
"""simple docstring"""




from __future__ import annotations

import time
from math import sqrt

# 1 for manhattan, 0 for euclidean
lowercase__		:Any			  =   0

lowercase__		:List[str]			  =   [
    [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],
]

lowercase__		:Optional[Any]			  =   [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right

lowercase__		:List[Any]			  =   tuple[int, int]







class     lowercase		:




							def __init__(    self       ,A__       ,A__       ,A__       ,A__       ,A__       ,A__       ,):
												lowercase						     =						pos_x
												lowercase						     =						pos_y
												lowercase						     =						(pos_y, pos_x)
												lowercase						     =						goal_x
												lowercase						     =						goal_y
												lowercase						     =						g_cost
												lowercase						     =						parent
												lowercase						     =						self.calculate_heuristic()
												lowercase						     =						self.g_cost + self.h_cost




							def 			A__				(    self):
												lowercase						     =						self.pos_x - self.goal_x
												lowercase						     =						self.pos_y - self.goal_y
												if HEURISTIC == 1:
																	return abs(a_) + abs(a_)
												else:
																	return sqrt(dy**2 + dx**2)





							def __lt__(    self       ,A__):
												return self.f_cost < other.f_cost







class     lowercase		:




							def __init__(    self       ,A__       ,A__):
												lowercase						     =						Node(start[1]       ,start[0]       ,goal[1]       ,goal[0]       ,0       ,a_)
												lowercase						     =						Node(goal[1]       ,goal[0]       ,goal[1]       ,goal[0]       ,9_9_9_9_9       ,a_)

												lowercase						     =						[self.start]
												lowercase						     =						[]

												lowercase						     =						False




							def 			A__				(    self):

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

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

																	self.closed_nodes.append(a_)
																	lowercase						     =						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
																											lowercase						     =						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       ,A__):
												lowercase						     =						[]
												for action in delta:
																	lowercase						     =						parent.pos_x + action[1]
																	lowercase						     =						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       ,A__):
												lowercase						     =						node
												lowercase						     =						[]
												while current_node is not None:
																	path.append((current_node.pos_y, current_node.pos_x))
																	lowercase						     =						current_node.parent
												path.reverse()
												return path







class     lowercase		:




							def __init__(    self       ,A__       ,A__):
												lowercase						     =						AStar(a_       ,a_)
												lowercase						     =						AStar(a_       ,a_)
												lowercase						     =						False




							def 			A__				(    self):

												while self.fwd_astar.open_nodes or self.bwd_astar.open_nodes:
																	self.fwd_astar.open_nodes.sort()
																	self.bwd_astar.open_nodes.sort()
																	lowercase						     =						self.fwd_astar.open_nodes.pop(0)
																	lowercase						     =						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_)

																	lowercase						     =						current_bwd_node
																	lowercase						     =						current_fwd_node

																	lowercase						     =						{
																	    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
																																lowercase						     =						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       ,A__       ,A__):
												lowercase						     =						self.fwd_astar.retrace_path(a_)
												lowercase						     =						self.bwd_astar.retrace_path(a_)
												bwd_path.pop()
												bwd_path.reverse()
												lowercase						     =						fwd_path + bwd_path
												return path


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

							lowercase__		:List[str]			  =   time.time()
							lowercase__		:str			  =   AStar(init, goal)
							lowercase__		:Tuple			  =   a_star.search()
							lowercase__		:int			  =   time.time() - start_time
							print(F'AStar execution time = {end_time:f} seconds')

							lowercase__		:Dict			  =   time.time()
							lowercase__		:List[str]			  =   BidirectionalAStar(init, goal)
							lowercase__		:Tuple			  =   time.time() - bd_start_time
							print(F'BidirectionalAStar execution time = {bd_end_time:f} seconds')






import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict







@dataclass
class     lowercase		( SCREAMING_SNAKE_CASE__		):
							lowercase_	:	int	 =ComputeEnvironment.AMAZON_SAGEMAKER
							lowercase_	:	Optional[int]	 =True
							lowercase_	:	Any	 ='''ml.p3.2xlarge'''
							lowercase_	:	Any	 ='''accelerate_sagemaker_execution_role'''
							lowercase_	:	Union[str, Any]	 ='''hf-sm'''
							lowercase_	:	Any	 ='''us-east-1'''
							lowercase_	:	List[str]	 =1
							lowercase_	:	Any	 ='''accelerate-sagemaker-1'''
							lowercase_	:	Union[str, Any]	 ='''1.6'''
							lowercase_	:	Any	 ='''4.4'''
							lowercase_	:	Any	 ='''train.py'''
							lowercase_	:	int	 =[
							    '''--model_name_or_path''',
							    '''bert''',
							    '''--do_train''',
							    '''False''',
							    '''--epochs''',
							    '''3''',
							    '''--learning_rate''',
							    '''5e-5''',
							    '''--max_steps''',
							    '''50.5''',
							]
							lowercase_	:	List[Any]	 =[
							    '''--model_name_or_path''',
							    '''bert''',
							    '''--do_train''',
							    '''--do_test''',
							    '''False''',
							    '''--do_predict''',
							    '''--epochs''',
							    '''3''',
							    '''--learning_rate''',
							    '''5e-5''',
							    '''--max_steps''',
							    '''50.5''',
							]







class     lowercase		( unittest.TestCase		):




							def 			A__				(    self):
												# If no defaults are changed, `to_kwargs` returns an empty dict.
												lowercase						     =						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args)
												assert isinstance(converted_args['''model_name_or_path''']       ,A__)
												assert isinstance(converted_args['''do_train''']       ,A__)
												assert isinstance(converted_args['''epochs''']       ,A__)
												assert isinstance(converted_args['''learning_rate''']       ,A__)
												assert isinstance(converted_args['''max_steps''']       ,A__)

												with pytest.raises(A__):
																	_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args)




