
import numpy as np



class    _snake_case :


 def __init__(       self):


   '''simple docstring'''




   lowercase__	: Optional[int]     		=   (0, 0)
   lowercase__	: Optional[int]     		=   None
   lowercase__	: Optional[int]     		=   0
   lowercase__	: Optional[Any]     		=   0
   lowercase__	: Tuple     		=   0


 def __eq__(       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return self.position == cell.position



 def   lowercase__  (       self):


   '''simple docstring'''




   print(self.position)



class    _snake_case :


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=(5, 5)):


   '''simple docstring'''




   lowercase__	: List[Any]     		=   np.zeros(SCREAMING_SNAKE_CASE_)
   lowercase__	: int     		=   world_size[0]
   lowercase__	: Tuple     		=   world_size[1]


 def   lowercase__  (       self):


   '''simple docstring'''




   print(self.w)



 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




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

def 		UpperCamelCase						(   lowercase_			,			lowercase_			,			lowercase_ )		->						Tuple:


  '''simple docstring'''






  lowercase__	: List[str]     		=   []
  lowercase__	: int     		=   []
  _open.append(lowercase_ )

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

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


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








from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase__     :		List[Any]        = logging.get_logger(__name__)

lowerCamelCase__     :		Union[str, Any]        = {
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Union[str, Any]	   =      'convbert'


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_=3_05_22       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=12       ,	SCREAMING_SNAKE_CASE_=30_72       ,	SCREAMING_SNAKE_CASE_="gelu"       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=0.1       ,	SCREAMING_SNAKE_CASE_=5_12       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=0.0_2       ,	SCREAMING_SNAKE_CASE_=1E-12       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=0       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=7_68       ,	SCREAMING_SNAKE_CASE_=2       ,	SCREAMING_SNAKE_CASE_=9       ,	SCREAMING_SNAKE_CASE_=1       ,	SCREAMING_SNAKE_CASE_=None       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   super().__init__(
       pad_token_id=SCREAMING_SNAKE_CASE_       ,	bos_token_id=SCREAMING_SNAKE_CASE_       ,	eos_token_id=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_       ,	)

   lowercase__	: Dict     		=   vocab_size
   lowercase__	: List[Any]     		=   hidden_size
   lowercase__	: Optional[Any]     		=   num_hidden_layers
   lowercase__	: Union[str, Any]     		=   num_attention_heads
   lowercase__	: List[str]     		=   intermediate_size
   lowercase__	: Optional[int]     		=   hidden_act
   lowercase__	: Tuple     		=   hidden_dropout_prob
   lowercase__	: List[str]     		=   attention_probs_dropout_prob
   lowercase__	: Tuple     		=   max_position_embeddings
   lowercase__	: Dict     		=   type_vocab_size
   lowercase__	: Union[str, Any]     		=   initializer_range
   lowercase__	: Dict     		=   layer_norm_eps
   lowercase__	: Tuple     		=   embedding_size
   lowercase__	: List[str]     		=   head_ratio
   lowercase__	: Dict     		=   conv_kernel_size
   lowercase__	: Dict     		=   num_groups
   lowercase__	: int     		=   classifier_dropout



class    _snake_case (						UpperCAmelCase_				):


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   if self.task == "multiple-choice":
     lowercase__	: Union[str, Any]     		=   {0: """batch""", 1: """choice""", 2: """sequence"""}
   else:
     lowercase__	: str     		=   {0: """batch""", 1: """sequence"""}
   return OrderedDict(
       [
           ("""input_ids""", dynamic_axis),
           ("""attention_mask""", dynamic_axis),
           ("""token_type_ids""", dynamic_axis),
       ])






