






'''simple docstring'''







from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_A			:    List[Any]					  =0

_A			:    int					  =[
    [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[Any]					  =[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

_A			:    Optional[Any]					  =tuple[int, int]

class _lowercase			:




							def __init__(							self:       List[str]    ,							UpperCamelCase__:       int    ,							UpperCamelCase__:       int    ,							UpperCamelCase__:       int    ,							UpperCamelCase__:       int    ,							UpperCamelCase__:       int    ,							UpperCamelCase__:       Node | None    ,							):
														lowerCamelCase__      :			Dict 						= pos_x
														lowerCamelCase__      :			int 						= pos_y
														lowerCamelCase__      :			List[Any] 						= (pos_y, pos_x)
														lowerCamelCase__      :			Dict 						= goal_x
														lowerCamelCase__      :			Any 						= goal_y
														lowerCamelCase__      :			List[Any] 						= g_cost
														lowerCamelCase__      :			Optional[Any] 						= parent
														lowerCamelCase__      :			Any 						= self.calculate_heuristic()
														lowerCamelCase__      :			List[Any] 						= self.g_cost + self.h_cost




							def 	lowerCamelCase_       (							self:       str  ):
														lowerCamelCase__      :			int 						= self.pos_x - self.goal_x
														lowerCamelCase__      :			Union[str, Any] 						= self.pos_y - self.goal_y
														if HEURISTIC == 1:
																					return abs(UpperCamelCase__  ) + abs(UpperCamelCase__  )
														else:
																					return sqrt(dy**2 + dx**2  )




							def __lt__(							self:       Optional[int]    ,							UpperCamelCase__:       Node  ):
														return self.f_cost < other.f_cost



class _lowercase			:




							def __init__(							self:       str    ,							UpperCamelCase__:       TPosition    ,							UpperCamelCase__:       TPosition  ):
														lowerCamelCase__      :			Tuple 						= Node(start[1]    ,							start[0]    ,							goal[1]    ,							goal[0]    ,							0    ,							UpperCamelCase__  )
														lowerCamelCase__      :			Union[str, Any] 						= Node(goal[1]    ,							goal[0]    ,							goal[1]    ,							goal[0]    ,							99_999    ,							UpperCamelCase__  )

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

														lowerCamelCase__      :			List[Any] 						= False




							def 	lowerCamelCase_       (							self:       int  ):
														while self.open_nodes:
																					# Open Nodes are sorted using __lt__
																					self.open_nodes.sort()
																					lowerCamelCase__      :			Dict 						= self.open_nodes.pop(0  )

																					if current_node.pos == self.target.pos:
																												return self.retrace_path(UpperCamelCase__  )

																					self.closed_nodes.append(UpperCamelCase__  )
																					lowerCamelCase__      :			Tuple 						= self.get_successors(UpperCamelCase__  )

																					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(UpperCamelCase__  )
																												else:
																																			# retrieve the best current path
																																			lowerCamelCase__      :			int 						= self.open_nodes.pop(self.open_nodes.index(UpperCamelCase__  )  )

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

														return [self.start.pos]




							def 	lowerCamelCase_       (							self:       Any    ,							UpperCamelCase__:       Node  ):
														lowerCamelCase__      :			List[str] 						= []
														for action in delta:
																					lowerCamelCase__      :			List[str] 						= parent.pos_x + action[1]
																					lowerCamelCase__      :			Tuple 						= parent.pos_y + action[0]
																					if not (0 <= pos_x <= len(grid[0]  ) - 1 and 0 <= pos_y <= len(UpperCamelCase__  ) - 1):
																												continue

