then calculate convolution using nn.Conv2d,
patches_conv = nn.Conv2d(64, 64, 3, 1, 1)(patches)

fig, ax = plt.subplots(figsize=(8, 8), nrows=8, ncols=8)
plt.subplots_adjust(hspace=0.02, wspace=0.005)
for i, axes in enumerate(ax.ravel()):
    axes.imshow(patches_conv[0, i].detach().numpy()*70, vmin=0, vmax=70, cmap='pyart_NWSRef')
    axes.set_axis_off()

截屏2020-11-28 下午7.29.38914×892 148 KB
It does not reconstruct the patched model prediction image. It does not works using the F.fold function to reconstruct the image, and get the same image.
So I’m very confused, could you help me?