// 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

// Convert the session initializer to a function.
std::unique_ptr<OperationPass<ModuleOp>>
CreateConvertSessionInitializerToFunctionPass();

// Creates forwarding functions for 'exported_names'.
std::unique_ptr<OperationPass<ModuleOp>>
CreateAddFunctionsForExportedNamesPass();

#define GEN_PASS_REGISTRATION
#define GEN_PASS_DECL_DEDUPBOUNDINPUTBINDINGPASS
#define GEN_PASS_DECL_FREEZEASSETSPASS

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

    %cst = arith.constant dense<0.000000e+00> : tensor<5xf32>
    %cst_0 = arith.constant dense<1.0> : tensor<5x384xf32>
    %cst_1 = arith.constant dense<1.0> : tensor<5x384xf32>

    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(

namespace mlir {
namespace tf_saved_model {

// The name of the attribute indicating under what name an object is exported.
inline constexpr StringRef kTfSavedModelExportedNamesAttr =
    "tf_saved_model.exported_names";

// The name of the attribute attached to input arguments or results of a
// function to represent the path which one would use to index into a structured
// value to reach a given tensor.

    %cst = "tf.Const"() {value = dense<2> : tensor<960x960x3x512xi8>} : () -> tensor<960x960x3x512xi8>
    %cst_0 = "tf.Const"() {value = dense<0.00117647066> : tensor<f32>} : () -> tensor<f32>

    %cst = "tf.Const"() {device = "", value = dense<[7.72826624, 8.8264122, 3.64885974]> : tensor<3xf32>} : () -> tensor<3xf32>

  let summary = "Create a trampoline function for each exported name.";
  let description = [{
      This converts
        func.func @foo() attributes {tf_saved_model.exported_names = ["a", "b", "c"]}
      to
        func.func @a() {return @foo_internal()}
        func.func @b() {return @foo_internal()}
        func.func @c() {return @foo_internal()}
        func.func private @foo_internal()

  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()