def METHOD_NAME(image, test=False, w_bias=False):
    h = PF.convolution(image, 16, (5, 5), (1, 1),
                       with_bias=False, name='conv1')
    h = PF.batch_normalization(h, batch_stat=False, name='conv1-bn')
    h = F.max_pooling(h, (2, 2))
    h = F.relu(h)
    h = PF.convolution(h, 16, (5, 5), (1, 1), with_bias=True, name='conv2')
    h = PF.batch_normalization(h, batch_stat=False, name='conv2-bn')
    h = F.max_pooling(h, (2, 2))
    h = F.relu(h)
    h = PF.affine(h, 10, with_bias=False, name='fc1')
    h = F.relu(h)
    pred = PF.affine(h, 10, with_bias=True, name='fc2')
    return pred