diff --git a/deeplift.egg-info/PKG-INFO b/deeplift.egg-info/PKG-INFO
index 681c185..27ac4fb 100644
--- a/deeplift.egg-info/PKG-INFO
+++ b/deeplift.egg-info/PKG-INFO
@@ -1,13 +1,13 @@
 Metadata-Version: 2.1
 Name: deeplift
-Version: 0.6.9.3
+Version: 0.6.10.0
 Summary: DeepLIFT (Deep Learning Important FeaTures)
 Home-page: https://github.com/kundajelab/deeplift
 License: UNKNOWN
 Description: Algorithms for computing importance scores in deep neural networks.
-        
+
         Implements the methods in "Learning Important Features Through Propagating Activation Differences" by Shrikumar, Greenside & Kundaje, as well as other commonly-used methods such as gradients, guided backprop and integrated gradients. See https://github.com/kundajelab/deeplift for documentation and FAQ.
-                  
+
 Platform: UNKNOWN
 Provides-Extra: tensorflow
 Provides-Extra: tensorflow with gpu
diff --git a/deeplift/__init__.py b/deeplift/__init__.py
index 520f9d8..647cd0e 100644
--- a/deeplift/__init__.py
+++ b/deeplift/__init__.py
@@ -1 +1 @@
-__version__ = '0.6.9.3'
+__version__ = '0.6.10.0'
diff --git a/deeplift/layers/core.py b/deeplift/layers/core.py
index 5e0a57a..6c34621 100644
--- a/deeplift/layers/core.py
+++ b/deeplift/layers/core.py
@@ -69,7 +69,13 @@ def _initialize_mxts(self):
 
     def reset_mxts_updated(self):
         for output_layer in self._output_layers:
-            output_layer.reset_mxts_updated()
+            # only update layer if needed
+            # if output_layer was already called by another layer:
+            #     output_layer._mxts_updated == False
+            # otherwise we call it
+            if output_layer._mxts_updated:                                                                                         
+                 output_layer.reset_mxts_updated()  
+         
         self._initialize_mxts()
         self._mxts_updated = False
         self._mxts_for_inputs_updated = False
diff --git a/setup.py b/setup.py
index 39fceaa..e1247a8 100644
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@
 Implements the methods in "Learning Important Features Through Propagating Activation Differences" by Shrikumar, Greenside & Kundaje, as well as other commonly-used methods such as gradients, guided backprop and integrated gradients. See https://github.com/kundajelab/deeplift for documentation and FAQ.
           """,
           url='https://github.com/kundajelab/deeplift',
-          version='0.6.9.3',
+          version='0.6.10.0',
           packages=['deeplift',
                     'deeplift.layers', 'deeplift.visualization',
                     'deeplift.conversion'],