent_vertex in self.vertices[vertex]:
               if adjacent_vertex not in visited:
                  queue.put(__SCREAMING_SNAKE_CASE)
                  visited.add(__SCREAMING_SNAKE_CASE)
         return visited


if __name__ == "__main__":
     from doctest import testmod

     testmod(verbose=True)

     __UpperCAmelCase      			=  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()
     # 0  :  1 -> 2
     # 1  :  2
     # 2  :  0 -> 3
     # 3  :  3

     assert sorted(g.bfs(2)) == [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,
)


__UpperCAmelCase      			=  {
    """configuration_switch_transformers""": [
        """SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SwitchTransformersConfig""",
        """SwitchTransformersOnnxConfig""",
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __UpperCAmelCase      			=  [
         """SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """SwitchTransformersEncoderModel""",
         """SwitchTransformersForConditionalGeneration""",
         """SwitchTransformersModel""",
         """SwitchTransformersPreTrainedModel""",
         """SwitchTransformersTop1Router""",
         """SwitchTransformersSparseMLP""",
     ]


if TYPE_CHECKING:
     from .configuration_switch_transformers import (
         SWITCH_TRANSFORMERS_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SwitchTransformersConfig,
         SwitchTransformersOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_switch_transformers import (
              SWITCH_TRANSFORMERS_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwitchTransformersEncoderModel,
              SwitchTransformersForConditionalGeneration,
              SwitchTransformersModel,
              SwitchTransformersPreTrainedModel,
              SwitchTransformersSparseMLP,
              SwitchTransformersTopaRouter,
          )


else:
     import sys

     __UpperCAmelCase      			=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

