


"""simple docstring"""

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


UpperCAmelCase__					=logging.get_logger(__name__)





class  lowerCamelCase__    (		_a     ):
      a			:  Optional[int]           =		"upernet"
      def __init__(		self						:						List[Any]   ,							A_						:						List[Any]=None   ,							A_						:						str=5_1_2   ,							A_						:						List[Any]=0.02   ,							A_						:						int=[1, 2, 3, 6]   ,							A_						:						List[str]=True   ,							A_						:						List[str]=0.4   ,							A_						:						Optional[Any]=3_8_4   ,							A_						:						Any=2_5_6   ,							A_						:						Optional[Any]=1   ,							A_						:						Optional[Any]=False   ,							A_						:						List[str]=2_5_5   ,							**A_						:						List[str]   ,							):






       '''simple docstring'''


       super().__init__(**A_				)

       if backbone_config is None:
        logger.info("""`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."""				)
        __lowercase						=						CONFIG_MAPPING["""resnet"""](out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]				)
       elif isinstance(A_   ,							A_				):
        __lowercase						=						backbone_config.get("""model_type"""				)
        __lowercase						=						CONFIG_MAPPING[backbone_model_type]
        __lowercase						=						config_class.from_dict(A_				)

       __lowercase						=						backbone_config
       __lowercase						=						hidden_size
       __lowercase						=						initializer_range
       __lowercase						=						pool_scales
       __lowercase						=						use_auxiliary_head
       __lowercase						=						auxiliary_loss_weight
       __lowercase						=						auxiliary_in_channels
       __lowercase						=						auxiliary_channels
       __lowercase						=						auxiliary_num_convs
       __lowercase						=						auxiliary_concat_input
       __lowercase						=						loss_ignore_index






      def SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       __lowercase						=						copy.deepcopy(self.__dict__				)
       __lowercase						=						self.backbone_config.to_dict()
       __lowercase						=						self.__class__.model_type
       return output




'''simple docstring'''
from __future__ import annotations

__SCREAMING_SNAKE_CASE					:				Optional[int]									=		list[tuple[int, int]]

__SCREAMING_SNAKE_CASE					:				Union[str, Any]									=		[
    [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],
]

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






class 					__lowerCAmelCase   :

						"""simple docstring"""






						def __init__(  self							:      List[str] ,  lowerCAmelCase							:      int ,  lowerCAmelCase							:      int ,  lowerCAmelCase							:      int ,  lowerCAmelCase							:      int ,  lowerCAmelCase							:      float ,  lowerCAmelCase							:      Node | None ,  ):
													A_			    =		pos_x
													A_			    =		pos_y
													A_			    =		(pos_y, pos_x)
													A_			    =		goal_x
													A_			    =		goal_y
													A_			    =		g_cost
													A_			    =		parent
													A_			    =		self.calculate_heuristic()






						def 				_UpperCAmelCase       (  self							:      Tuple	):
													A_			    =		abs(self.pos_x - self.goal_x	)
													A_			    =		abs(self.pos_y - self.goal_y	)
													return dx + dy






						def __lt__(  self							:      Tuple ,  lowerCAmelCase							:      Any	):
													return self.f_cost < other.f_cost






class 					__lowerCAmelCase   :

						"""simple docstring"""






						def __init__(  self							:      Union[str, Any] ,  lowerCAmelCase							:      tuple[int, int] ,  lowerCAmelCase							:      tuple[int, int]	):
													A_			    =		Node(start[1] ,  start[0] ,  goal[1] ,  goal[0] ,  0 ,  lowerCAmelCase	)
													A_			    =		Node(goal[1] ,  goal[0] ,  goal[1] ,  goal[0] ,  9_99_99 ,  lowerCAmelCase	)

													A_			    =		[self.start]
													A_			    =		[]

													A_			    =		False






						def 				_UpperCAmelCase       (  self							:      str	):
													while self.open_nodes:
																				# Open Nodes are sorted using __lt__
																				self.open_nodes.sort()
																				A_			    =		self.open_nodes.pop(0	)

																				if current_node.pos == self.target.pos:
																											A_			    =		True
																											return self.retrace_path(lowerCAmelCase	)

																				self.closed_nodes.append(lowerCAmelCase	)
																				A_			    =		self.get_successors(lowerCAmelCase	)

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

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

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






						def 				_UpperCAmelCase       (  self							:      List[Any] ,  lowerCAmelCase							:      Node	):
													A_			    =		[]
													for action in delta:
																				A_			    =		parent.pos_x + action[1]
																				A_			    =		parent.pos_y + action[0]

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

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

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






						def 				_UpperCAmelCase       (  self							:      Tuple ,  lowerCAmelCase							:      Node | None	):
													A_			    =		node
													A_			    =		[]
													while current_node is not None:
																				path.append((current_node.pos_y, current_node.pos_x)	)
																				A_			    =		current_node.parent
													path.reverse()
													return path


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

							print('''------''')

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

														for elem in grid:
																					print(elem)





