
from heapq import heappop, heappush

import numpy as np



def 						lowercase_      (       A__			,		A__			,		A__			,		A__			,		)							->							tuple[float | int, list[tuple[int, int]]]:
    """simple docstring"""

    snake_case					,							snake_case								= grid.shape
    snake_case								= [-1, 1, 0, 0]
    snake_case								= [0, 0, -1, 1]
    if allow_diagonal:
        dx += [-1, -1, 1, 1]
        dy += [-1, 1, -1, 1]

    snake_case					,							snake_case								= [(0, source)], set()
    snake_case								= np.full((rows, cols)			,		np.inf		)
    snake_case								= 0
    snake_case								= np.empty((rows, cols)			,		dtype=A__		)
    snake_case								= None

    while queue:
        ((snake_case)					,							(snake_case))								= heappop(A__		)
        if (x, y) in visited:
            continue
        visited.add((x, y)		)

        if (x, y) == destination:
            snake_case								= []
            while (x, y) != source:
                path.append((x, y)		)
                snake_case					,							snake_case								= predecessors[x, y]
            path.append(A__		)  # add the source manually
            path.reverse()
            return matrix[destination], path

        for i in range(len(A__		)		):
            snake_case					,							snake_case								= x + dx[i], y + dy[i]
            if 0 <= nx < rows and 0 <= ny < cols:
                snake_case								= grid[nx][ny]
                if next_node == 1 and matrix[nx, ny] > dist + 1:
                    heappush(A__			,		(dist + 1, (nx, ny))		)
                    snake_case								= dist + 1
                    snake_case								= (x, y)

    return np.inf, []


if __name__ == "__main__":
   import doctest

   doctest.testmod()



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A   =			{
    "configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A   =			[
       "LILT_PRETRAINED_MODEL_ARCHIVE_LIST",
       "LiltForQuestionAnswering",
       "LiltForSequenceClassification",
       "LiltForTokenClassification",
       "LiltModel",
       "LiltPreTrainedModel",
   ]

if TYPE_CHECKING:
   from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_lilt import (
          LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
          LiltForQuestionAnswering,
          LiltForSequenceClassification,
          LiltForTokenClassification,
          LiltModel,
          LiltPreTrainedModel,
      )

else:
   import sys

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

