


'''simple docstring'''
from __future__ import annotations

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


def       a				(      __a			, __a			, __a			, __a			, __a			, )  ->     tuple[list[list[int]], list[list[int]]]:



					'''simple docstring'''






					UpperCamelCase__       :Dict							 =			[
					    [0 for col in range(len(grid[0]       )       )] for row in range(len(_lowercase       )       )
					]  # the reference grid
					UpperCamelCase__       :Any							 =			1
					UpperCamelCase__       :List[Any]							 =			[
					    [0 for col in range(len(grid[0]       )       )] for row in range(len(_lowercase       )       )
					]  # the action grid

					UpperCamelCase__       :str							 =			init[0]
					UpperCamelCase__       :Any							 =			init[1]
					UpperCamelCase__       :List[str]							 =			0
					UpperCamelCase__       :int							 =			g + heuristic[x][y]  # cost from starting cell to destination cell
					UpperCamelCase__       :Dict							 =			[[f, g, x, y]]

					UpperCamelCase__       :List[Any]							 =			False  # flag that is set when search is complete
					UpperCamelCase__       :Optional[int]							 =			False  # flag set if we can't find expand

					while not found and not resign:
										if len(_lowercase       ) == 0:
															raise ValueError('''Algorithm is unable to find solution'''       )
										else:  # to choose the least costliest action so as to move closer to the goal
															cell.sort()
															cell.reverse()
															UpperCamelCase__       :Optional[int]							 =			cell.pop()
															UpperCamelCase__       :Dict							 =			next_cell[2]
															UpperCamelCase__       :int							 =			next_cell[3]
															UpperCamelCase__       :Union[str, Any]							 =			next_cell[1]

															if x == goal[0] and y == goal[1]:
																				UpperCamelCase__       :List[Any]							 =			True
															else:
																				for i in range(len(_lowercase       )       ):  # to try out different valid actions
																									UpperCamelCase__       :Optional[Any]							 =			x + DIRECTIONS[i][0]
																									UpperCamelCase__       :List[Any]							 =			y + DIRECTIONS[i][1]
																									if xa >= 0 and xa < len(_lowercase       ) and ya >= 0 and ya < len(grid[0]       ):
																														if closed[xa][ya] == 0 and grid[xa][ya] == 0:
																																			UpperCamelCase__       :Dict							 =			g + cost
																																			UpperCamelCase__       :List[Any]							 =			ga + heuristic[xa][ya]
																																			cell.append([fa, ga, xa, ya]       )
																																			UpperCamelCase__       :Any							 =			1
																																			UpperCamelCase__       :Union[str, Any]							 =			i
					UpperCamelCase__       :Tuple							 =			[]
					UpperCamelCase__       :Tuple							 =			goal[0]
					UpperCamelCase__       :Optional[Any]							 =			goal[1]
					invpath.append([x, y]       )  # we get the reverse path from here
					while x != init[0] or y != init[1]:
										UpperCamelCase__       :Dict							 =			x - DIRECTIONS[action[x][y]][0]
										UpperCamelCase__       :Union[str, Any]							 =			y - DIRECTIONS[action[x][y]][1]
										UpperCamelCase__       :Optional[int]							 =			xa
										UpperCamelCase__       :Tuple							 =			ya
										invpath.append([x, y]       )

					UpperCamelCase__       :Optional[int]							 =			[]
					for i in range(len(_lowercase       )       ):
										path.append(invpath[len(_lowercase       ) - 1 - i]       )
					return path, action


if __name__ == "__main__":
		_UpperCAmelCase											=					[
		    [0, 1, 0, 0, 0, 0],
		    [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
		    [0, 1, 0, 0, 0, 0],
		    [0, 1, 0, 0, 1, 0],
		    [0, 0, 0, 0, 1, 0],
		]

		_UpperCAmelCase											=					[0, 0]
		# all coordinates are given in format [y,x]
		_UpperCAmelCase											=					[len(grid) - 1, len(grid[0]) - 1]
		_UpperCAmelCase											=					1

		# the cost map which pushes the path closer to the goal
		_UpperCAmelCase											=					[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
		for i in range(len(grid)):
				for j in range(len(grid[0])):
						_UpperCAmelCase											=					abs(i - goal[0]) + abs(j - goal[1])
						if grid[i][j] == 1:
								# added extra penalty in the heuristic map
								_UpperCAmelCase											=					99

		_UpperCAmelCase											=					search(grid, init, goal, cost, heuristic)

		print('''ACTION MAP''')
		for i in range(len(action)):
				print(action[i])

		for i in range(len(path)):
				print(path[i])



'''simple docstring'''
from argparse import ArgumentParser

from .env import EnvironmentCommand


def       a				(      )  ->     Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__       :Union[str, Any]							 =			ArgumentParser('''Diffusers CLI tool'''			, usage='''diffusers-cli <command> [<args>]'''       )
					UpperCamelCase__       :Union[str, Any]							 =			parser.add_subparsers(help='''diffusers-cli command helpers'''       )

					# Register commands
					EnvironmentCommand.register_subcommand(__a       )

					# Let's go
					UpperCamelCase__       :Optional[int]							 =			parser.parse_args()

					if not hasattr(__a			, '''func'''       ):
										parser.print_help()
										exit(1       )

					# Run
					UpperCamelCase__       :Optional[int]							 =			args.func(__a       )
					service.run()


if __name__ == "__main__":
		main()