6a455db8f33ceefa0f8c544dc427ba6402f85588,gpflow/conditionals/uncertain_conditionals.py,,uncertain_conditional,#Any#Any#Any#Any#Any#Any#,12

Before Change

    num_data = Xnew_mu.shape[0]  // number of new inputs (N)
    num_ind = q_mu.shape[0]  // number of inducing points (M)
    num_func = q_mu.shape[1]  // output dimension (D)

    q_sqrt_r = tf.linalg.band_part(q_sqrt, -1, 0)  // [D, M, M]

After Change

    pXnew = Gaussian(Xnew_mu, Xnew_var)

    num_data = tf.shape(Xnew_mu)[0]  // number of new inputs (N)
    num_ind, num_func = tf.unstack(tf.shape(q_mu), num=2, axis=0)  // number of inducing points (M), output dimension (D)
    q_sqrt_r = tf.linalg.band_part(q_sqrt, -1, 0)  // [D, M, M]

    eKuf = tf.transpose(expectation(pXnew, (kernel, inducing_variable)))  // [M, N] (psi1)

Instances