cnn_model.py 文件源码

def cnn_model(X, w, w2, w3, w4, w_o, p_drop_conv, p_drop_hidden):
    l1a = rectify(T.nnet.conv2d(X, w, border_mode='full'))
    l1 = pool.pool_2d(l1a, (2, 2))
    l1 = dropout(l1, p_drop_conv)

    l2a = rectify(T.nnet.conv2d(l1, w2))
    l2 = pool.pool_2d(l2a, (2, 2))
    l2 = dropout(l2, p_drop_conv)

    l3a = rectify(T.nnet.conv2d(l2, w3))
    l3b = pool.pool_2d(l3a, (2, 2))
    l3 = T.flatten(l3b, outdim=2)
    l3 = dropout(l3, p_drop_conv)

    l4 = rectify(T.dot(l3, w4))
    l4 = dropout(l4, p_drop_hidden)

    pyx = softmax(T.dot(l4, w_o))
    return l1, l2, l3, l4, pyx