diff --git a/GPy/kern/src/diff_kern.py b/GPy/kern/src/diff_kern.py
index 2c141ef5..df939c57 100644
--- a/GPy/kern/src/diff_kern.py
+++ b/GPy/kern/src/diff_kern.py
@@ -48,7 +48,7 @@ class DiffKern(CombinationKernel):
         self.base_kern.reset_gradients()
 
     def get_gradient(self):
-        return self.base_kern.gradient.copy()
+        return self.base_kern.gradient
 
     def append_gradient(self, gradient):
         self.base_kern.gradient += gradient
diff --git a/GPy/kern/src/kern.py b/GPy/kern/src/kern.py
index bf0062af..20061bc5 100644
--- a/GPy/kern/src/kern.py
+++ b/GPy/kern/src/kern.py
@@ -202,7 +202,7 @@ class Kern(Parameterized):
         raise NotImplementedError
     
     def get_gradient(self):
-        return self.gradient.copy()
+        return self.gradient
     
     def append_gradient(self,gradient):
         self.gradient += gradient
diff --git a/GPy/kern/src/multioutput_derivative_kern.py b/GPy/kern/src/multioutput_derivative_kern.py
index 0a969239..4054947a 100644
--- a/GPy/kern/src/multioutput_derivative_kern.py
+++ b/GPy/kern/src/multioutput_derivative_kern.py
@@ -23,7 +23,7 @@ class KernWrapper(Kern):
         return self.fg(dL_dK, X, X2=X2)
 
     def get_gradient(self):
-        return self.base_kern.gradient.copy()
+        return self.base_kern.gradient
 
     def append_gradient(self, gradient):
         self.base_kern.gradient += gradient
diff --git a/GPy/kern/src/multioutput_kern.py b/GPy/kern/src/multioutput_kern.py
index 61b7a6d5..a28d5bbb 100644
--- a/GPy/kern/src/multioutput_kern.py
+++ b/GPy/kern/src/multioutput_kern.py
@@ -97,12 +97,12 @@ class MultioutputKern(CombinationKernel):
         return target
     
     def _update_gradients_full_wrapper(self, cov_struct, dL_dK, X, X2):
-        gradient = cov_struct['kern'].get_gradient()
+        gradient = cov_struct['kern'].get_gradient().copy()
         cov_struct['update_gradients_full'](dL_dK, X, X2)
         cov_struct['kern'].append_gradient(gradient)
     
     def _update_gradients_diag_wrapper(self, kern, dL_dKdiag, X):
-        gradient = kern.get_gradient()
+        gradient = kern.get_gradient().copy()
         kern.update_gradients_diag(dL_dKdiag, X)
         kern.append_gradient(gradient)