






"""simple docstring"""







from argparse import ArgumentParser

from . import BaseTransformersCLICommand


def      UpperCamelCase       ( _A )     ->       Any:
				return DownloadCommand(args.model  ,				args.cache_dir  ,				args.force  ,				args.trust_remote_code )


class      UpperCamelCase		(__snake_case     ):






						@staticmethod
						def      __snake_case      (		__magic_name__  :ArgumentParser				)      ->List[Any]:
										lowercase    :      Tuple       = parser.add_parser("""download"""				)
										download_parser.add_argument(
										    """--cache-dir"""			, type=__magic_name__			, default=__magic_name__			, help="""Path to location to store the models"""				)
										download_parser.add_argument(
										    """--force"""			, action="""store_true"""			, help="""Force the model to be download even if already in cache-dir"""				)
										download_parser.add_argument(
										    """--trust-remote-code"""			, action="""store_true"""			, help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""			, )
										download_parser.add_argument("""model"""			, type=__magic_name__			, help="""Name of the model to download"""				)
										download_parser.set_defaults(func=__magic_name__				)






						def __init__(		self  :Optional[Any]			, __magic_name__  :str			, __magic_name__  :str			, __magic_name__  :bool			, __magic_name__  :bool				)      ->List[Any]:
										lowercase    :      Optional[int]       = model
										lowercase    :      int       = cache
										lowercase    :      int       = force
										lowercase    :      Any       = trust_remote_code






						def      __snake_case      (		self  :int				)      ->Dict:
										from ..models.auto import AutoModel, AutoTokenizer

										AutoModel.from_pretrained(
										    self._model			, cache_dir=self._cache			, force_download=self._force			, trust_remote_code=self._trust_remote_code				)
										AutoTokenizer.from_pretrained(
										    self._model			, cache_dir=self._cache			, force_download=self._force			, trust_remote_code=self._trust_remote_code				)








"""simple docstring"""







import numpy as np


class      UpperCamelCase		:






						def __init__(		self  :List[Any]				)      ->Optional[Any]:
										lowercase    :      Dict       = (0, 0)
										lowercase    :      str       = None
										lowercase    :      Any       = 0
										lowercase    :      List[Any]       = 0
										lowercase    :      Union[str, Any]       = 0






						def __eq__(		self  :List[Any]			, __magic_name__  :Optional[Any]				)      ->Tuple:
										return self.position == cell.position






						def      __snake_case      (		self  :Any				)      ->List[Any]:
										print(self.position				)


class      UpperCamelCase		:






						def __init__(		self  :Any			, __magic_name__  :int=(5, 5)				)      ->Dict:
										lowercase    :      Tuple       = np.zeros(__magic_name__				)
										lowercase    :      List[str]       = world_size[0]
										lowercase    :      str       = world_size[1]






						def      __snake_case      (		self  :str				)      ->int:
										print(self.w				)






						def      __snake_case      (		self  :Any			, __magic_name__  :Any				)      ->Optional[int]:
										lowercase    :      Optional[Any]       = [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										lowercase    :      List[str]       = cell.position[0]
										lowercase    :      List[str]       = cell.position[1]
										lowercase    :      Optional[int]       = []
										for n in neughbour_cord:
														lowercase    :      List[Any]       = current_x + n[0]
														lowercase    :      List[Any]       = current_y + n[1]
														if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																		lowercase    :      Tuple       = Cell()
																		lowercase    :      Union[str, Any]       = (x, y)
																		lowercase    :      Dict       = cell
																		neighbours.append(__magic_name__				)
										return neighbours


def      UpperCamelCase       ( _A  ,				_A  ,				_A )     ->       Tuple:
				lowercase    :      Dict       = []
				lowercase    :      List[str]       = []
				_open.append(_A )

				while _open:
								lowercase    :      List[str]       = np.argmin([n.f for n in _open] )
								lowercase    :      int       = _open[min_f]
								_closed.append(_open.pop(_A ) )
								if current == goal:
												break
								for n in world.get_neigbours(_A ):
												for c in _closed:
																if c == n:
																				continue
												lowercase    :      List[Any]       = current.g + 1
												lowercase      ,      lowercase    :      Any       = n.position
												lowercase      ,      lowercase    :      List[str]       = goal.position
												lowercase    :      Any       = (ya - ya) ** 2 + (xa - xa) ** 2
												lowercase    :      Union[str, Any]       = n.h + n.g

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(_A )
				lowercase    :      List[str]       = []
				while current.parent is not None:
								path.append(current.position )
								lowercase    :      int       = current.parent
				path.append(current.position )
				return path[::-1]


if __name__ == "__main__":
				_lowerCAmelCase            =	Gridworld()
				# Start position and goal
				_lowerCAmelCase            =	Cell()
				_lowerCAmelCase            =	(0, 0)
				_lowerCAmelCase            =	Cell()
				_lowerCAmelCase            =	(4, 4)
				print(F'path from {start.position} to {goal.position}')
				_lowerCAmelCase            =	astar(world, start, goal)
				#   Just for visual reasons.
				for i in s:
								_lowerCAmelCase            =	1
				print(world.w)
