dgp.py 文件源码

def predict_density(self, Xnew, Ynew, num_samples):
        Fmean, Fvar = self.build_predict(Xnew, full_cov=False, S=num_samples)
        S, N, D = shape_as_list(Fmean)
        Ynew = tile_over_samples(Ynew, num_samples)
        flat_arrays = [tf.reshape(a, [S*N, -1]) for a in [Fmean, Fvar, Ynew]]
        l_flat = self.likelihood.predict_density(*flat_arrays)
        l = tf.reshape(l_flat, [S, N, -1])
        log_num_samples = tf.log(tf.cast(num_samples, float_type))
        return tf.reduce_logsumexp(l - log_num_samples, axis=0)