



"""simple docstring"""





import numpy as np
class    lowercase__     :



       def __init__(							self    :						Tuple					)				->		List[str]:


             '''simple docstring'''




             UpperCAmelCase_    				=							(0, 0)
             UpperCAmelCase_    				=							None
             UpperCAmelCase_    				=							0
             UpperCAmelCase_    				=							0
             UpperCAmelCase_    				=							0



       def __eq__(							self    :						List[str]	,       _UpperCAmelCase    :						Any					)				->		List[Any]:


             '''simple docstring'''




             return self.position == cell.position







       def   lowercase__       (							self    :						List[str]					)				->		List[Any]:


             '''simple docstring'''




             print(self.position					)



class    lowercase__     :



       def __init__(							self    :						Tuple	,       _UpperCAmelCase    :						Tuple=(5, 5)					)				->		int:


             '''simple docstring'''




             UpperCAmelCase_    				=							np.zeros(lowercase__					)
             UpperCAmelCase_    				=							world_size[0]
             UpperCAmelCase_    				=							world_size[1]



       def   lowercase__       (							self    :						List[str]					)				->		List[Any]:


             '''simple docstring'''




             print(self.w					)







       def   lowercase__       (							self    :						Dict	,       _UpperCAmelCase    :						Tuple					)				->		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      a__			(   lowerCAmelCase__			,    lowerCAmelCase__			,    lowerCAmelCase__   ):
      UpperCAmelCase_    				=							[]
      UpperCAmelCase_    				=							[]
      _open.append(SCREAMING_SNAKE_CASE_   )

      while _open:
            UpperCAmelCase_    				=							np.argmin([n.f for n in _open]   )
            UpperCAmelCase_    				=							_open[min_f]
            _closed.append(_open.pop(SCREAMING_SNAKE_CASE_   )   )
            if current == goal:
                  break
            for n in world.get_neigbours(SCREAMING_SNAKE_CASE_   ):
                  for c in _closed:
                        if c == n:
                              continue
                  UpperCAmelCase_    				=							current.g + 1
                  UpperCAmelCase_    				=							n.position
                  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(SCREAMING_SNAKE_CASE_   )
      UpperCAmelCase_    				=							[]
      while current.parent is not None:
            path.append(current.position   )
            UpperCAmelCase_    				=							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)









"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase      =		logging.get_logger(__name__)

lowerCamelCase      =		{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  '''mobilenet_v1'''



       def __init__(							self    :						Tuple	,       _UpperCAmelCase    :						int=3	,       _UpperCAmelCase    :						Union[str, Any]=224	,       _UpperCAmelCase    :						Any=1.0	,       _UpperCAmelCase    :						Any=8	,       _UpperCAmelCase    :						List[Any]="relu6"	,       _UpperCAmelCase    :						List[str]=True	,       _UpperCAmelCase    :						Dict=0.999	,       _UpperCAmelCase    :						List[Any]=0.02	,       _UpperCAmelCase    :						List[Any]=0.001	,       **_UpperCAmelCase    :						str	,       )				->		Optional[int]:


             '''simple docstring'''




             super().__init__(**_UpperCAmelCase					)

             if depth_multiplier <= 0:
                   raise ValueError("depth_multiplier must be greater than zero."					)

             UpperCAmelCase_    				=							num_channels
             UpperCAmelCase_    				=							image_size
             UpperCAmelCase_    				=							depth_multiplier
             UpperCAmelCase_    				=							min_depth
             UpperCAmelCase_    				=							hidden_act
             UpperCAmelCase_    				=							tf_padding
             UpperCAmelCase_    				=							classifier_dropout_prob
             UpperCAmelCase_    				=							initializer_range
             UpperCAmelCase_    				=							layer_norm_eps



class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  version.parse('''1.11'''   )



       @property
       def   lowercase__       (							self    :						List[Any]					)				->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




             return OrderedDict([("pixel_values", {0: "batch"})]					)



       @property
       def   lowercase__       (							self    :						List[Any]					)				->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




             if self.task == "image-classification":
                   return OrderedDict([("logits", {0: "batch"})]					)
             else:
                   return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]					)







       @property
       def   lowercase__       (							self    :						Tuple					)				->		float:


             '''simple docstring'''




             return 1e-4




