


import numpy as np


class     lowercase__  :






  def __init__(					self      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     (0, 0)
         UpperCAmelCase__										=     None
         UpperCAmelCase__										=     0
         UpperCAmelCase__										=     0
         UpperCAmelCase__										=     0






  def __eq__(					self      :					Dict		,						_lowercase      :					Dict ):




         """simple docstring"""







         return self.position == cell.position






  def 			_UpperCAmelCase  (					self      :					str ):




         """simple docstring"""







         print(self.position )




class     lowercase__  :






  def __init__(					self      :					int		,						_lowercase      :					Optional[int]=(5, 5) ):




         """simple docstring"""







         UpperCAmelCase__										=     np.zeros(_lowercase )
         UpperCAmelCase__										=     world_size[0]
         UpperCAmelCase__										=     world_size[1]






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         print(self.w )






  def 			_UpperCAmelCase  (					self      :					str		,						_lowercase      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     [
             (-1, -1),
             (-1, 0),
             (-1, 1),
             (0, -1),
             (0, 1),
             (1, -1),
             (1, 0),
             (1, 1),
         ]
         UpperCAmelCase__										=     cell.position[0]
         UpperCAmelCase__										=     cell.position[1]
         UpperCAmelCase__										=     []
         for n in neughbour_cord:
                UpperCAmelCase__										=     current_x + n[0]
                UpperCAmelCase__										=     current_y + n[1]
                if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
                       UpperCAmelCase__										=     Cell()
                       UpperCAmelCase__										=     (x, y)
                       UpperCAmelCase__										=     cell
                       neighbours.append(_lowercase )
         return neighbours





def __UpperCAmelCase       (		__A ,						__A ,						__A			)						->					Optional[Any]:



       '''simple docstring'''





       UpperCAmelCase__										=     []
       UpperCAmelCase__										=     []
       _open.append(__A			)

       while _open:
              UpperCAmelCase__										=     np.argmin([n.f for n in _open]			)
              UpperCAmelCase__										=     _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
                     UpperCAmelCase__										=     current.g + 1
                     UpperCAmelCase__						,			UpperCAmelCase__										=     n.position
                     UpperCAmelCase__						,			UpperCAmelCase__										=     goal.position
                     UpperCAmelCase__										=     (ya - ya) ** 2 + (xa - xa) ** 2
                     UpperCAmelCase__										=     n.h + n.g

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


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









import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


A      = logging.get_logger(__name__)


class     lowercase__  (					__SCREAMING_SNAKE_CASE		):






  def __init__(					self      :					Union[str, Any]		,						*_lowercase      :					Any		,						**_lowercase      :					Optional[int] ):




         """simple docstring"""







         warnings.warn(
             "The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use DPTImageProcessor instead."		,						_lowercase		,						)
         super().__init__(*_lowercase		,						**_lowercase )





