



'''simple docstring'''






from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass

@dataclass
class 							a__:
    lowercase__			=   42
    lowercase__			=   42

class 							a__:







    def __init__(				self			:  str						,      __snake_case			:  int     ):
      a						: list[list[Edge]]					       =					[[] for _ in range(__snake_case     )]
      a						: str					       =					size







    def __getitem__(				self			:  str						,      __snake_case			:  int     ):
      return iter(self._graph[vertex]     )







    @property
    def       lowercase_	(				self			:  int     ):
      return self._size







    def       lowercase_	(				self			:  Any						,      __snake_case			:  int						,      __snake_case			:  int						,      __snake_case			:  int     ):
      if weight not in (0, 1):
        raise ValueError('Edge weight must be either 0 or 1.'     )

      if to_vertex < 0 or to_vertex >= self.size:
        raise ValueError('Vertex indexes must be in [0; size).'     )

      self._graph[from_vertex].append(Edge(__snake_case						,      __snake_case     )     )







    def       lowercase_	(				self			:  List[Any]						,      __snake_case			:  int						,      __snake_case			:  int     ):
      a						: Dict					       =					deque([start_vertex]     )
      a						: list[int | None]					       =					[None] * self.size
      a						: str					       =					0

      while queue:
        a						: Optional[Any]					       =					queue.popleft()
        a						: Dict					       =					distances[current_vertex]
        if current_distance is None:
          continue

        for edge in self[current_vertex]:
          a						: Any					       =					current_distance + edge.weight
          a						: Any					       =					distances[edge.destination_vertex]
          if (
              isinstance(__snake_case						,      __snake_case     )
              and new_distance >= dest_vertex_distance
          ):
            continue
          a						: Optional[Any]					       =					new_distance
          if edge.weight == 0:
            queue.appendleft(edge.destination_vertex     )
          else:
            queue.append(edge.destination_vertex     )

      if distances[finish_vertex] is None:
        raise ValueError('No path from start_vertex to finish_vertex.'     )

      return distances[finish_vertex]


if __name__ == "__main__":
     import doctest

     doctest.testmod()




'''simple docstring'''






from typing import TYPE_CHECKING

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


lowerCAmelCase: Optional[int]							=						{
    'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase: int							=						[
         'GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'GraphormerForGraphClassification',
         'GraphormerModel',
         'GraphormerPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_graphormer import GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, GraphormerConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_graphormer import (
              GRAPHORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              GraphormerForGraphClassification,
              GraphormerModel,
              GraphormerPreTrainedModel,
          )


else:
     import sys

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