"""simple docstring"""



import numpy as np
from PIL import Image



def 					_lowerCamelCase(					a ,  a ,  a							):
       __a     				=  np.array(a							)
       if arr.shape[0] != arr.shape[1]:
              raise ValueError("The input array is not a square matrix"							)
       __a     				=  0
       __a     				=  0
       __a     				=  0
       __a     				=  0

       # compute the shape of the output matrix
       __a     				=  (arr.shape[0] - size) // stride + 1
       # initialize the output matrix with zeros of shape maxpool_shape
       __a     				=  np.zeros((maxpool_shape, maxpool_shape)							)

       while i < arr.shape[0]:
              if i + size > arr.shape[0]:
                     # if the end of the matrix is reached, break
                     break
              while j < arr.shape[1]:
                     # if the end of the matrix is reached, break
                     if j + size > arr.shape[1]:
                            break
                     # compute the maximum of the pooling matrix
                     __a     				=  np.max(arr[i : i + size, j : j + size]							)
                     # shift the pooling matrix by stride of column pixels
                     j += stride
                     mat_j += 1

              # shift the pooling matrix by stride of row pixels
              i += stride
              mat_i += 1

              # reset the column index to 0
              __a     				=  0
              __a     				=  0

       return updated_arr



def 					_lowerCamelCase(					a ,  a ,  a							):
       __a     				=  np.array(a							)
       if arr.shape[0] != arr.shape[1]:
              raise ValueError("The input array is not a square matrix"							)
       __a     				=  0
       __a     				=  0
       __a     				=  0
       __a     				=  0

       # compute the shape of the output matrix
       __a     				=  (arr.shape[0] - size) // stride + 1
       # initialize the output matrix with zeros of shape avgpool_shape
       __a     				=  np.zeros((avgpool_shape, avgpool_shape)							)

       while i < arr.shape[0]:
              # if the end of the matrix is reached, break
              if i + size > arr.shape[0]:
                     break
              while j < arr.shape[1]:
                     # if the end of the matrix is reached, break
                     if j + size > arr.shape[1]:
                            break
                     # compute the average of the pooling matrix
                     __a     				=  int(np.average(arr[i : i + size, j : j + size]							)							)
                     # shift the pooling matrix by stride of column pixels
                     j += stride
                     mat_j += 1

              # shift the pooling matrix by stride of row pixels
              i += stride
              mat_i += 1
              # reset the column index to 0
              __a     				=  0
              __a     				=  0

       return updated_arr


# Main Function
if __name__ == "__main__":
   from doctest import testmod

   testmod(name="""avgpooling""", verbose=True)

   # Loading the image
   SCREAMING_SNAKE_CASE__:Optional[Any]			=	Image.open("""path_to_image""")

   # Converting the image to numpy array and maxpooling, displaying the result
   # Ensure that the image is a square matrix

   Image.fromarray(maxpooling(np.array(image), size=3, stride=2)).show()

   # Converting the image to numpy array and averagepooling, displaying the result
   # Ensure that the image is a square matrix

   Image.fromarray(avgpooling(np.array(image), size=3, stride=2)).show()

"""simple docstring"""



import os



def 					_lowerCamelCase(					):
       with open(os.path.dirname(a							) + "/grid.txt"							) as f:
              __a     				=  []  # noqa: E741
              for _ in range(2_0							):
                     l.append([int(a							) for x in f.readline().split()]							)

              __a     				=  0

              # right
              for i in range(2_0							):
                     for j in range(1_7							):
                            __a     				=  l[i][j] * l[i][j + 1] * l[i][j + 2] * l[i][j + 3]
                            if temp > maximum:
                                   __a     				=  temp

        # down
              for i in range(1_7							):
                     for j in range(2_0							):
                            __a     				=  l[i][j] * l[i + 1][j] * l[i + 2][j] * l[i + 3][j]
                            if temp > maximum:
                                   __a     				=  temp

        # diagonal 1
              for i in range(1_7							):
                     for j in range(1_7							):
                            __a     				=  l[i][j] * l[i + 1][j + 1] * l[i + 2][j + 2] * l[i + 3][j + 3]
                            if temp > maximum:
                                   __a     				=  temp

        # diagonal 2
              for i in range(1_7							):
                     for j in range(3 ,  2_0							):
                            __a     				=  l[i][j] * l[i + 1][j - 1] * l[i + 2][j - 2] * l[i + 3][j - 3]
                            if temp > maximum:
                                   __a     				=  temp
              return maximum


if __name__ == "__main__":
   print(solution())
