diff --git a/tensorflow/cc/framework/gradients_test.cc b/tensorflow/cc/framework/gradients_test.cc
index 26e3170ad8e..75291678177 100644
--- a/tensorflow/cc/framework/gradients_test.cc
+++ b/tensorflow/cc/framework/gradients_test.cc
@@ -503,6 +503,42 @@ TEST_F(GradientsTest, MultiOutputNodeDependentOutputs) {
   EXPECT_EQ(grad_result[0].flat<float>()(0), 17610.0f);
 }
 
+TEST_F(GradientsTest, AddSymbolicGradientsTest) {
+  Scope scope = Scope::NewRootScope();
+  for (int cnt = 0; cnt < 100; ++cnt) {
+    int N = 5 + rand() % 10;
+    // Construct forward graph.
+    OutputList inputs;
+    for (int i = 0; i < N; ++i) {
+      auto a = Const(scope, i, {1});
+      inputs.push_back(a);
+    }
+
+    auto pack = Stack(scope, inputs);
+    TF_ASSERT_OK(scope.status());
+
+    // Construct grad inputs.
+    OutputList output_grads;
+    Tensor ts(DT_INT32, {N, 1});
+    auto v = ts.matrix<int32>();
+    for (int i = 0; i < N; ++i) {
+      v(i, 0) = i;
+    }
+    auto dy = Const(scope, ts);
+    output_grads.push_back(dy);
+    // Call AddSymbolicGradients.
+    std::vector<Output> grad_outputs;
+    TF_ASSERT_OK(AddSymbolicGradients(scope, {pack.output}, inputs,
+                                      output_grads, &grad_outputs));
+    ClientSession session((scope));
+    std::vector<Tensor> in_grad;
+    TF_ASSERT_OK(session.Run(grad_outputs, &in_grad));
+    for (int i = 0; i < N; ++i) {
+      test::ExpectTensorEqual<int>(in_grad[i], test::AsTensor<int>({i}, {1}));
+    }
+  }
+}
+
 // StopGradientSingleOutputMultiEdgeTest tests combinations of valid and
 // 'NoGradient' (induced by StopGradient op) returned along multiple edges from
 // a single nodes output.