


"""simple docstring"""


from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
__lowerCamelCase      :str	    =		0

__lowerCamelCase      :Optional[int]	    =		[
    [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      :Tuple	    =		[[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

__lowerCamelCase      :Tuple	    =		tuple[int, int]


class 			A__	:


					"""simple docstring"""

					def __init__(	self:						int     ,		__a:						int     ,		__a:						int     ,		__a:						int     ,		__a:						int     ,		__a:						int     ,		__a:						Node | None     ,		)->    None:
											lowerCamelCase					:					Optional[int]        =	pos_x
											lowerCamelCase					:					List[Any]        =	pos_y
											lowerCamelCase					:					Union[str, Any]        =	(pos_y, pos_x)
											lowerCamelCase					:					List[Any]        =	goal_x
											lowerCamelCase					:					Optional[Any]        =	goal_y
											lowerCamelCase					:					str        =	g_cost
											lowerCamelCase					:					str        =	parent
											lowerCamelCase					:					Optional[Any]        =	self.calculate_heuristic()
											lowerCamelCase					:					List[str]        =	self.g_cost + self.h_cost

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







					def __lt__(	self:						List[Any]     ,		__a:						Node	)->    bool:
											return self.f_cost < other.f_cost


class 			A__	:


					"""simple docstring"""

					def __init__(	self:						Any     ,		__a:						TPosition     ,		__a:						TPosition	)->    Optional[Any]:
											lowerCamelCase					:					List[Any]        =	Node(start[1]     ,		start[0]     ,		goal[1]     ,		goal[0]     ,		0     ,		__a	)
											lowerCamelCase					:					Tuple        =	Node(goal[1]     ,		goal[0]     ,		goal[1]     ,		goal[0]     ,		99_999     ,		__a	)

											lowerCamelCase					:					Optional[Any]        =	[self.start]
											lowerCamelCase					:					list[Node]        =	[]

											lowerCamelCase					:					Tuple        =	False

					def 		a__						(	self:						int	)->    list[TPosition]:
											while self.open_nodes:
																	# Open Nodes are sorted using __lt__
																	self.open_nodes.sort()
																	lowerCamelCase					:					Tuple        =	self.open_nodes.pop(0	)

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

																	self.closed_nodes.append(__a	)
																	lowerCamelCase					:					Dict        =	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
																													lowerCamelCase					:					Any        =	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 		a__						(	self:						Union[str, Any]     ,		__a:						Node	)->    list[Node]:
											lowerCamelCase					:					str        =	[]
											for action in delta:
																	lowerCamelCase					:					Union[str, Any]        =	parent.pos_x + action[1]
																	lowerCamelCase					:					Optional[Any]        =	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 		a__						(	self:						Union[str, Any]     ,		__a:						Node | None	)->    list[TPosition]:
											lowerCamelCase					:					Dict        =	node
											lowerCamelCase					:					Tuple        =	[]
											while current_node is not None:
																	path.append((current_node.pos_y, current_node.pos_x)	)
																	lowerCamelCase					:					str        =	current_node.parent
											path.reverse()
											return path


class 			A__	:


					"""simple docstring"""

					def __init__(	self:						Union[str, Any]     ,		__a:						TPosition     ,		__a:						TPosition	)->    None:
											lowerCamelCase					:					Dict        =	AStar(__a     ,		__a	)
											lowerCamelCase					:					str        =	AStar(__a     ,		__a	)
											lowerCamelCase					:					int        =	False

					def 		a__						(	self:						str	)->    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					:					List[Any]        =	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	)

																	lowerCamelCase					:					int        =	current_bwd_node
																	lowerCamelCase					:					List[Any]        =	current_fwd_node

																	lowerCamelCase					:					Optional[int]        =	{
																	    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
																																			lowerCamelCase					:					str        =	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 		a__						(	self:						List[str]     ,		__a:						Node     ,		__a:						Node	)->    list[TPosition]:
											lowerCamelCase					:					str        =	self.fwd_astar.retrace_path(__a	)
											lowerCamelCase					:					Any        =	self.bwd_astar.retrace_path(__a	)
											bwd_path.pop()
											bwd_path.reverse()
											lowerCamelCase					:					Any        =	fwd_path + bwd_path
											return path


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

				__lowerCamelCase      :Optional[int]	    =		time.time()
				__lowerCamelCase      :Optional[int]	    =		AStar(init, goal)
				__lowerCamelCase      :int	    =		a_star.search()
				__lowerCamelCase      :Optional[Any]	    =		time.time() - start_time
				print(f"""AStar execution time = {end_time:f} seconds""")

				__lowerCamelCase      :List[Any]	    =		time.time()
				__lowerCamelCase      :List[str]	    =		BidirectionalAStar(init, goal)
				__lowerCamelCase      :List[str]	    =		time.time() - bd_start_time
				print(f"""BidirectionalAStar execution time = {bd_end_time:f} seconds""")








"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


__lowerCamelCase      :List[str]	    =		{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase      :Optional[int]	    =		['OwlViTFeatureExtractor']
    __lowerCamelCase      :List[str]	    =		['OwlViTImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase      :Optional[Any]	    =		[
        'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'OwlViTModel',
        'OwlViTPreTrainedModel',
        'OwlViTTextModel',
        'OwlViTVisionModel',
        'OwlViTForObjectDetection',
    ]

if TYPE_CHECKING:
    from .configuration_owlvit import (
        OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        OwlViTConfig,
        OwlViTOnnxConfig,
        OwlViTTextConfig,
        OwlViTVisionConfig,
    )
    from .processing_owlvit import OwlViTProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_owlvit import OwlViTFeatureExtractor
        from .image_processing_owlvit import OwlViTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_owlvit import (
            OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            OwlViTForObjectDetection,
            OwlViTModel,
            OwlViTPreTrainedModel,
            OwlViTTextModel,
            OwlViTVisionModel,
        )

else:
    import sys

    __lowerCamelCase      :Dict	    =		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




