diff --git a/onnxruntime/core/framework/tensorprotoutils.cc b/onnxruntime/core/framework/tensorprotoutils.cc
index cbe635e60b..6dee78fb24 100644
--- a/onnxruntime/core/framework/tensorprotoutils.cc
+++ b/onnxruntime/core/framework/tensorprotoutils.cc
@@ -518,8 +518,7 @@ ONNXTensorElementDataType GetTensorElementType(const ONNX_NAMESPACE::TensorProto
   return CApiElementTypeFromProtoType(tensor_proto.data_type());
 }
 
-ONNX_NAMESPACE::TensorProto TensorToTensorProto(const Tensor& tensor, const std::string& tensor_proto_name,
-                                                const ONNX_NAMESPACE::TypeProto& tensor_proto_type) {
+ONNX_NAMESPACE::TensorProto TensorToTensorProto(const Tensor& tensor, const std::string& tensor_proto_name) {
   // Given we are using the raw_data field in the protobuf, this will work only for little-endian format.
   ORT_ENFORCE(endian::native == endian::little);
 
@@ -532,12 +531,17 @@ ONNX_NAMESPACE::TensorProto TensorToTensorProto(const Tensor& tensor, const std:
     tensor_proto.add_dims(dim);
   }
 
-  // TODO Once utils::GetTensorProtoType supports all data types, you can get the tensor proto type from the tensor,
-  // as follows (which will allow us to get rid of the tensor_proto_type argument).
-  //tensor_proto.set_data_type(utils::GetTensorProtoType(tensor));
-
-  tensor_proto.set_data_type(tensor_proto_type.tensor_type().elem_type());
-  tensor_proto.set_raw_data(tensor.DataRaw(), tensor.SizeInBytes());
+  tensor_proto.set_data_type(tensor.GetElementType());
+  if (tensor.IsDataTypeString()) {
+    auto* mutable_string_data = tensor_proto.mutable_string_data();
+    auto f = tensor.Data<std::string>();
+    auto end = f + tensor.Shape().Size();
+    for (; f < end; ++f) {
+      *mutable_string_data->Add() = *f;
+    }
+  } else {
+    tensor_proto.set_raw_data(tensor.DataRaw(), tensor.SizeInBytes());
+  }
 
   return tensor_proto;
 }
diff --git a/onnxruntime/core/framework/tensorprotoutils.h b/onnxruntime/core/framework/tensorprotoutils.h
index 7e6fd72506..48b8742624 100644
--- a/onnxruntime/core/framework/tensorprotoutils.h
+++ b/onnxruntime/core/framework/tensorprotoutils.h
@@ -38,14 +38,11 @@ common::Status TensorProtoToMLValue(const Env& env, const ORTCHAR_T* tensor_prot
 /** Creates a TensorProto from a Tensor.
     @param[in] tensor the Tensor whose data and shape will be used to create the TensorProto.
     @param[in] tensor_proto_name the name of the TensorProto.
-    @param[in] tensor_proto_type the type of the TensorProto.
     @return the TensorProto. 
     
     Note: Method currently requires that data is in little-endian format.
-    TODO Once the GetTensorProtoType supports all data types, we can remove the tensor_proto_type parameter and 
-    instead get the type from the tensor. */
-ONNX_NAMESPACE::TensorProto TensorToTensorProto(const Tensor& tensor, const std::string& tensor_proto_name,
-                                                const ONNX_NAMESPACE::TypeProto& tensor_proto_type);
+ */
+ONNX_NAMESPACE::TensorProto TensorToTensorProto(const Tensor& tensor, const std::string& tensor_proto_name);
 
 ONNXTensorElementDataType CApiElementTypeFromProtoType(int type);
 ONNXTensorElementDataType GetTensorElementType(const ONNX_NAMESPACE::TensorProto& tensor_proto);
diff --git a/onnxruntime/core/optimizer/constant_folding.cc b/onnxruntime/core/optimizer/constant_folding.cc
index d00c1759ce..5bcd688385 100644
--- a/onnxruntime/core/optimizer/constant_folding.cc
+++ b/onnxruntime/core/optimizer/constant_folding.cc
@@ -94,7 +94,7 @@ Status ConstantFolding::ApplyImpl(Graph& graph, bool& modified, int graph_level,
       ORT_ENFORCE(ort_value.IsTensor());
       const Tensor& out_tensor = ort_value.Get<Tensor>();
       ONNX_NAMESPACE::TensorProto out_tensorproto =
-          utils::TensorToTensorProto(out_tensor, constant_arg_out->Name(), *constant_arg_out->TypeAsProto());
+          utils::TensorToTensorProto(out_tensor, constant_arg_out->Name());
 
       graph.AddInitializedTensor(out_tensorproto);
     }