diff --git a/tensorflow/python/saved_model/builder.py b/tensorflow/python/saved_model/builder.py
index 43b97cf70c651455bcbaf22ffbd6ccac0644764d..24126c01935a02d695d775479b508598725dc36a 100644
--- a/tensorflow/python/saved_model/builder.py
+++ b/tensorflow/python/saved_model/builder.py
@@ -249,11 +249,18 @@ class SavedModelBuilder(object):
     proto_meta_graph_def = self._saved_model.meta_graphs.add()
     proto_meta_graph_def.CopyFrom(meta_graph_def)
 
+  def _maybe_clear_devices(self, clear_devices):
+    if not clear_devices:
+      return
+    for node in ops.get_default_graph().as_graph_def().node:
+      node.device = ""
+
   def add_meta_graph(self,
                      tags,
                      signature_def_map=None,
                      assets_collection=None,
-                     legacy_init_op=None):
+                     legacy_init_op=None,
+                     clear_devices=False):
     """Adds the current meta graph to the SavedModel.
 
     Creates a Saver in the current scope and uses the Saver to export the meta
@@ -268,7 +275,9 @@ class SavedModelBuilder(object):
           that this collection should be a subset of the assets saved as part of
           the first meta graph in the SavedModel.
       legacy_init_op: Op or group of ops to execute after the restore op upon a
-        load.
+          load.
+      clear_devices: Set to true if the device info on the default graph should
+          be cleared.
 
     Raises:
       AssertionError: If the variables for the SavedModel have not been saved
@@ -279,6 +288,8 @@ class SavedModelBuilder(object):
           "Variables and assets have not been saved yet. "
           "Please invoke `add_meta_graph_and_variables()` first.")
 
+    self._maybe_clear_devices(clear_devices)
+
     # Save asset files and write them to disk, if any.
     self._save_and_write_assets(assets_collection)
 
@@ -300,7 +311,8 @@ class SavedModelBuilder(object):
                                    tags,
                                    signature_def_map=None,
                                    assets_collection=None,
-                                   legacy_init_op=None):
+                                   legacy_init_op=None,
+                                   clear_devices=False):
     """Adds the current meta graph to the SavedModel and saves variables.
 
     Creates a Saver to save the variables from the provided session. Exports the
@@ -318,11 +330,15 @@ class SavedModelBuilder(object):
       assets_collection: Assets collection to be saved with SavedModel.
       legacy_init_op: Op or group of ops to execute after the restore op upon a
         load.
+      clear_devices: Set to true if the device info on the default graph should
+          be cleared.
     """
     if self._has_saved_variables:
       raise AssertionError("Variables and assets have already been saved. "
                            "Please invoke `add_meta_graph()` instead.")
 
+    self._maybe_clear_devices(clear_devices)
+
     # Save asset files and write them to disk, if any.
     self._save_and_write_assets(assets_collection)
 
diff --git a/tensorflow/python/saved_model/saved_model_test.py b/tensorflow/python/saved_model/saved_model_test.py
index a50620e113c8a4d50abfc757efed64b73dfadc91..6f2132b49241f9b33a5acdcd288c8913058fea1f 100644
--- a/tensorflow/python/saved_model/saved_model_test.py
+++ b/tensorflow/python/saved_model/saved_model_test.py
@@ -553,6 +553,29 @@ class SavedModelTest(tf.test.TestCase):
       tf.get_collection("init_op")[0].run()
       self.assertEqual(3, tf.get_collection("v")[2].eval())
 
+  def testClearDevices(self):
+    export_dir = os.path.join(tf.test.get_temp_dir(), "test_clear_devices")
+    builder = saved_model_builder.SavedModelBuilder(export_dir)
+
+    # Specify a device and save a variable.
+    tf.reset_default_graph()
+    with tf.Session(
+        target="",
+        config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:
+      with sess.graph.device("/cpu:0"):
+        self._init_and_validate_variable(sess, "v", 42)
+        builder.add_meta_graph_and_variables(
+            sess, [tag_constants.TRAINING], clear_devices=True)
+
+    # Save the SavedModel to disk.
+    builder.save()
+
+    # Restore the graph with a single predefined tag whose variables were saved
+    # without any device information.
+    with self.test_session(graph=tf.Graph()) as sess:
+      loader.load(sess, [tag_constants.TRAINING], export_dir)
+      self.assertEqual(42, tf.get_collection(tf.GraphKeys.VARIABLES)[0].eval())
+
 
 if __name__ == "__main__":
   tf.test.main()