





from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
_SCREAMING_SNAKE_CASE      	=		0

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

_SCREAMING_SNAKE_CASE      	=		tuple[int, int]
class SCREAMING_SNAKE_CASE_						:






						def __init__(      self      :      Optional[int]		,   _A      :      int		,   _A      :      int		,   _A      :      int		,   _A      :      int		,   _A      :      int		,   _A      :      Node | None		,   )							->    None:







							"""simple docstring"""


							snake_case_		:			int											=	pos_x
							snake_case_		:			List[Any]											=	pos_y
							snake_case_		:			Tuple											=	(pos_y, pos_x)
							snake_case_		:			Dict											=	goal_x
							snake_case_		:			Dict											=	goal_y
							snake_case_		:			Tuple											=	g_cost
							snake_case_		:			int											=	parent
							snake_case_		:			Dict											=	self.calculate_heuristic()
							snake_case_		:			List[Any]											=	self.g_cost + self.h_cost






						def UpperCAmelCase_				(      self      :      Optional[Any]	)							->    float:







							"""simple docstring"""


							snake_case_		:			Any											=	self.pos_x - self.goal_x
							snake_case_		:			str											=	self.pos_y - self.goal_y
							if HEURISTIC == 1:
								return abs(_A	) + abs(_A	)
							else:
								return sqrt(dy**2 + dx**2	)






						def __lt__(      self      :      str		,   _A      :      Node	)							->    bool:







							"""simple docstring"""


							return self.f_cost < other.f_cost
class SCREAMING_SNAKE_CASE_						:






						def __init__(      self      :      Tuple		,   _A      :      TPosition		,   _A      :      TPosition	)							->    Union[str, Any]:







							"""simple docstring"""


							snake_case_		:			int											=	Node(start[1]		,   start[0]		,   goal[1]		,   goal[0]		,   0		,   _A	)
							snake_case_		:			Tuple											=	Node(goal[1]		,   goal[0]		,   goal[1]		,   goal[0]		,   99999		,   _A	)

							snake_case_		:			Any											=	[self.start]
							snake_case_		:			list[Node]											=	[]

							snake_case_		:			Tuple											=	False






						def UpperCAmelCase_				(      self      :      str	)							->    list[TPosition]:







							"""simple docstring"""


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

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

								self.closed_nodes.append(_A	)
								snake_case_		:			Union[str, 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
										snake_case_		:			str											=	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	)

							return [self.start.pos]






						def UpperCAmelCase_				(      self      :      int		,   _A      :      Node	)							->    list[Node]:







							"""simple docstring"""


							snake_case_		:			List[Any]											=	[]
							for action in delta:
								snake_case_		:			Tuple											=	parent.pos_x + action[1]
								snake_case_		:			Optional[int]											=	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 UpperCAmelCase_				(      self      :      Union[str, Any]		,   _A      :      Node | None	)							->    list[TPosition]:







							"""simple docstring"""


							snake_case_		:			str											=	node
							snake_case_		:			Optional[int]											=	[]
							while current_node is not None:
								path.append((current_node.pos_y, current_node.pos_x)	)
								snake_case_		:			str											=	current_node.parent
							path.reverse()
							return path
class SCREAMING_SNAKE_CASE_						:






						def __init__(      self      :      str		,   _A      :      TPosition		,   _A      :      TPosition	)							->    None:







							"""simple docstring"""


							snake_case_		:			List[Any]											=	AStar(_A		,   _A	)
							snake_case_		:			Dict											=	AStar(_A		,   _A	)
							snake_case_		:			int											=	False






						def UpperCAmelCase_				(      self      :      List[str]	)							->    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()
								snake_case_		:			str											=	self.fwd_astar.open_nodes.pop(0	)
								snake_case_		:			int											=	self.bwd_astar.open_nodes.pop(0	)

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

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

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

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

								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(_A	)
										else:
											# retrieve the best current path
											snake_case_		:			List[Any]											=	astar.open_nodes.pop(
											    astar.open_nodes.index(_A	)	)

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

							return [self.fwd_astar.start.pos]






						def UpperCAmelCase_				(      self      :      Optional[int]		,   _A      :      Node		,   _A      :      Node	)							->    list[TPosition]:







							"""simple docstring"""


							snake_case_		:			Union[str, Any]											=	self.fwd_astar.retrace_path(_A	)
							snake_case_		:			str											=	self.bwd_astar.retrace_path(_A	)
							bwd_path.pop()
							bwd_path.reverse()
							snake_case_		:			Dict											=	fwd_path + bwd_path
							return path


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

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

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








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


_SCREAMING_SNAKE_CASE      	=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE      	=		{
    """SCUT-DLVCLab/lilt-roberta-en-base""": (
        """https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"""
    ),
}
class SCREAMING_SNAKE_CASE_						(					snake_case_					):
						__magic_name__:			str       =       "lilt"






						def __init__(      self      :      Any		,   _A      :      Dict=30522		,   _A      :      List[Any]=768		,   _A      :      str=12		,   _A      :      int=12		,   _A      :      Optional[int]=3072		,   _A      :      Optional[Any]="gelu"		,   _A      :      Dict=0.1		,   _A      :      Tuple=0.1		,   _A      :      str=512		,   _A      :      Union[str, Any]=2		,   _A      :      Union[str, Any]=0.0_2		,   _A      :      Optional[Any]=1E-12		,   _A      :      Optional[int]=0		,   _A      :      Dict="absolute"		,   _A      :      Any=None		,   _A      :      Optional[Any]=4		,   _A      :      Any=1024		,   **_A      :      Union[str, Any]		,   )							->    List[str]:







							"""simple docstring"""


							super().__init__(pad_token_id=_A		,   **_A	)

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

