

from __future__ import annotations

import time

a_      =     list[tuple[int, int]]

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






class _UpperCamelCase				:
			'''simple docstring'''







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

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[Any]					  =							pos_x
				SCREAMING_SNAKE_CASE :   Dict					  =							pos_y
				SCREAMING_SNAKE_CASE :   int					  =							(pos_y, pos_x)
				SCREAMING_SNAKE_CASE :   Any					  =							goal_x
				SCREAMING_SNAKE_CASE :   Dict					  =							goal_y
				SCREAMING_SNAKE_CASE :   str					  =							parent






class _UpperCamelCase				:
			'''simple docstring'''







			def __init__(      self				:			Dict   ,   a				:			tuple[int, int]   ,   a				:			tuple[int, int]						)				->							Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   int					  =							Node(start[1]   ,   start[0]   ,   goal[1]   ,   goal[0]   ,   a						)
				SCREAMING_SNAKE_CASE :   Tuple					  =							Node(goal[1]   ,   goal[0]   ,   goal[1]   ,   goal[0]   ,   a						)

				SCREAMING_SNAKE_CASE :   str					  =							[self.start]
				SCREAMING_SNAKE_CASE :   Any					  =							False
			def 				__UpperCamelCase			(      self				:			str						)				->							Path | None:

				"""simple docstring"""

				while self.node_queue:
					SCREAMING_SNAKE_CASE :   List[str]					  =							self.node_queue.pop(0						)

					if current_node.pos == self.target.pos:
						SCREAMING_SNAKE_CASE :   Tuple					  =							True
						return self.retrace_path(a						)

					SCREAMING_SNAKE_CASE :   str					  =							self.get_successors(a						)

					for node in successors:
						self.node_queue.append(a						)

				if not self.reached:
					return [self.start.pos]
				return None
			def 				__UpperCamelCase			(      self				:			Dict   ,   a				:			Node						)				->							list[Node]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Any					  =							[]
				for action in delta:
					SCREAMING_SNAKE_CASE :   int					  =							parent.pos_x + action[1]
					SCREAMING_SNAKE_CASE :   Dict					  =							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   ,   a						)						)
				return successors






			def 				__UpperCamelCase			(      self				:			Union[str, Any]   ,   a				:			Node | None						)				->							Path:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Tuple					  =							node
				SCREAMING_SNAKE_CASE :   List[Any]					  =							[]
				while current_node is not None:
					path.append((current_node.pos_y, current_node.pos_x)						)
					SCREAMING_SNAKE_CASE :   Dict					  =							current_node.parent
				path.reverse()
				return path






class _UpperCamelCase				:
			'''simple docstring'''







			def __init__(      self				:			str   ,   a				:			Optional[int]   ,   a				:			Optional[Any]						)				->							Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							BreadthFirstSearch(a   ,   a						)
				SCREAMING_SNAKE_CASE :   Any					  =							BreadthFirstSearch(a   ,   a						)
				SCREAMING_SNAKE_CASE :   Dict					  =							False
			def 				__UpperCamelCase			(      self				:			List[Any]						)				->							Path | None:

				"""simple docstring"""

				while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.fwd_bfs.node_queue.pop(0						)
					SCREAMING_SNAKE_CASE :   Any					  =							self.bwd_bfs.node_queue.pop(0						)

					if current_bwd_node.pos == current_fwd_node.pos:
						SCREAMING_SNAKE_CASE :   int					  =							True
						return self.retrace_bidirectional_path(
						    a   ,   a						)

					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							current_bwd_node
					SCREAMING_SNAKE_CASE :   str					  =							current_fwd_node

					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							{
					    self.fwd_bfs: self.fwd_bfs.get_successors(a						),
					    self.bwd_bfs: self.bwd_bfs.get_successors(a						),
					}

					for bfs in [self.fwd_bfs, self.bwd_bfs]:
						for node in successors[bfs]:
							bfs.node_queue.append(a						)

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






			def 				__UpperCamelCase			(      self				:			int   ,   a				:			Node   ,   a				:			Node						)				->							Path:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Tuple					  =							self.fwd_bfs.retrace_path(a						)
				SCREAMING_SNAKE_CASE :   str					  =							self.bwd_bfs.retrace_path(a						)
				bwd_path.pop()
				bwd_path.reverse()
				SCREAMING_SNAKE_CASE :   Any					  =							fwd_path + bwd_path
				return path


if __name__ == "__main__":
			# all coordinates are given in format [y,x]
			import doctest

			doctest.testmod()
			a_      =     (0, 0)
			a_      =     (len(grid) - 1, len(grid[0]) - 1)
			for elem in grid:
						print(elem)

			a_      =     time.time()
			a_      =     BreadthFirstSearch(init, goal)
			a_      =     bfs.search()
			a_      =     time.time() - start_bfs_time

			print('Unidirectional BFS computation time : ', bfs_time)

			a_      =     time.time()
			a_      =     BidirectionalBreadthFirstSearch(init, goal)
			a_      =     bd_bfs.search()
			a_      =     time.time() - start_bd_bfs_time

			print('Bidirectional BFS computation time : ', bd_bfs_time)


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


a_      =     {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig']}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     ['PLBartTokenizer']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     [
			    'PLBART_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'PLBartForCausalLM',
			    'PLBartForConditionalGeneration',
			    'PLBartForSequenceClassification',
			    'PLBartModel',
			    'PLBartPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_plbart import PLBartTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_plbart import (
						    PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
						    PLBartForCausalLM,
						    PLBartForConditionalGeneration,
						    PLBartForSequenceClassification,
						    PLBartModel,
						    PLBartPreTrainedModel,
						)


else:
			import sys

			a_      =     _LazyModule(__name__, globals()['__file__'], _import_structure)