Hi! Here’s the network definition:
layers = []

layers += [nn.Conv2d(in_channels, 32, kernel_size=conv_kernel[0]),
           nn.Tanh(),
           nn.LPPool2d(norm_type=2, kernel_size=pool_kernel[0])]
layers += [SpatialSubtractiveNormalization2d(in_channels=32, kernel_size=5)]

layers += [nn.Conv2d(32, 64, kernel_size=conv_kernel[1]),
           nn.Tanh(),
           nn.LPPool2d(norm_type=2, kernel_size=pool_kernel[1])]
layers += [SpatialSubtractiveNormalization2d(in_channels=64, kernel_size=5)]

layers += [nn.Conv2d(64, 128, kernel_size=conv_kernel[2]),
           nn.Tanh(),
           nn.LPPool2d(norm_type=2, kernel_size=pool_kernel[2])]

Why does the model matter?