from heapq import heappop, heappush

import numpy as np







def  __UpperCamelCase    (						A ,							A ,							A ,							A ,							):
     UpperCamelCase__						,       UpperCamelCase__										=      grid.shape
     UpperCamelCase__										=      [-1, 1, 0, 0]
     UpperCamelCase__										=      [0, 0, -1, 1]
     if allow_diagonal:
          dx += [-1, -1, 1, 1]
          dy += [-1, 1, -1, 1]

     UpperCamelCase__						,       UpperCamelCase__										=      [(0, source)], set()
     UpperCamelCase__										=      np.full((rows, cols) ,							np.inf							)
     UpperCamelCase__										=      0
     UpperCamelCase__										=      np.empty((rows, cols) ,							dtype=A							)
     UpperCamelCase__										=      None

     while queue:
          ((UpperCamelCase__)						,       (UpperCamelCase__))										=      heappop(A							)
          if (x, y) in visited:
               continue
          visited.add((x, y)							)

          if (x, y) == destination:
               UpperCamelCase__										=      []
               while (x, y) != source:
                    path.append((x, y)							)
                    UpperCamelCase__						,       UpperCamelCase__										=      predecessors[x, y]
               path.append(A							)  # add the source manually
               path.reverse()
               return matrix[destination], path

          for i in range(len(A							)							):
               UpperCamelCase__						,       UpperCamelCase__										=      x + dx[i], y + dy[i]
               if 0 <= nx < rows and 0 <= ny < cols:
                    UpperCamelCase__										=      grid[nx][ny]
                    if next_node == 1 and matrix[nx, ny] > dist + 1:
                         heappush(A ,							(dist + 1, (nx, ny))							)
                         UpperCamelCase__										=      dist + 1
                         UpperCamelCase__										=      (x, y)

     return np.inf, []


if __name__ == "__main__":
     import doctest

     doctest.testmod()




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__magic_name__								=logging.get_logger(__name__)

__magic_name__								={
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}



class     _A   (    __UpperCamelCase							):
  SCREAMING_SNAKE_CASE_	:	Dict						="vit_mae"






  def __init__(self   ,				SCREAMING_SNAKE_CASE_=768   ,				SCREAMING_SNAKE_CASE_=12   ,				SCREAMING_SNAKE_CASE_=12   ,				SCREAMING_SNAKE_CASE_=3072   ,				SCREAMING_SNAKE_CASE_="gelu"   ,				SCREAMING_SNAKE_CASE_=0.0   ,				SCREAMING_SNAKE_CASE_=0.0   ,				SCREAMING_SNAKE_CASE_=0.02   ,				SCREAMING_SNAKE_CASE_=1E-12   ,				SCREAMING_SNAKE_CASE_=224   ,				SCREAMING_SNAKE_CASE_=16   ,				SCREAMING_SNAKE_CASE_=3   ,				SCREAMING_SNAKE_CASE_=True   ,				SCREAMING_SNAKE_CASE_=16   ,				SCREAMING_SNAKE_CASE_=512   ,				SCREAMING_SNAKE_CASE_=8   ,				SCREAMING_SNAKE_CASE_=2048   ,				SCREAMING_SNAKE_CASE_=0.75   ,				SCREAMING_SNAKE_CASE_=False   ,				**SCREAMING_SNAKE_CASE_   ,				)		->      Optional[Any]:





       '''simple docstring'''





       super().__init__(**SCREAMING_SNAKE_CASE_	)

       UpperCamelCase__										=      hidden_size
       UpperCamelCase__										=      num_hidden_layers
       UpperCamelCase__										=      num_attention_heads
       UpperCamelCase__										=      intermediate_size
       UpperCamelCase__										=      hidden_act
       UpperCamelCase__										=      hidden_dropout_prob
       UpperCamelCase__										=      attention_probs_dropout_prob
       UpperCamelCase__										=      initializer_range
       UpperCamelCase__										=      layer_norm_eps
       UpperCamelCase__										=      image_size
       UpperCamelCase__										=      patch_size
       UpperCamelCase__										=      num_channels
       UpperCamelCase__										=      qkv_bias
       UpperCamelCase__										=      decoder_num_attention_heads
       UpperCamelCase__										=      decoder_hidden_size
       UpperCamelCase__										=      decoder_num_hidden_layers
       UpperCamelCase__										=      decoder_intermediate_size
       UpperCamelCase__										=      mask_ratio
       UpperCamelCase__										=      norm_pix_loss



