diff --git a/onnx/test/cpp/shape_inference_test.cc b/onnx/test/cpp/shape_inference_test.cc
index 614fa10bec8..9791958cc5c 100644
--- a/onnx/test/cpp/shape_inference_test.cc
+++ b/onnx/test/cpp/shape_inference_test.cc
@@ -507,8 +507,7 @@ TEST(GraphInferencerImplTest, Scan9_BasicTest) {
   doInferencingTest(false);
 }
 
-void RunReshapeShapeInfTest(const char* modelStr, TensorShapeProto& expectedShape) {
-  ModelProto model;
+void ParseAndInfer(ModelProto& model, const char* modelStr) {
   OnnxParser parser(modelStr);
   auto status = parser.Parse(model);
   EXPECT_TRUE(status.IsOK()) << status.ErrorMessage();
@@ -516,6 +515,11 @@ void RunReshapeShapeInfTest(const char* modelStr, TensorShapeProto& expectedShap
 
   ShapeInferenceOptions options{true, 1, true};
   ONNX_NAMESPACE::shape_inference::InferShapes(model, ONNX_NAMESPACE::OpSchemaRegistry::Instance(), options);
+}
+
+void RunReshapeShapeInfTest(const char* modelStr, TensorShapeProto& expectedShape) {
+  ModelProto model;
+  ParseAndInfer(model, modelStr);
 
   const auto inferredShape = model.graph().output(0).type().tensor_type().shape();
   EXPECT_TRUE(inferredShape.dim_size() == expectedShape.dim_size());
@@ -620,5 +624,37 @@ TEST(ShapeInferenceTest, CheckShapesAndTypesTest) {
 #endif
 }
 
+TEST(ShapeInferenceTest, CustomOpTest) {
+  const char* modelStr = R"ONNX(
+<ir_version: 8,  opset_import: ["" : 15, "custom.domain" : 1]>
+agraph (float[256, 768, 3] x) => (z1, z2)
+{
+    z1 = custom.domain.CustomOp (x)
+    # Inference cannot determine the type/shape of z1
+    z2 = Abs(x)
+    # Inference SHOULD determine the type/shape of z2 (same as that of x)
+}
+)ONNX";
+
+  ModelProto model;
+  ParseAndInfer(model, modelStr);
+
+  auto& z1_value_info = model.graph().output(0);
+  // Check no inferred type for z1 (It's a quirk of the implementation that it
+  // has a dummy TypeProto, but it should have no values filled in.)
+  ASSERT_TRUE(z1_value_info.has_type());
+  ASSERT_FALSE(z1_value_info.type().has_tensor_type());
+
+  // Check inferred type for z2:
+  auto& z2_value_info = model.graph().output(1);
+  ASSERT_TRUE(z2_value_info.has_type());
+  ASSERT_TRUE(z2_value_info.type().has_tensor_type());
+  EXPECT_EQ(z2_value_info.type().tensor_type().elem_type(), TensorProto_DataType_FLOAT);
+  EXPECT_EQ(z2_value_info.type().tensor_type().shape().dim_size(), 3);
+  EXPECT_EQ(z2_value_info.type().tensor_type().shape().dim(0).dim_value(), 256);
+  EXPECT_EQ(z2_value_info.type().tensor_type().shape().dim(1).dim_value(), 768);
+  EXPECT_EQ(z2_value_info.type().tensor_type().shape().dim(2).dim_value(), 3);
+}
+
 } // namespace Test
 } // namespace ONNX_NAMESPACE