

'''simple docstring'''





from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
A_	= 0

A_	= [
    [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_	= [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

A_	= tuple[int, int]


class  UpperCAmelCase :

		'''simple docstring'''






		def __init__(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			)  ->     None:






							'''simple docstring'''



							lowerCamelCase_  				=      pos_x
							lowerCamelCase_  				=      pos_y
							lowerCamelCase_  				=      (pos_y, pos_x)
							lowerCamelCase_  				=      goal_x
							lowerCamelCase_  				=      goal_y
							lowerCamelCase_  				=      g_cost
							lowerCamelCase_  				=      parent
							lowerCamelCase_  				=      self.calculate_heuristic()
							lowerCamelCase_  				=      self.g_cost + self.h_cost
		def 			UpperCamelCase(					self		)  ->     float:






							'''simple docstring'''



							lowerCamelCase_  				=      self.pos_x - self.goal_x
							lowerCamelCase_  				=      self.pos_y - self.goal_y
							if HEURISTIC == 1:
												return abs(SCREAMING_SNAKE_CASE_		) + abs(SCREAMING_SNAKE_CASE_		)
							else:
												return sqrt(dy**2 + dx**2		)






		def __lt__(					self   ,			SCREAMING_SNAKE_CASE_		)  ->     bool:






							'''simple docstring'''



							return self.f_cost < other.f_cost


class  UpperCAmelCase :

		'''simple docstring'''






		def __init__(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      Node(start[1]   ,			start[0]   ,			goal[1]   ,			goal[0]   ,			0   ,			SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      Node(goal[1]   ,			goal[0]   ,			goal[1]   ,			goal[0]   ,			99999   ,			SCREAMING_SNAKE_CASE_		)

							lowerCamelCase_  				=      [self.start]
							lowerCamelCase_  				=      []

							lowerCamelCase_  				=      False
		def 			UpperCamelCase(					self		)  ->     list[TPosition]:






							'''simple docstring'''



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

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

												self.closed_nodes.append(SCREAMING_SNAKE_CASE_		)
												lowerCamelCase_  				=      self.get_successors(SCREAMING_SNAKE_CASE_		)

												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(SCREAMING_SNAKE_CASE_		)
																	else:
																						# retrieve the best current path
																						lowerCamelCase_  				=      self.open_nodes.pop(self.open_nodes.index(SCREAMING_SNAKE_CASE_		)		)

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

							return [self.start.pos]
		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_		)  ->     list[Node]:






							'''simple docstring'''



							lowerCamelCase_  				=      []
							for action in delta:
												lowerCamelCase_  				=      parent.pos_x + action[1]
												lowerCamelCase_  				=      parent.pos_y + action[0]
												if not (0 <= pos_x <= len(grid[0]		) - 1 and 0 <= pos_y <= len(SCREAMING_SNAKE_CASE_		) - 1):
																	continue

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

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






		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_		)  ->     list[TPosition]:






							'''simple docstring'''



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


class  UpperCAmelCase :

		'''simple docstring'''






		def __init__(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     None:






							'''simple docstring'''



							lowerCamelCase_  				=      AStar(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      AStar(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      False
		def 			UpperCamelCase(					self		)  ->     list[TPosition]:






							'''simple docstring'''



							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_  				=      self.fwd_astar.open_nodes.pop(0		)
												lowerCamelCase_  				=      self.bwd_astar.open_nodes.pop(0		)

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

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

												lowerCamelCase_  				=      current_bwd_node
												lowerCamelCase_  				=      current_fwd_node

												lowerCamelCase_  				=      {
												    self.fwd_astar: self.fwd_astar.get_successors(SCREAMING_SNAKE_CASE_		),
												    self.bwd_astar: self.bwd_astar.get_successors(SCREAMING_SNAKE_CASE_		),
												}

												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(SCREAMING_SNAKE_CASE_		)
																						else:
																											# retrieve the best current path
																											lowerCamelCase_  				=      astar.open_nodes.pop(
																											    astar.open_nodes.index(SCREAMING_SNAKE_CASE_		)		)

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

							return [self.fwd_astar.start.pos]






		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     list[TPosition]:






							'''simple docstring'''



							lowerCamelCase_  				=      self.fwd_astar.retrace_path(SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      self.bwd_astar.retrace_path(SCREAMING_SNAKE_CASE_		)
							bwd_path.pop()
							bwd_path.reverse()
							lowerCamelCase_  				=      fwd_path + bwd_path
							return path


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

				A_	= time.time()
				A_	= AStar(init, goal)
				A_	= a_star.search()
				A_	= time.time() - start_time
				print(f'''AStar execution time = {end_time:f} seconds''')

