analyzer.py 文件源码

def loss(model, xs, ts, uss=None):
    model.reset_state()
    tags = model([Variable(
        np.array([x], dtype=np.int32)
    ) for x in xs])
    zss = []
    d = Variable(np.array(0, dtype=np.float32))
    for t, (y, zs) in zip(ts, tags):
        d += cf.sigmoid_cross_entropy(
            y, Variable(np.array([[t]], dtype=np.int32))
        )
        if t:
            zss.append(zs)
    if uss:
        assert len(uss) == len(zss)
        for us, zs in zip(uss, zss):
            for u, z in zip(us, zs):
                d += cf.softmax_cross_entropy(
                    z, Variable(np.array([u], dtype=np.int32))
                )
    return d