%0  = "tf.Const"() {value = dense<[56, 904]> : tensor<2xi32>} : () -> tensor<2xi32>

      // For example:
      //   "tf_saved_model.session_initializer"() {initializers = [@init_all_tables]} : () -> () // NOLINT
      //   func @init_all_tables() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_init_all_tables"]} { // NOLINT
      //     "tf.NoOp"() {device = ""} : () -> ()
      //     return
      //   }
      // clang-format on

    %cst = stablehlo.constant dense<0.000000e+00>: tensor<10x1024x3xf32>

    const std::string& input_filename, int saved_model_version,
    const std::unordered_set<std::string>& tags,
    absl::Span<const std::string> extra_tf_opdefs,
    absl::Span<std::string> exported_names, const GraphImportConfig& specs,
    bool enable_variable_lifting, mlir::MLIRContext* context,
    std::unique_ptr<tensorflow::SavedModelBundle>* saved_model_bundle);

Status ConvertTFExecutorToStablehloFlatbuffer(

  for (auto globalTensor : module.getOps<tf_saved_model::GlobalTensorOp>()) {
    auto exportedNames = tf_saved_model::GetExportedNames(globalTensor);
    std::string name;
    if (exportedNames.empty()) {
      name = "global_ml_" + globalTensor.getSymName().str();
    } else if (exportedNames.size() == 1) {
      name = exportedNames[0].str();
    } else {
      return globalTensor.emitError()