yacht_regression.py 文件源码

def loglike(nn, sample_preds, y):
    """Return the Avg. Test Log-Likelihood
    """
    if y.shape[1] == 1:
        y = y.ravel()
    sample_ll = np.zeros((sample_preds.shape[1], sample_preds.shape[0]))
    a, b = np.exp(nn.extra_inf['a1'].get_value()), np.exp(nn.extra_inf['b1'].get_value())
    etau, elogtau = (a / b).astype(np.float32), (psi(a) - np.log(b)).astype(np.float32)
    for sample in xrange(sample_preds.shape[0]):
        ypred = sample_preds[sample].astype(np.float32)
        if len(y.shape) > 1:
            sll = -.5 * np.sum(etau * (y - ypred)**2, axis=1)
        else:
            sll = -.5 * etau * (y - ypred)**2
        sample_ll[:, sample] = sll

    return np.mean(logsumexp(sample_ll, axis=1) - np.log(sample_preds.shape[0]) - .5 * np.log(2*np.pi) + .5 * elogtau.sum())