def _build_common_terms(self):
num_inducing = len(self.feature)
err = self.Y - self.mean_function(self.X) # size N x R
Kdiag = self.kern.Kdiag(self.X)
Kuf = self.feature.Kuf(self.kern, self.X)
Kuu = self.feature.Kuu(self.kern, jitter=settings.numerics.jitter_level)
Luu = tf.cholesky(Kuu) # => Luu Luu^T = Kuu
V = tf.matrix_triangular_solve(Luu, Kuf) # => V^T V = Qff = Kuf^T Kuu^-1 Kuf
diagQff = tf.reduce_sum(tf.square(V), 0)
nu = Kdiag - diagQff + self.likelihood.variance
B = tf.eye(num_inducing, dtype=settings.float_type) + tf.matmul(V / nu, V, transpose_b=True)
L = tf.cholesky(B)
beta = err / tf.expand_dims(nu, 1) # size N x R
alpha = tf.matmul(V, beta) # size N x R
gamma = tf.matrix_triangular_solve(L, alpha, lower=True) # size N x R
return err, nu, Luu, L, alpha, beta, gamma
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