


'''simple docstring'''



from queue import PriorityQueue
from typing import Any

import numpy as np




def      _a     (						_lowercase :     dict      , _lowercase :     str      , _lowercase :     set      , _lowercase :     set      , _lowercase :     dict      , _lowercase :     dict      , _lowercase :     PriorityQueue      , _lowercase :     dict      , _lowercase :     float | int      , ):





     '''simple docstring'''






     for nxt, d in graph[v]:
          if nxt in visited_forward:
               continue
          __UpperCAmelCase     :			int  							=      cst_fwd.get(_lowercase      , np.inf  )
          __UpperCAmelCase     :			Tuple  							=      cst_fwd[v] + d
          if new_cost_f < old_cost_f:
               queue.put((new_cost_f, nxt)  )
               __UpperCAmelCase     :			int  							=      new_cost_f
               __UpperCAmelCase     :			List[Any]  							=      v
          if nxt in visited_backward:
               if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
                    __UpperCAmelCase     :			Tuple  							=      cst_fwd[v] + d + cst_bwd[nxt]
     return shortest_distance




def      _a     (						_lowercase :     str      , _lowercase :     str      , _lowercase :     dict      , _lowercase :     dict  ):





     '''simple docstring'''






     __UpperCAmelCase     :			List[str]  							=      -1

     __UpperCAmelCase     :			Dict  							=      set()
     __UpperCAmelCase     :			Any  							=      set()
     __UpperCAmelCase     :			Union[str, Any]  							=      {source: 0}
     __UpperCAmelCase     :			Tuple  							=      {destination: 0}
     __UpperCAmelCase     :			List[str]  							=      {source: None}
     __UpperCAmelCase     :			Any  							=      {destination: None}
     __UpperCAmelCase     :			PriorityQueue[Any]  							=      PriorityQueue()
     __UpperCAmelCase     :			PriorityQueue[Any]  							=      PriorityQueue()

     __UpperCAmelCase     :			List[Any]  							=      np.inf

     queue_forward.put((0, source)  )
     queue_backward.put((0, destination)  )

     if source == destination:
          return 0

     while not queue_forward.empty() and not queue_backward.empty():
          __UpperCAmelCase     :			int  							=      queue_forward.get()
          visited_forward.add(_lowercase  )

          __UpperCAmelCase     :			List[Any]  							=      queue_backward.get()
          visited_backward.add(_lowercase  )

          __UpperCAmelCase     :			List[Any]  							=      pass_and_relaxation(
              _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , )

          __UpperCAmelCase     :			Optional[int]  							=      pass_and_relaxation(
              _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , _lowercase      , )

          if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
               break

     if shortest_distance != np.inf:
          __UpperCAmelCase     :			Union[str, Any]  							=      shortest_distance
     return shortest_path_distance


__UpperCAmelCase      :int			    =       {
    "B": [["C", 1]],
    "C": [["D", 1]],
    "D": [["F", 1]],
    "E": [["B", 1], ["G", 2]],
    "F": [],
    "G": [["F", 1]],
}
__UpperCAmelCase      :str			    =       {
    "B": [["E", 1]],
    "C": [["B", 1]],
    "D": [["C", 1]],
    "F": [["D", 1], ["G", 1]],
    "E": [[None, np.inf]],
    "G": [["E", 2]],
}

if __name__ == "__main__":
 import doctest

 doctest.testmod()



'''simple docstring'''



from typing import TYPE_CHECKING

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


__UpperCAmelCase      :List[Any]			    =       {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       ["LxmertTokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       [
          "LxmertEncoder",
          "LxmertForPreTraining",
          "LxmertForQuestionAnswering",
          "LxmertModel",
          "LxmertPreTrainedModel",
          "LxmertVisualFeatureEncoder",
          "LxmertXLayer",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[str]			    =       [
          "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFLxmertForPreTraining",
          "TFLxmertMainLayer",
          "TFLxmertModel",
          "TFLxmertPreTrainedModel",
          "TFLxmertVisualFeatureEncoder",
      ]


if TYPE_CHECKING:
      from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
      from .tokenization_lxmert import LxmertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_lxmert_fast import LxmertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_lxmert import (
                LxmertEncoder,
                LxmertForPreTraining,
                LxmertForQuestionAnswering,
                LxmertModel,
                LxmertPreTrainedModel,
                LxmertVisualFeatureEncoder,
                LxmertXLayer,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_lxmert import (
                TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFLxmertForPreTraining,
                TFLxmertMainLayer,
                TFLxmertModel,
                TFLxmertPreTrainedModel,
                TFLxmertVisualFeatureEncoder,
            )

else:
      import sys

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