analyzer.py 文件源码

def test(model, xs, ts, uss=None):
    model.reset_state()
    tags = model([Variable(
        np.array([x], dtype=np.int32)
    ) for x in xs])
    zss = []

    y_mat = np.zeros((2, 2))
    zs_mat = tuple(
        np.zeros((clf.n_output, clf.n_output))
        for clf in model.tagger.classifiers
    )
    for t, (y, zs) in zip(ts, tags):
        y_mat[t, int(cf.sigmoid(y).data[0, 0] > 0.5)] += 1.0
        if t:
            zss.append(zs)
    if uss:
        assert len(uss) == len(zss)
        for us, zs in zip(uss, zss):
            for m, u, z in zip(zs_mat, us, zs):
                m[u, cf.softmax(z).data.argmax(1)[0]] += 1
    return y_mat, zs_mat