				A_	= time.time()
				A_	= BidirectionalAStar(init, goal)
				A_	= time.time() - bd_start_time
				print(f'''BidirectionalAStar execution time = {bd_end_time:f} seconds''')










from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
					import timm


if is_torch_available():
					from torch import Tensor

class 							__SCREAMING_SNAKE_CASE       (  _a ,		_a							):
							snake_case  :   int      =							"""pixel_values"""
							snake_case  :   List[Any]      =							False
							snake_case  :   str      =							TimmBackboneConfig






							def __init__(    self	,			__lowerCAmelCase	,			**__lowerCAmelCase	):
														requires_backends(self	,			"""timm"""	)
														super().__init__(__lowerCAmelCase	)
														UpperCamelCase__					  =      config

														if config.backbone is None:
																					raise ValueError("""backbone is not set in the config. Please set it to a timm model name."""	)

														if config.backbone not in timm.list_models():
																					raise ValueError(f"""backbone {config.backbone} is not supported by timm."""	)

														if hasattr(__lowerCAmelCase	,			"""out_features"""	) and config.out_features is not None:
																					raise ValueError("""out_features is not supported by TimmBackbone. Please use out_indices instead."""	)

														UpperCamelCase__					  =      getattr(__lowerCAmelCase	,			"""use_pretrained_backbone"""	,			__lowerCAmelCase	)
														if pretrained is None:
																					raise ValueError("""use_pretrained_backbone is not set in the config. Please set it to True or False."""	)

														# We just take the final layer by default. This matches the default for the transformers models.
														UpperCamelCase__					  =      config.out_indices if getattr(__lowerCAmelCase	,			"""out_indices"""	,			__lowerCAmelCase	) is not None else (-1,)

														UpperCamelCase__					  =      timm.create_model(
														    config.backbone	,			pretrained=__lowerCAmelCase	,			features_only=config.features_only	,			in_chans=config.num_channels	,			out_indices=__lowerCAmelCase	,			**__lowerCAmelCase	,			)
														# These are used to control the output of the model when called. If output_hidden_states is True, then
														# return_layers is modified to include all layers.
														UpperCamelCase__					  =      self._backbone.return_layers
														UpperCamelCase__					  =      {layer["""module"""]: str(__lowerCAmelCase	) for i, layer in enumerate(self._backbone.feature_info.info	)}
														super()._init_backbone(__lowerCAmelCase	)






							@classmethod
							def 					_lowerCamelCase		(    cls	,			__lowerCAmelCase	,			*__lowerCAmelCase	,			**__lowerCAmelCase	):
														requires_backends(cls	,			["""vision""", """timm"""]	)
														from ...models.timm_backbone import TimmBackboneConfig

														UpperCamelCase__					  =      kwargs.pop("""config"""	,			TimmBackboneConfig()	)

														UpperCamelCase__					  =      kwargs.pop("""use_timm_backbone"""	,			__lowerCAmelCase	)
														if not use_timm:
																					raise ValueError("""use_timm_backbone must be True for timm backbones"""	)

														UpperCamelCase__					  =      kwargs.pop("""num_channels"""	,			config.num_channels	)
														UpperCamelCase__					  =      kwargs.pop("""features_only"""	,			config.features_only	)
														UpperCamelCase__					  =      kwargs.pop("""use_pretrained_backbone"""	,			config.use_pretrained_backbone	)
														UpperCamelCase__					  =      kwargs.pop("""out_indices"""	,			config.out_indices	)
														UpperCamelCase__					  =      TimmBackboneConfig(
														    backbone=__lowerCAmelCase	,			num_channels=__lowerCAmelCase	,			features_only=__lowerCAmelCase	,			use_pretrained_backbone=__lowerCAmelCase	,			out_indices=__lowerCAmelCase	,			)
														return super()._from_config(__lowerCAmelCase	,			**__lowerCAmelCase	)






							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	):
														pass







							def 					_lowerCamelCase		(    self	,			__lowerCAmelCase	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			__lowerCAmelCase=None	,			**__lowerCAmelCase	):
														UpperCamelCase__					  =      return_dict if return_dict is not None else self.config.use_return_dict
														UpperCamelCase__					  =      (
														    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
														)
														UpperCamelCase__					  =      output_attentions if output_attentions is not None else self.config.output_attentions

														if output_attentions:
																					raise ValueError("""Cannot output attentions for timm backbones at the moment"""	)

														if output_hidden_states:
																					# We modify the return layers to include all the stages of the backbone
																					UpperCamelCase__					  =      self._all_layers
																					UpperCamelCase__					  =      self._backbone(__lowerCAmelCase	,			**__lowerCAmelCase	)
																					UpperCamelCase__					  =      self._return_layers
																					UpperCamelCase__					  =      tuple(hidden_states[i] for i in self.out_indices	)
														else:
																					UpperCamelCase__					  =      self._backbone(__lowerCAmelCase	,			**__lowerCAmelCase	)
																					UpperCamelCase__					  =      None

														UpperCamelCase__					  =      tuple(__lowerCAmelCase	)
														UpperCamelCase__					  =      tuple(__lowerCAmelCase	) if hidden_states is not None else None

														if not return_dict:
																					UpperCamelCase__					  =      (feature_maps,)
																					if output_hidden_states:
																												UpperCamelCase__					  =      output + (hidden_states,)
																					return output

														return BackboneOutput(feature_maps=__lowerCAmelCase	,			hidden_states=__lowerCAmelCase	,			attentions=__lowerCAmelCase	)




