From 0450e228a8edf364d9fa328285c0c56e7d511194 Mon Sep 17 00:00:00 2001 From: James Hensman Date: Tue, 5 May 2015 14:29:07 +0100 Subject: [PATCH] svgp tests are passing with re-ordered chols --- GPy/inference/latent_function_inference/svgp.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/GPy/inference/latent_function_inference/svgp.py b/GPy/inference/latent_function_inference/svgp.py index 261a68b6..b23a09b0 100644 --- a/GPy/inference/latent_function_inference/svgp.py +++ b/GPy/inference/latent_function_inference/svgp.py @@ -100,10 +100,8 @@ class SVGP(LatentFunctionInference): #sum (gradients of) expected likelihood and KL part - log_marginal = F.sum() - dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm*0, dF_dS- dKL_dS*0, dF_dKmm- dKL_dKmm*0, dF_dKmn - #log_marginal = F.sum() - KL - #dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn + log_marginal = F.sum() - KL + dL_dm, dL_dS, dL_dKmm, dL_dKmn = dF_dm - dKL_dm, dF_dS- dKL_dS, dF_dKmm- dKL_dKmm, dF_dKmn dL_dchol = 2.*np.array([np.dot(a,b) for a, b in zip(dL_dS, L) ]) dL_dchol = choleskies.triang_to_flat(dL_dchol)