Skip Constant Folding for ops producing an optional type output

onnxruntime/core/optimizer/constant_folding.cc

@@ -196,11 +196,11 @@ Status ConstantFolding::ApplyImpl(Graph& graph, bool& modified, int graph_level,
       ORT_ENFORCE(fetches.size() == node->OutputDefs().size());
       converted_to_constant = true;
       for (size_t fetch_idx = 0; fetch_idx < fetches.size(); ++fetch_idx) {
-        OrtValue& ort_value = fetches[fetch_idx];
+        const auto& constant_arg_out = *node->OutputDefs()[fetch_idx];
         // XXX: Add support for SparseTensors outputs when we have sparse outputs
-        if (!ort_value.IsTensor()) {
-          LOGS(logger, WARNING) << "Unsupported output type of " << ort_value.Type()
-                                << ". Can't constant fold " << node->OpType() << " node '" << node->Name() << "'";
+        if (!utils::HasTensorType(*constant_arg_out.TypeAsProto())) {
+          LOGS(logger, INFO) << "Unsupported output type of " << constant_arg_out.Type()
+                             << ". Can't constant fold " << node->OpType() << " node '" << node->Name() << "'";
           converted_to_constant = false;
           break;
         }

onnxruntime/core/providers/cpu/optional/optional_ops.cc

@@ -118,7 +118,11 @@ Status Optional::Compute(OpKernelContext* ctx) const {
 
   } else {  // No input was provided - we use the type proto to construct the output OrtValue
 
-    CheckValidTypeProto(*type_proto_);
+    if (!CheckValidTypeProto(*type_proto_)) {
+      return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT,
+                             "The TypeProto attribute in the Optional op ",
+                             "can only be of type(tensor) or (seq(tensor))");
+    }
 
     // type is either Tensor or TensorSeq (we have validated this already in CheckValidTypeProto())
     if (type_proto_->has_tensor_type()) {

onnxruntime/test/shared_lib/test_inference.cc

@@ -182,6 +182,7 @@ static constexpr PATH_TYPE VARIED_INPUT_CUSTOM_OP_MODEL_URI_2 = TSTR("testdata/f
 static constexpr PATH_TYPE OPTIONAL_INPUT_OUTPUT_CUSTOM_OP_MODEL_URI = TSTR("testdata/foo_bar_1.onnx");
 static constexpr PATH_TYPE OPTIONAL_INPUT_OUTPUT_CUSTOM_OP_MODEL_URI_2 = TSTR("testdata/foo_bar_2.onnx");
 static constexpr PATH_TYPE CUSTOM_OP_MODEL_WITH_ATTRIBUTES_URI = TSTR("testdata/foo_bar_3.onnx");
+static constexpr PATH_TYPE OPTIONAL_TYPE_GH_11717_MODEL = TSTR("testdata/gh_issue_11717.onnx");
 #if !defined(DISABLE_SPARSE_TENSORS)
 static constexpr PATH_TYPE SPARSE_OUTPUT_MODEL_URI = TSTR("testdata/sparse_initializer_as_output.onnx");
 #ifndef DISABLE_CONTRIB_OPS
@@ -2164,3 +2165,13 @@ TEST(CApiTest, TestCudaMemcpyToHostWithSequenceTensors) {
 }
 
 #endif
+
+#if !defined(DISABLE_OPTIONAL_TYPE)
+TEST(CApiTest, GH_11717) {
+  const auto* model_path = OPTIONAL_TYPE_GH_11717_MODEL;
+  Ort::SessionOptions session_options{};
+  // Just check if the model loads fine without a segmentation fault
+  // in the default CPU EP
+  EXPECT_NO_THROW(Ort::Session session(*ort_env, model_path, session_options));
+}
+#endif