


from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
lowerCamelCase						=		0

lowerCamelCase						=		[
    [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],
]

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

lowerCamelCase						=		tuple[int, int]





class  _a							:




	def __init__( self						:		Tuple		, _SCREAMING_SNAKE_CASE						:		int		, _SCREAMING_SNAKE_CASE						:		Tuple		, _SCREAMING_SNAKE_CASE						:		Any		, _SCREAMING_SNAKE_CASE						:		List[str]		, _SCREAMING_SNAKE_CASE						:		List[Any]		, _SCREAMING_SNAKE_CASE						:		List[str]		, )->	None:
			lowerCAmelCase__       :      Dict   					= pos_x
			lowerCAmelCase__       :      List[str]   					= pos_y
			lowerCAmelCase__       :      int   					= (pos_y, pos_x)
			lowerCAmelCase__       :      Dict   					= goal_x
			lowerCAmelCase__       :      Dict   					= goal_y
			lowerCAmelCase__       :      Dict   					= g_cost
			lowerCAmelCase__       :      List[Any]   					= parent
			lowerCAmelCase__       :      Any   					= self.calculate_heuristic()
			lowerCAmelCase__       :      str   					= self.g_cost + self.h_cost




	def 							UpperCAmelCase__( self						:		List[Any]		)->	float:
			lowerCAmelCase__       :      Optional[Any]   					= self.pos_x - self.goal_x
			lowerCAmelCase__       :      Any   					= self.pos_y - self.goal_y
			if HEURISTIC == 1:
					return abs(lowerCAmelCase__		) + abs(lowerCAmelCase__		)
			else:
					return sqrt(dy**2 + dx**2		)




	def __lt__( self						:		str		, _SCREAMING_SNAKE_CASE						:		Any		)->	bool:
			return self.f_cost < other.f_cost





class  _a							:




	def __init__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		int		, _SCREAMING_SNAKE_CASE						:		Optional[int]		)->	Any:
			lowerCAmelCase__       :      List[str]   					= Node(start[1]		, start[0]		, goal[1]		, goal[0]		, 0		, lowerCAmelCase__		)
			lowerCAmelCase__       :      Optional[Any]   					= Node(goal[1]		, goal[0]		, goal[1]		, goal[0]		, 9_9999		, lowerCAmelCase__		)

			lowerCAmelCase__       :      int   					= [self.start]
			lowerCAmelCase__       :      Optional[int]   					= []

			lowerCAmelCase__       :      Union[str, Any]   					= False




	def 							UpperCAmelCase__( self						:		Tuple		)->	list[TPosition]:
			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(lowerCAmelCase__		)

					self.closed_nodes.append(lowerCAmelCase__		)
					lowerCAmelCase__       :      List[Any]   					= 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
									lowerCAmelCase__       :      List[str]   					= 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__		)

			return [self.start.pos]




	def 							UpperCAmelCase__( self						:		Optional[int]		, _SCREAMING_SNAKE_CASE						:		Optional[Any]		)->	list[Node]:
			lowerCAmelCase__       :      str   					= []
			for action in delta:
					lowerCAmelCase__       :      Union[str, Any]   					= parent.pos_x + action[1]
					lowerCAmelCase__       :      Union[str, Any]   					= 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						:		Optional[int]		, _SCREAMING_SNAKE_CASE						:		List[Any]		)->	list[TPosition]:
			lowerCAmelCase__       :      Tuple   					= node
			lowerCAmelCase__       :      Any   					= []
			while current_node is not None:
					path.append((current_node.pos_y, current_node.pos_x)		)
					lowerCAmelCase__       :      int   					= current_node.parent
			path.reverse()
			return path





class  _a							:




	def __init__( self						:		Union[str, Any]		, _SCREAMING_SNAKE_CASE						:		List[str]		, _SCREAMING_SNAKE_CASE						:		Optional[Any]		)->	None:
			lowerCAmelCase__       :      str   					= AStar(lowerCAmelCase__		, lowerCAmelCase__		)
			lowerCAmelCase__       :      Optional[Any]   					= AStar(lowerCAmelCase__		, lowerCAmelCase__		)
			lowerCAmelCase__       :      List[Any]   					= False




	def 							UpperCAmelCase__( self						:		Dict		)->	list[TPosition]:
			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__       :      Tuple   					= self.fwd_astar.open_nodes.pop(0		)
					lowerCAmelCase__       :      Dict   					= self.bwd_astar.open_nodes.pop(0		)

