from queue import PriorityQueue
from typing import Any

import numpy as np
def  snake_case						(__lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      )	->	float | int:

      '''simple docstring'''



      for nxt, d in graph[v]:
            if nxt in visited_forward:
                  continue
            _snake_case						:					Union[str, Any]    =   cst_fwd.get(__lowercase ,      np.inf						)
            _snake_case						:					Any    =   cst_fwd[v] + d
            if new_cost_f < old_cost_f:
                  queue.put((new_cost_f, nxt)						)
                  _snake_case						:					str    =   new_cost_f
                  _snake_case						:					Any    =   v
            if nxt in visited_backward:
                  if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
                        _snake_case						:					int    =   cst_fwd[v] + d + cst_bwd[nxt]
      return shortest_distance
def  snake_case						(__lowercase ,      __lowercase ,      __lowercase ,      __lowercase						)	->	int:

      '''simple docstring'''



      _snake_case						:					List[str]    =   -1

      _snake_case						:					List[str]    =   set()
      _snake_case						:					Optional[Any]    =   set()
      _snake_case						:					Optional[int]    =   {source: 0}
      _snake_case						:					Any    =   {destination: 0}
      _snake_case						:					int    =   {source: None}
      _snake_case						:					List[Any]    =   {destination: None}
      _snake_case						:					PriorityQueue[Any]    =   PriorityQueue()
      _snake_case						:					PriorityQueue[Any]    =   PriorityQueue()

      _snake_case						:					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():
            _snake_case						:					Optional[int]    =   queue_forward.get()
            visited_forward.add(__lowercase						)

            _snake_case						:					int    =   queue_backward.get()
            visited_backward.add(__lowercase						)

            _snake_case						:					str    =   pass_and_relaxation(
                __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      __lowercase ,      )

            _snake_case						:					str    =   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:
            _snake_case						:					str    =   shortest_distance
      return shortest_path_distance


__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			{
    '''B''': [['''C''', 1]],
    '''C''': [['''D''', 1]],
    '''D''': [['''F''', 1]],
    '''E''': [['''B''', 1], ['''G''', 2]],
    '''F''': [],
    '''G''': [['''F''', 1]],
}
__SCREAMING_SNAKE_CASE						:   List[Any]         =			{
    '''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()
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE						:   Union[str, Any]         =			[
				    'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'AutoformerForPrediction',
				    'AutoformerModel',
				    'AutoformerPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_autoformer import (
				    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    AutoformerConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_autoformer import (
								    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    AutoformerForPrediction,
								    AutoformerModel,
								    AutoformerPreTrainedModel,
								)

else:
				import sys

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