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

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




							def 	lowerCamelCase_       (							self:       Any    ,							UpperCamelCase__:       Node | None  ):
														lowerCamelCase__      :			Dict 						= node
														lowerCamelCase__      :			Optional[Any] 						= []
														while current_node is not None:
																					path.append((current_node.pos_y, current_node.pos_x)  )
																					lowerCamelCase__      :			List[Any] 						= current_node.parent
														path.reverse()
														return path



class _lowercase			:




							def __init__(							self:       Dict    ,							UpperCamelCase__:       TPosition    ,							UpperCamelCase__:       TPosition  ):
														lowerCamelCase__      :			Dict 						= AStar(UpperCamelCase__    ,							UpperCamelCase__  )
														lowerCamelCase__      :			str 						= AStar(UpperCamelCase__    ,							UpperCamelCase__  )
														lowerCamelCase__      :			Optional[Any] 						= False




							def 	lowerCamelCase_       (							self:       List[str]  ):
														while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
																					self.fwd_astar.open_nodes.sort()
																					self.bwd_astar.open_nodes.sort()
																					lowerCamelCase__      :			List[Any] 						= self.fwd_astar.open_nodes.pop(0  )
																					lowerCamelCase__      :			List[Any] 						= self.bwd_astar.open_nodes.pop(0  )

																					if current_bwd_node.pos == current_fwd_node.pos:
																												return self.retrace_bidirectional_path(
																												    UpperCamelCase__    ,							UpperCamelCase__  )

																					self.fwd_astar.closed_nodes.append(UpperCamelCase__  )
																					self.bwd_astar.closed_nodes.append(UpperCamelCase__  )

																					lowerCamelCase__      :			Optional[Any] 						= current_bwd_node
																					lowerCamelCase__      :			Optional[int] 						= current_fwd_node

																					lowerCamelCase__      :			Optional[int] 						= {
																					    self.fwd_astar: self.fwd_astar.get_successors(UpperCamelCase__  ),
																					    self.bwd_astar: self.bwd_astar.get_successors(UpperCamelCase__  ),
																					}

																					for astar in [self.fwd_astar, self.bwd_astar]:
																												for child_node in successors[astar]:
																																			if child_node in astar.closed_nodes:
																																										continue

																																			if child_node not in astar.open_nodes:
																																										astar.open_nodes.append(UpperCamelCase__  )
																																			else:
																																										# retrieve the best current path
																																										lowerCamelCase__      :			Union[str, Any] 						= astar.open_nodes.pop(
																																										    astar.open_nodes.index(UpperCamelCase__  )  )

																																										if child_node.g_cost < better_node.g_cost:
																																																	astar.open_nodes.append(UpperCamelCase__  )
																																										else:
																																																	astar.open_nodes.append(UpperCamelCase__  )

														return [self.fwd_astar.start.pos]




							def 	lowerCamelCase_       (							self:       List[Any]    ,							UpperCamelCase__:       Node    ,							UpperCamelCase__:       Node  ):
														lowerCamelCase__      :			Optional[Any] 						= self.fwd_astar.retrace_path(UpperCamelCase__  )
														lowerCamelCase__      :			List[Any] 						= self.bwd_astar.retrace_path(UpperCamelCase__  )
														bwd_path.pop()
														bwd_path.reverse()
														lowerCamelCase__      :			Any 						= fwd_path + bwd_path
														return path


if __name__ == "__main__":
			# all coordinates are given in format [y,x]
			_A			:    Optional[Any]					  =(0, 0)
			_A			:    Tuple					  =(len(grid) - 1, len(grid[0]) - 1)
			for elem in grid:
						print(elem)

			_A			:    Optional[Any]					  =time.time()
			_A			:    List[Any]					  =AStar(init, goal)
			_A			:    Dict					  =a_star.search()
			_A			:    Any					  =time.time() - start_time
			print(F'AStar execution time = {end_time:f} seconds')

			_A			:    List[Any]					  =time.time()
			_A			:    str					  =BidirectionalAStar(init, goal)
			_A			:    Optional[Any]					  =time.time() - bd_start_time
			print(F'BidirectionalAStar execution time = {bd_end_time:f} seconds')









'''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

