






import numpy as np

class     _SCREAMING_SNAKE_CASE       :





	def __init__(		self				:					int	):
		UpperCamelCase     :int          =	(0, 0)
		UpperCamelCase     :List[str]          =	None
		UpperCamelCase     :Union[str, Any]          =	0
		UpperCamelCase     :Optional[Any]          =	0
		UpperCamelCase     :Optional[Any]          =	0





	def __eq__(		self				:					Union[str, Any] ,  __lowerCamelCase				:					int	):
		return self.position == cell.position





	def 						_A (		self				:					Optional[Any]	):
		print(self.position	)

class     _SCREAMING_SNAKE_CASE       :





	def __init__(		self				:					List[Any] ,  __lowerCamelCase				:					Any=(5, 5)	):
		UpperCamelCase     :Tuple          =	np.zeros(__lowerCamelCase	)
		UpperCamelCase     :str          =	world_size[0]
		UpperCamelCase     :List[str]          =	world_size[1]





	def 						_A (		self				:					List[Any]	):
		print(self.w	)





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

def    SCREAMING_SNAKE_CASE_							(							__magic_name__					:  Any	,			__magic_name__					:  str	,			__magic_name__					:  Optional[int]					)		->			List[Any]:






	"""simple docstring"""



	UpperCamelCase     :List[str]          =	[]
	UpperCamelCase     :List[str]          =	[]
	_open.append(__magic_name__					)

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

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


if __name__ == "__main__":
	UpperCAmelCase_ :						List[Any]      =      Gridworld()
	# Start position and goal
	UpperCAmelCase_ :						List[str]      =      Cell()
	UpperCAmelCase_ :						str      =      (0, 0)
	UpperCAmelCase_ :						Tuple      =      Cell()
	UpperCAmelCase_ :						int      =      (4, 4)
	print(F'''path from {start.position} to {goal.position}''')
	UpperCAmelCase_ :						Tuple      =      astar(world, start, goal)
	#   Just for visual reasons.
	for i in s:
		UpperCAmelCase_ :						Union[str, Any]      =      1
	print(world.w)








from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream

class     _SCREAMING_SNAKE_CASE       (			_a      ):





	def __init__(		self				:					List[Any] ,  __lowerCamelCase				:					Callable ,  __lowerCamelCase				:					Optional[Features] = None ,  __lowerCamelCase				:					str = None ,  __lowerCamelCase				:					bool = False ,  __lowerCamelCase				:					bool = False ,  __lowerCamelCase				:					Optional[dict] = None ,  __lowerCamelCase				:					Optional[int] = None ,  **__lowerCamelCase				:					List[Any] ,  ):
		super().__init__(
		    features=__lowerCamelCase ,  cache_dir=__lowerCamelCase ,  keep_in_memory=__lowerCamelCase ,  streaming=__lowerCamelCase ,  num_proc=__lowerCamelCase ,  **__lowerCamelCase ,  )
		UpperCamelCase     :Union[str, Any]          =	Generator(
		    cache_dir=__lowerCamelCase ,  features=__lowerCamelCase ,  generator=__lowerCamelCase ,  gen_kwargs=__lowerCamelCase ,  **__lowerCamelCase ,  )





	def 						_A (		self				:					List[str]	):
		# Build iterable dataset
		if self.streaming:
			UpperCamelCase     :Any          =	self.builder.as_streaming_dataset(split="""train"""	)
		# Build regular (map-style) dataset
		else:
			UpperCamelCase     :Tuple          =	None
			UpperCamelCase     :Dict          =	None
			UpperCamelCase     :Dict          =	None
			UpperCamelCase     :List[str]          =	None

			self.builder.download_and_prepare(
			    download_config=__lowerCamelCase ,  download_mode=__lowerCamelCase ,  verification_mode=__lowerCamelCase ,  base_path=__lowerCamelCase ,  num_proc=self.num_proc ,  )
			UpperCamelCase     :Tuple          =	self.builder.as_dataset(
			    split="""train""" ,  verification_mode=__lowerCamelCase ,  in_memory=self.keep_in_memory	)
		return dataset
