vgp.py 文件源码

def __init__(self, X, Y, kern, likelihood,
                 mean_function=None,
                 num_latent=None,
                 **kwargs):
        """
        X is a data matrix, size N x D
        Y is a data matrix, size N x R
        kern, likelihood, mean_function are appropriate GPflow objects

        """

        X = DataHolder(X)
        Y = DataHolder(Y)
        GPModel.__init__(self, X, Y, kern, likelihood, mean_function, **kwargs)
        self.num_data = X.shape[0]
        self.num_latent = num_latent or Y.shape[1]

        self.q_mu = Parameter(np.zeros((self.num_data, self.num_latent)))
        q_sqrt = np.array([np.eye(self.num_data)
                           for _ in range(self.num_latent)]).swapaxes(0, 2)
        transform = transforms.LowerTriangular(self.num_data, self.num_latent)
        self.q_sqrt = Parameter(q_sqrt, transform=transform)