kernels.py 文件源码

def K(self, X, X2=None, presliced=False):
        if X2 is None:
            d = tf.fill(tf.stack([tf.shape(X)[0]]), tf.squeeze(self.variance))
            return tf.matrix_diag(d)
        else:
            shape = tf.stack([tf.shape(X)[0], tf.shape(X2)[0]])
            return tf.zeros(shape, settings.float_type)