const std::vector<std::string> &signature_keys,
    const std::unordered_set<std::string> &tags,
    const QuantizationOptions &quantization_options,
    const absl::flat_hash_map<std::string, SignatureDef> &signature_def_map,
    const PyFunctionLibrary &py_function_library,
    const absl::flat_hash_map<std::string, RepresentativeDatasetFile>
        &representative_dataset_file_map_serialized) {

  // Builds and returns list of tfl.SignatureDef sections in the model.
  std::optional<VectorBufferOffset<BufferOffset<tflite::SignatureDef>>>
  CreateSignatureDefs(const std::vector<SignatureDefData>& signature_defs);

  // Returns list of offsets for the passed 'items' in TensorMap structure
  // inside the flatbuffer.
  // 'items' is a map from tensor name in signatureDef to tensor name in

    fbb_.AddOffset(SignatureDef::VT_INPUTS, inputs);
  }
  void add_outputs(::flatbuffers::Offset<::flatbuffers::Vector<::flatbuffers::Offset<tflite::TensorMap>>> outputs) {
    fbb_.AddOffset(SignatureDef::VT_OUTPUTS, outputs);
  }
  void add_signature_key(::flatbuffers::Offset<::flatbuffers::String> signature_key) {
    fbb_.AddOffset(SignatureDef::VT_SIGNATURE_KEY, signature_key);
  }

  // Find the FuncOp which corresponds to current SignatureDef.
  mlir::SymbolTable sub_symbol_table(*sub_module);
  auto func_op = sub_symbol_table.lookup<mlir::func::FuncOp>(sig_def_key);
  TF_RET_CHECK(func_op)
      << "Graphdef importer should have created a function named "
      << sig_def_key << ".";

  // Use unique SignatureDef key as exported name.
  func_op->setAttr(kTfSavedModelExportedNamesAttr,

    *   Add 5D support to `SLICE` op.
    *   TFLite Supports SingatureDef:
        *   TFLiteConverter exports models with SignatureDef
        *   Interpreter supports getting a list of signatures and getting
            callable function for a given signaturedef.
    *   Add int8 support for `ReshapeV2`.
    *   Add experimental support for optimization with sparsity.