train_rotconv.py 文件源码

def model(X, w, w2, w3, w4, w_o, p_drop_conv, p_drop_hid, convs_mult):
    l1 = conv_and_pool(X, w, convs_mult, p_drop_conv)
    l2 = conv_and_pool(l1, w2, convs_mult, p_drop_conv)
    l3 = conv_and_pool(l2, w3, convs_mult, p_drop_conv)
    l4 = rectify(conv2d(l3, w4))
    l4 = dropout(l4, p_drop_hid)
    l4 = T.flatten(l4, outdim=2)
    pyx = nn.nonlinearities.softmax(T.dot(l4, w_o))
    return pyx