



from __future__ import annotations

a     :    str      						=					list[tuple[int, int]]

a     :    str      						=					[
    [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],
]

a     :    Optional[int]      						=					([-1, 0], [0, -1], [1, 0], [0, 1])  # up, left, down, right

class     UpperCamelCase_				:





	def __init__(						self	,	A	,	A	,	A	,	A	,	A	,	A	,	)    ->    str:
								UpperCAmelCase  :	List[str]							  =	pos_x
								UpperCAmelCase  :	List[str]							  =	pos_y
								UpperCAmelCase  :	Optional[int]							  =	(pos_y, pos_x)
								UpperCAmelCase  :	int							  =	goal_x
								UpperCAmelCase  :	int							  =	goal_y
								UpperCAmelCase  :	Union[str, Any]							  =	g_cost
								UpperCAmelCase  :	Dict							  =	parent
								UpperCAmelCase  :	Tuple							  =	self.calculate_heuristic()





	def 				_lowercase(						self					)    ->    float:
								UpperCAmelCase  :	int							  =	abs(self.pos_x - self.goal_x					)
								UpperCAmelCase  :	List[Any]							  =	abs(self.pos_y - self.goal_y					)
								return dx + dy






	def __lt__(						self	,	A					)    ->    bool:
								return self.f_cost < other.f_cost




class     UpperCamelCase_				:





	def __init__(						self	,	A	,	A					)    ->    int:
								UpperCAmelCase  :	Any							  =	Node(start[1]	,	start[0]	,	goal[1]	,	goal[0]	,	0	,	A					)
								UpperCAmelCase  :	Optional[Any]							  =	Node(goal[1]	,	goal[0]	,	goal[1]	,	goal[0]	,	99999	,	A					)

								UpperCAmelCase  :	Union[str, Any]							  =	[self.start]
								UpperCAmelCase  :	list[Node]							  =	[]

								UpperCAmelCase  :	Any							  =	False





	def 				_lowercase(						self					)    ->    Path | None:
								while self.open_nodes:
															# Open Nodes are sorted using __lt__
															self.open_nodes.sort()
															UpperCAmelCase  :	str							  =	self.open_nodes.pop(0					)

															if current_node.pos == self.target.pos:
																						UpperCAmelCase  :	List[Any]							  =	True
																						return self.retrace_path(A					)

															self.closed_nodes.append(A					)
															UpperCAmelCase  :	Any							  =	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  :	Tuple							  =	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 				_lowercase(						self	,	A					)    ->    list[Node]:
								UpperCAmelCase  :	int							  =	[]
								for action in delta:
															UpperCAmelCase  :	Optional[int]							  =	parent.pos_x + action[1]
															UpperCAmelCase  :	Union[str, Any]							  =	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 				_lowercase(						self	,	A					)    ->    Path:
								UpperCAmelCase  :	str							  =	node
								UpperCAmelCase  :	Tuple							  =	[]
								while current_node is not None:
															path.append((current_node.pos_y, current_node.pos_x)					)
															UpperCAmelCase  :	Union[str, Any]							  =	current_node.parent
								path.reverse()
								return path


if __name__ == "__main__":
							a     :    str      						=					(0, 0)
							a     :    Union[str, Any]      						=					(len(grid) - 1, len(grid[0]) - 1)
							for elem in grid:
														print(elem)

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

							a     :    Optional[Any]      						=					GreedyBestFirst(init, goal)
							a     :    Optional[Any]      						=					greedy_bf.search()
							if path:
														for pos_x, pos_y in path:
																					a     :    Any      						=					2

														for elem in grid:
																					print(elem)






'''simple docstring'''




from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
							from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