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

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

					lowerCAmelCase__       :      str   					= current_bwd_node
					lowerCAmelCase__       :      int   					= current_fwd_node

					lowerCAmelCase__       :      Optional[Any]   					= {
					    self.fwd_astar: self.fwd_astar.get_successors(lowerCAmelCase__		),
					    self.bwd_astar: self.bwd_astar.get_successors(lowerCAmelCase__		),
					}

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

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

			return [self.fwd_astar.start.pos]




	def 							UpperCAmelCase__( self						:		Optional[int]		, _SCREAMING_SNAKE_CASE						:		str		, _SCREAMING_SNAKE_CASE						:		List[Any]		)->	list[TPosition]:
			lowerCAmelCase__       :      Dict   					= self.fwd_astar.retrace_path(lowerCAmelCase__		)
			lowerCAmelCase__       :      Union[str, Any]   					= self.bwd_astar.retrace_path(lowerCAmelCase__		)
			bwd_path.pop()
			bwd_path.reverse()
			lowerCAmelCase__       :      int   					= fwd_path + bwd_path
			return path


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

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

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




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase						=		logging.get_logger(__name__)

lowerCamelCase						=		{
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}





class  _a							(    _lowercase):
	_a  :  List[Any]				   =							'''dpr'''




	def __init__( self						:		List[str]		, _SCREAMING_SNAKE_CASE						:		List[str]=3_0522		, _SCREAMING_SNAKE_CASE						:		Optional[int]=768		, _SCREAMING_SNAKE_CASE						:		List[str]=12		, _SCREAMING_SNAKE_CASE						:		Tuple=12		, _SCREAMING_SNAKE_CASE						:		str=3072		, _SCREAMING_SNAKE_CASE						:		Optional[Any]="gelu"		, _SCREAMING_SNAKE_CASE						:		Dict=0.1		, _SCREAMING_SNAKE_CASE						:		Optional[int]=0.1		, _SCREAMING_SNAKE_CASE						:		List[str]=512		, _SCREAMING_SNAKE_CASE						:		int=2		, _SCREAMING_SNAKE_CASE						:		Optional[Any]=0.02		, _SCREAMING_SNAKE_CASE						:		Tuple=1E-12		, _SCREAMING_SNAKE_CASE						:		Union[str, Any]=0		, _SCREAMING_SNAKE_CASE						:		List[str]="absolute"		, _SCREAMING_SNAKE_CASE						:		int = 0		, **_SCREAMING_SNAKE_CASE						:		Optional[Any]		, )->	Optional[int]:
			super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE		, **_SCREAMING_SNAKE_CASE		)

			lowerCAmelCase__       :      Union[str, Any]   					= vocab_size
			lowerCAmelCase__       :      Tuple   					= hidden_size
			lowerCAmelCase__       :      Union[str, Any]   					= num_hidden_layers
			lowerCAmelCase__       :      List[Any]   					= num_attention_heads
			lowerCAmelCase__       :      Optional[int]   					= hidden_act
			lowerCAmelCase__       :      Optional[Any]   					= intermediate_size
			lowerCAmelCase__       :      Optional[Any]   					= hidden_dropout_prob
			lowerCAmelCase__       :      int   					= attention_probs_dropout_prob
			lowerCAmelCase__       :      str   					= max_position_embeddings
			lowerCAmelCase__       :      List[Any]   					= type_vocab_size
			lowerCAmelCase__       :      Optional[int]   					= initializer_range
			lowerCAmelCase__       :      List[str]   					= layer_norm_eps
			lowerCAmelCase__       :      Dict   					= projection_dim
			lowerCAmelCase__       :      int   					= position_embedding_type




