diff --git a/tensorflow/python/saved_model/simple_save_test.py b/tensorflow/python/saved_model/simple_save_test.py
index 21c2e9df2fae9f..21be3677aa8496 100644
--- a/tensorflow/python/saved_model/simple_save_test.py
+++ b/tensorflow/python/saved_model/simple_save_test.py
@@ -21,7 +21,6 @@
 import os
 
 from tensorflow.python.framework import ops
-from tensorflow.python.framework import test_util
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import test
 from tensorflow.python.saved_model import loader
@@ -32,7 +31,7 @@
 
 class SimpleSaveTest(test.TestCase):
 
-  def _init_and_validate_variable(self, sess, variable_name, variable_value):
+  def _init_and_validate_variable(self, variable_name, variable_value):
     v = variables.Variable(variable_value, name=variable_name)
     self.evaluate(variables.global_variables_initializer())
     self.assertEqual(variable_value, self.evaluate(v))
@@ -54,50 +53,54 @@ def _check_tensor_info(self, actual_tensor_info, expected_tensor):
       self.assertEqual(actual_tensor_info.tensor_shape.dim[i].size,
                        expected_tensor.shape[i])
 
-  @test_util.run_deprecated_v1
   def testSimpleSave(self):
     """Test simple_save that uses the default parameters."""
     export_dir = os.path.join(test.get_temp_dir(),
                               "test_simple_save")
 
-    # Initialize input and output variables and save a prediction graph using
-    # the default parameters.
-    with self.session(graph=ops.Graph()) as sess:
-      var_x = self._init_and_validate_variable(sess, "var_x", 1)
-      var_y = self._init_and_validate_variable(sess, "var_y", 2)
-      inputs = {"x": var_x}
-      outputs = {"y": var_y}
-      simple_save.simple_save(sess, export_dir, inputs, outputs)
-
-    # Restore the graph with a valid tag and check the global variables and
-    # signature def map.
-    with self.session(graph=ops.Graph()) as sess:
-      graph = loader.load(sess, [tag_constants.SERVING], export_dir)
-      collection_vars = ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)
-
-      # Check value and metadata of the saved variables.
-      self.assertEqual(len(collection_vars), 2)
-      self.assertEqual(1, collection_vars[0].eval())
-      self.assertEqual(2, collection_vars[1].eval())
-      self._check_variable_info(collection_vars[0], var_x)
-      self._check_variable_info(collection_vars[1], var_y)
-
-      # Check that the appropriate signature_def_map is created with the
-      # default key and method name, and the specified inputs and outputs.
-      signature_def_map = graph.signature_def
-      self.assertEqual(1, len(signature_def_map))
-      self.assertEqual(signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY,
-                       list(signature_def_map.keys())[0])
-
-      signature_def = signature_def_map[
-          signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
-      self.assertEqual(signature_constants.PREDICT_METHOD_NAME,
-                       signature_def.method_name)
-
-      self.assertEqual(1, len(signature_def.inputs))
-      self._check_tensor_info(signature_def.inputs["x"], var_x)
-      self.assertEqual(1, len(signature_def.outputs))
-      self._check_tensor_info(signature_def.outputs["y"], var_y)
+    # Force the test to run in graph mode.
+    # This tests a deprecated v1 API that both requires a session and uses
+    # functionality that does not work with eager tensors (such as
+    # build_tensor_info as called by predict_signature_def).
+    with ops.Graph().as_default():
+      # Initialize input and output variables and save a prediction graph using
+      # the default parameters.
+      with self.session(graph=ops.Graph()) as sess:
+        var_x = self._init_and_validate_variable("var_x", 1)
+        var_y = self._init_and_validate_variable("var_y", 2)
+        inputs = {"x": var_x}
+        outputs = {"y": var_y}
+        simple_save.simple_save(sess, export_dir, inputs, outputs)
+
+      # Restore the graph with a valid tag and check the global variables and
+      # signature def map.
+      with self.session(graph=ops.Graph()) as sess:
+        graph = loader.load(sess, [tag_constants.SERVING], export_dir)
+        collection_vars = ops.get_collection(ops.GraphKeys.GLOBAL_VARIABLES)
+
+        # Check value and metadata of the saved variables.
+        self.assertEqual(len(collection_vars), 2)
+        self.assertEqual(1, collection_vars[0].eval())
+        self.assertEqual(2, collection_vars[1].eval())
+        self._check_variable_info(collection_vars[0], var_x)
+        self._check_variable_info(collection_vars[1], var_y)
+
+        # Check that the appropriate signature_def_map is created with the
+        # default key and method name, and the specified inputs and outputs.
+        signature_def_map = graph.signature_def
+        self.assertEqual(1, len(signature_def_map))
+        self.assertEqual(signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY,
+                         list(signature_def_map.keys())[0])
+
+        signature_def = signature_def_map[
+            signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
+        self.assertEqual(signature_constants.PREDICT_METHOD_NAME,
+                         signature_def.method_name)
+
+        self.assertEqual(1, len(signature_def.inputs))
+        self._check_tensor_info(signature_def.inputs["x"], var_x)
+        self.assertEqual(1, len(signature_def.outputs))
+        self._check_tensor_info(signature_def.outputs["y"], var_y)
 
 
 if __name__ == "__main__":