import numpy as np
def im2col(input_data, filter_h, filter_w, stride=1, pad=0):
N, C, H, W = input_data.shape
out_h = (H + 2 * pad - filter_h) // stride + 1
out_w = (W + 2 * pad - filter_w) // stride + 1
img = np.pad(input_data, [(0, 0), (0, 0), (pad, pad), (pad, pad)], 'constant')
col = np.zeros((N, C, filter_h, filter_w, out_h, out_w))
for y in range(filter_h):
y_max = y + stride * out_h
for x in range(filter_w):
x_max = x + stride * out_w
col[:, :, y, x, :, :] = img[:, :, y:y_max:stride, x:x_max:stride]
col = col.transpose(0, 4, 5, 1, 2, 3).reshape(N * out_h * out_w, -1)
return col
a = np.array([1,2,0,7,1,0,0,9,2,3,2,3,3,0,1,2,1,2,2,4,0,1,0,1,6,0,1,2,1,2,2,4,0,1,8,1]).reshape(6,6)
a2 = a.reshape(1,1,6,6)
result = im2col(a2,3,3,3,0)
b = np.max(result,axis=1)
c = b.reshape(2,2)
c