


'''simple docstring'''



from __future__ import annotations

_lowercase     :     Tuple        =	list[tuple[int, int]]

_lowercase     :     Dict        =	[
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

_lowercase     :     Union[str, Any]        =	([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right






class 			UpperCamelCase__:




				def __init__(						self     :					List[Any] ,       lowerCAmelCase     :					Dict ,       lowerCAmelCase     :					Dict ,       lowerCAmelCase     :					List[str] ,       lowerCAmelCase     :					int ,       lowerCAmelCase     :					Optional[Any] ,       lowerCAmelCase     :					int ,       )->	Any:

										"""simple docstring"""




										UpperCAmelCase								=      pos_x
										UpperCAmelCase								=      pos_y
										UpperCAmelCase								=      (pos_y, pos_x)
										UpperCAmelCase								=      goal_x
										UpperCAmelCase								=      goal_y
										UpperCAmelCase								=      g_cost
										UpperCAmelCase								=      parent
										UpperCAmelCase								=      self.calculate_heuristic()




				def 	a__(						self     :					Any )->	float:

										"""simple docstring"""




										UpperCAmelCase								=      abs(self.pos_x - self.goal_x )
										UpperCAmelCase								=      abs(self.pos_y - self.goal_y )
										return dx + dy





				def __lt__(						self     :					Optional[Any] ,       lowerCAmelCase     :					str )->	bool:

										"""simple docstring"""




										return self.f_cost < other.f_cost







class 			UpperCamelCase__:




				def __init__(						self     :					List[str] ,       lowerCAmelCase     :					Tuple ,       lowerCAmelCase     :					Dict )->	Dict:

										"""simple docstring"""




										UpperCAmelCase								=      Node(start[1] ,       start[0] ,       goal[1] ,       goal[0] ,       0 ,       a_ )
										UpperCAmelCase								=      Node(goal[1] ,       goal[0] ,       goal[1] ,       goal[0] ,       99999 ,       a_ )

										UpperCAmelCase								=      [self.start]
										UpperCAmelCase								=      []

										UpperCAmelCase								=      False




				def 	a__(						self     :					Tuple )->	Path | None:

										"""simple docstring"""




										while self.open_nodes:
																# Open Nodes are sorted using __lt__
																self.open_nodes.sort()
																UpperCAmelCase								=      self.open_nodes.pop(0 )

																if current_node.pos == self.target.pos:
																						UpperCAmelCase								=      True
																						return self.retrace_path(a_ )

																self.closed_nodes.append(a_ )
																UpperCAmelCase								=      self.get_successors(a_ )

																for child_node in successors:
																						if child_node in self.closed_nodes:
																												continue

																						if child_node not in self.open_nodes:
																												self.open_nodes.append(a_ )
																						else:
																												# retrieve the best current path
																												UpperCAmelCase								=      self.open_nodes.pop(self.open_nodes.index(a_ ) )

																												if child_node.g_cost < better_node.g_cost:
																																		self.open_nodes.append(a_ )
																												else:
																																		self.open_nodes.append(a_ )

										if not self.reached:
																return [self.start.pos]
										return None




				def 	a__(						self     :					str ,       lowerCAmelCase     :					Optional[Any] )->	list[Node]:

										"""simple docstring"""




										UpperCAmelCase								=      []
										for action in delta:
																UpperCAmelCase								=      parent.pos_x + action[1]
																UpperCAmelCase								=      parent.pos_y + action[0]

																if not (0 <= pos_x <= len(grid[0] ) - 1 and 0 <= pos_y <= len(a_ ) - 1):
																						continue

																if grid[pos_y][pos_x] != 0:
																						continue

																successors.append(
																    Node(
																        a_ ,       a_ ,       self.target.pos_y ,       self.target.pos_x ,       parent.g_cost + 1 ,       a_ ,       ) )
										return successors





				def 	a__(						self     :					List[str] ,       lowerCAmelCase     :					Any )->	Path:

										"""simple docstring"""




										UpperCAmelCase								=      node
										UpperCAmelCase								=      []
										while current_node is not None:
																path.append((current_node.pos_y, current_node.pos_x) )
																UpperCAmelCase								=      current_node.parent
										path.reverse()
										return path


if __name__ == "__main__":
	_lowercase     :     Dict        =	(0, 0)
	_lowercase     :     int        =	(len(grid) - 1, len(grid[0]) - 1)
	for elem in grid:
		print(elem)

	print("""------""")

	_lowercase     :     Optional[int]        =	GreedyBestFirst(init, goal)
	_lowercase     :     List[Any]        =	greedy_bf.search()
	if path:
		for pos_x, pos_y in path:
			_lowercase     :     Union[str, Any]        =	2

		for elem in grid:
			print(elem)








'''simple docstring'''




import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


_a					:			List[Any]							=    logging.get_logger(__name__)



class 							lowercase_						(		a			):

  '''simple docstring'''





  def __init__(  self ,			*a_ ,			**a_  )				->					None:


    """simple docstring"""
    warnings.warn(
        'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
        ' use DonutImageProcessor instead.' ,			a_ ,			)
    super().__init__(*a_ ,			**a_  )


