diff --git a/server/analysis/gpr/gprc.py b/server/analysis/gpr/gprc.py
index 341650e..86a4a75 100644
--- a/server/analysis/gpr/gprc.py
+++ b/server/analysis/gpr/gprc.py
@@ -45,4 +45,4 @@ class GPRC(GPR):
         else:
             fvar = self.kern.Kdiag(Xnew) - tf.reduce_sum(tf.square(A), 0)
             fvar = tf.tile(tf.reshape(fvar, (-1, 1)), [1, tf.shape(self.Y)[1]])
-        return fmean, fvar
+        return fmean, fvar, self.kern.variance, self.kern.lengthscales, self.likelihood.variance
diff --git a/server/analysis/gpr/optimize.py b/server/analysis/gpr/optimize.py
index cf31f1a..ca82cae 100644
--- a/server/analysis/gpr/optimize.py
+++ b/server/analysis/gpr/optimize.py
@@ -26,7 +26,7 @@ class GPRGDResult():
 
 
 def tf_optimize(model, Xnew_arr, learning_rate=0.01, maxiter=100, ucb_beta=3.,
-                active_dims=None, bounds=None):
+                active_dims=None, bounds=None, debug=True):
     Xnew_arr = check_array(Xnew_arr, copy=False, warn_on_dtype=True, dtype=FLOAT_DTYPES)
 
     Xnew = tf.Variable(Xnew_arr, name='Xnew', dtype=settings.float_type)
@@ -52,7 +52,8 @@ def tf_optimize(model, Xnew_arr, learning_rate=0.01, maxiter=100, ucb_beta=3.,
         Xin = Xnew_bounded
 
     beta_t = tf.constant(ucb_beta, name='ucb_beta', dtype=settings.float_type)
-    y_mean_var = model.likelihood.predict_mean_and_var(*model._build_predict(Xin))
+    fmean, fvar, kvar, kls, lvar = model._build_predict(Xin)  # pylint: disable=protected-access
+    y_mean_var = model.likelihood.predict_mean_and_var(fmean, fvar)
     y_mean = y_mean_var[0]
     y_var = y_mean_var[1]
     y_std = tf.sqrt(y_var)
@@ -74,4 +75,8 @@ def tf_optimize(model, Xnew_arr, learning_rate=0.01, maxiter=100, ucb_beta=3.,
         assert_all_finite(y_mean_value)
         assert_all_finite(y_std_value)
         assert_all_finite(loss_value)
+        if debug:
+            LOG.info("kernel variance: %f", session.run(kvar))
+            LOG.info("kernel lengthscale: %f", session.run(kls))
+            LOG.info("likelihood variance: %f", session.run(lvar))
         return GPRGDResult(y_mean_value, y_std_value, loss_value, Xnew_value)
diff --git a/server/website/website/settings/constants.py b/server/website/website/settings/constants.py
index d0424bf..0157015 100644
--- a/server/website/website/settings/constants.py
+++ b/server/website/website/settings/constants.py
@@ -66,7 +66,7 @@ HP_MAX_ITER = 5000
 HP_LEARNING_RATE = 0.001
 
 # ---GRADIENT DESCENT FOR DNN---
-DNN_TRAIN_ITER = 500
+DNN_TRAIN_ITER = 100
 
 DNN_EXPLORE = False