diff --git a/GPy/inference/latent_function_inference/var_dtc_parallel.py b/GPy/inference/latent_function_inference/var_dtc_parallel.py
index 43e52e2b..a4803460 100644
--- a/GPy/inference/latent_function_inference/var_dtc_parallel.py
+++ b/GPy/inference/latent_function_inference/var_dtc_parallel.py
@@ -388,10 +388,18 @@ def update_gradients(model, mpi_comm=None):
     #gradients w.r.t. Z
     model.Z.gradient += model.kern.gradients_X(dL_dKmm, model.Z)
     
-    # Update Log-likelihood
-    KL_div = model.variational_prior.KL_divergence(X, N=model.Y.shape[0])
-    # update for the KL divergence
-    model.variational_prior.update_gradients_KL(X, N=model.Y.shape[0])
+    from ...core.parameterization.variational import SpikeAndSlabPrior
+    if isinstance(model.variational_prior, SpikeAndSlabPrior):
+        # Update Log-likelihood
+        KL_div = model.variational_prior.KL_divergence(X, N=model.Y.shape[0])
+        # update for the KL divergence
+        model.variational_prior.update_gradients_KL(X, N=model.Y.shape[0])
+    else:
+        # Update Log-likelihood
+        KL_div = model.variational_prior.KL_divergence(X)
+        # update for the KL divergence
+        model.variational_prior.update_gradients_KL(X)
+
 
     if mpi_comm != None:
         KL_div_all = np.array(KL_div)