



"""simple docstring"""





from __future__ import annotations

lowerCamelCase  			=		[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def   a__      ( lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__      ,     lowerCAmelCase__      ,     ):
      UpperCAmelCase_     					=				[
          [0 for col in range(len(grid[0] ) )] for row in range(len(_A ) )
      ]  # the reference grid
      UpperCAmelCase_     					=				1
      UpperCAmelCase_     					=				[
          [0 for col in range(len(grid[0] ) )] for row in range(len(_A ) )
      ]  # the action grid

      UpperCAmelCase_     					=				init[0]
      UpperCAmelCase_     					=				init[1]
      UpperCAmelCase_     					=				0
      UpperCAmelCase_     					=				g + heuristic[x][y]  # cost from starting cell to destination cell
      UpperCAmelCase_     					=				[[f, g, x, y]]

      UpperCAmelCase_     					=				False  # flag that is set when search is complete
      UpperCAmelCase_     					=				False  # flag set if we can't find expand

      while not found and not resign:
            if len(_A ) == 0:
                  raise ValueError("Algorithm is unable to find solution" )
            else:  # to choose the least costliest action so as to move closer to the goal
                  cell.sort()
                  cell.reverse()
                  UpperCAmelCase_     					=				cell.pop()
                  UpperCAmelCase_     					=				next_cell[2]
                  UpperCAmelCase_     					=				next_cell[3]
                  UpperCAmelCase_     					=				next_cell[1]

                  if x == goal[0] and y == goal[1]:
                        UpperCAmelCase_     					=				True
                  else:
                        for i in range(len(_A ) ):  # to try out different valid actions
                              UpperCAmelCase_     					=				x + DIRECTIONS[i][0]
                              UpperCAmelCase_     					=				y + DIRECTIONS[i][1]
                              if xa >= 0 and xa < len(_A ) and ya >= 0 and ya < len(grid[0] ):
                                    if closed[xa][ya] == 0 and grid[xa][ya] == 0:
                                          UpperCAmelCase_     					=				g + cost
                                          UpperCAmelCase_     					=				ga + heuristic[xa][ya]
                                          cell.append([fa, ga, xa, ya] )
                                          UpperCAmelCase_     					=				1
                                          UpperCAmelCase_     					=				i
      UpperCAmelCase_     					=				[]
      UpperCAmelCase_     					=				goal[0]
      UpperCAmelCase_     					=				goal[1]
      invpath.append([x, y] )  # we get the reverse path from here
      while x != init[0] or y != init[1]:
            UpperCAmelCase_     					=				x - DIRECTIONS[action[x][y]][0]
            UpperCAmelCase_     					=				y - DIRECTIONS[action[x][y]][1]
            UpperCAmelCase_     					=				xa
            UpperCAmelCase_     					=				ya
            invpath.append([x, y] )

      UpperCAmelCase_     					=				[]
      for i in range(len(_A ) ):
            path.append(invpath[len(_A ) - 1 - i] )
      return path, action


if __name__ == "__main__":
  lowerCamelCase  			=		[
      [0, 1, 0, 0, 0, 0],
      [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
      [0, 1, 0, 0, 0, 0],
      [0, 1, 0, 0, 1, 0],
      [0, 0, 0, 0, 1, 0],
  ]

  lowerCamelCase  			=		[0, 0]
  # all coordinates are given in format [y,x]
  lowerCamelCase  			=		[len(grid) - 1, len(grid[0]) - 1]
  lowerCamelCase  			=		1

  # the cost map which pushes the path closer to the goal
  lowerCamelCase  			=		[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
  for i in range(len(grid)):
    for j in range(len(grid[0])):
      lowerCamelCase  			=		abs(i - goal[0]) + abs(j - goal[1])
      if grid[i][j] == 1:
        # added extra penalty in the heuristic map
        lowerCamelCase  			=		99

  lowerCamelCase  			=		search(grid, init, goal, cost, heuristic)

  print("""ACTION MAP""")
  for i in range(len(action)):
    print(action[i])

  for i in range(len(path)):
    print(path[i])





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__  :						str					=      {
    'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
    'processing_git': ['GitProcessor'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCamelCase__  :						str					=      [
      'GIT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'GitForCausalLM',
      'GitModel',
      'GitPreTrainedModel',
      'GitVisionModel',
  ]

if TYPE_CHECKING:
  from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
  from .processing_git import GitProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_git import (
        GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
        GitForCausalLM,
        GitModel,
        GitPreTrainedModel,
        GitVisionModel,
    )

else:
  import sys

  UpperCamelCase__  :						Tuple					=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




