diff --git a/trains/utilities/frameworks.py b/trains/utilities/frameworks.py
index bb4724d3..3da630bc 100644
--- a/trains/utilities/frameworks.py
+++ b/trains/utilities/frameworks.py
@@ -1047,7 +1047,8 @@ class PatchTensorFlowEager(object):
 
 class PatchKerasModelIO(object):
     __main_task = None
-    __patched = None
+    __patched_keras = None
+    __patched_tensorflow = None
 
     @staticmethod
     def update_current_task(task, **kwargs):
@@ -1058,7 +1059,7 @@ class PatchKerasModelIO(object):
 
     @staticmethod
     def _patch_model_checkpoint():
-        if 'keras' in sys.modules:
+        if 'keras' in sys.modules and not PatchKerasModelIO.__patched_keras:
             try:
                 from keras.engine.network import Network
             except ImportError:
@@ -1071,8 +1072,17 @@ class PatchKerasModelIO(object):
                 from keras import models as keras_saving
             except ImportError:
                 keras_saving = None
-            PatchKerasModelIO._patch_io_calls(Network, Sequential, keras_saving)
-        if 'tensorflow' in sys.modules:
+            # check that we are not patching anything twice
+            if PatchKerasModelIO.__patched_tensorflow:
+                PatchKerasModelIO.__patched_keras = [
+                    Network if PatchKerasModelIO.__patched_tensorflow[0] != Network else None,
+                    Sequential if PatchKerasModelIO.__patched_tensorflow[1] != Sequential else None,
+                    keras_saving if PatchKerasModelIO.__patched_tensorflow[2] != keras_saving else None,]
+            else:
+                PatchKerasModelIO.__patched_keras = [Network, Sequential, keras_saving]
+            PatchKerasModelIO._patch_io_calls(*PatchKerasModelIO.__patched_keras)
+
+        if 'tensorflow' in sys.modules and not PatchKerasModelIO.__patched_tensorflow:
             try:
                 # hack: make sure tensorflow.__init__ is called
                 import tensorflow
@@ -1091,29 +1101,34 @@ class PatchKerasModelIO(object):
                 from tensorflow.python.keras import models as keras_saving
             except ImportError:
                 keras_saving = None
-            PatchKerasModelIO._patch_io_calls(Network, Sequential, keras_saving)
+
+            if PatchKerasModelIO.__patched_keras:
+                PatchKerasModelIO.__patched_tensorflow = [
+                    Network if PatchKerasModelIO.__patched_keras[0] != Network else None,
+                    Sequential if PatchKerasModelIO.__patched_keras[1] != Sequential else None,
+                    keras_saving if PatchKerasModelIO.__patched_keras[2] != keras_saving else None,]
+            else:
+                PatchKerasModelIO.__patched_tensorflow = [Network, Sequential, keras_saving]
+            PatchKerasModelIO._patch_io_calls(*PatchKerasModelIO.__patched_tensorflow)
 
     @staticmethod
     def _patch_io_calls(Network, Sequential, keras_saving):
         try:
-            # only patch once
-            if not PatchKerasModelIO.__patched:
-                PatchKerasModelIO.__patched = True
-                if Sequential is not None:
-                    Sequential._updated_config = _patched_call(Sequential._updated_config,
-                                                               PatchKerasModelIO._updated_config)
-                    Sequential.from_config = _patched_call(Sequential.from_config, PatchKerasModelIO._from_config)
+            if Sequential is not None:
+                Sequential._updated_config = _patched_call(Sequential._updated_config,
+                                                           PatchKerasModelIO._updated_config)
+                Sequential.from_config = _patched_call(Sequential.from_config, PatchKerasModelIO._from_config)
 
-                if Network is not None:
-                    Network._updated_config = _patched_call(Network._updated_config, PatchKerasModelIO._updated_config)
-                    Network.from_config = _patched_call(Network.from_config, PatchKerasModelIO._from_config)
-                    Network.save = _patched_call(Network.save, PatchKerasModelIO._save)
-                    Network.save_weights = _patched_call(Network.save_weights, PatchKerasModelIO._save_weights)
-                    Network.load_weights = _patched_call(Network.load_weights, PatchKerasModelIO._load_weights)
+            if Network is not None:
+                Network._updated_config = _patched_call(Network._updated_config, PatchKerasModelIO._updated_config)
+                Network.from_config = _patched_call(Network.from_config, PatchKerasModelIO._from_config)
+                Network.save = _patched_call(Network.save, PatchKerasModelIO._save)
+                Network.save_weights = _patched_call(Network.save_weights, PatchKerasModelIO._save_weights)
+                Network.load_weights = _patched_call(Network.load_weights, PatchKerasModelIO._load_weights)
 
-                if keras_saving is not None:
-                    keras_saving.save_model = _patched_call(keras_saving.save_model, PatchKerasModelIO._save_model)
-                    keras_saving.load_model = _patched_call(keras_saving.load_model, PatchKerasModelIO._load_model)
+            if keras_saving is not None:
+                keras_saving.save_model = _patched_call(keras_saving.save_model, PatchKerasModelIO._save_model)
+                keras_saving.load_model = _patched_call(keras_saving.load_model, PatchKerasModelIO._load_model)
         except Exception as ex:
             getLogger(TrainsFrameworkAdapter).warning(str(ex))