CreateTmpDir());

  std::string calibration_data_dir =
      config.calibration_options().calibration_data_dir();
  if (calibration_data_dir.empty()) {
    TF_ASSIGN_OR_RETURN(calibration_data_dir, CreateTmpDir());
  }

  TF_RETURN_IF_ERROR(ExportToSavedModel(
      module_op, calibration_data_dir,
      config.calibration_options().force_regenerate_calibration_data(),

std::unique_ptr<OperationPass<ModuleOp>>
CreateInsertCalibrationStatisticsSaverPass(
    StringRef calibration_data_dir,
    const std::vector<std::string>& aggregator_ops_to_ignore) {
  InsertCalibrationStatisticsSaverPassOptions options = {
      .aggregator_ops_to_ignore_ = aggregator_ops_to_ignore,
      .calibration_data_dir_ = calibration_data_dir.str(),
  };
  return std::make_unique<InsertCalibrationStatisticsSaverPass>(options);
}

// Reads the calibration statistics from the given directory.
absl::StatusOr<CalibrationStatisticsFlatMap> ReadStatistics(
    absl::string_view calibration_data_dir) {
  TF_ASSIGN_OR_RETURN(std::vector<std::string> statistics_files,
                      io::ListDirectory(calibration_data_dir));

  CalibrationStatisticsFlatMap statistics_map;
  for (const std::string& statistics_file : statistics_files) {
    TF_ASSIGN_OR_RETURN(

  }
  mlir::OwningOpRef<mlir::ModuleOp> module_ref = std::move(module).value();

  std::string calibration_data_dir =
      quantization_options.calibration_options().calibration_data_dir();
  if (calibration_data_dir.empty()) {
    TF_ASSIGN_OR_RETURN(calibration_data_dir, CreateTmpDir());
  }

  TF_ASSIGN_OR_RETURN(ExportedModel calibration_exported_model,

// Reads the calibration statistics from the given directory.
absl::StatusOr<absl::flat_hash_map<
    std::string, tensorflow::calibrator::CalibrationStatistics>>
ReadStatistics(absl::string_view calibration_data_dir);

// Adds calibrated min / max values to CustomAggregator nodes in `graph_def`.
// The min and max values will be added to the "min" and "max" attributes,

  // representative dataset. Returns a failure status if the export fails.
  absl::Status ExportToSavedModel(ModuleOp module_op,
                                  absl::string_view calibration_data_dir,
                                  bool force_regenerate_calibration_data,
                                  absl::string_view dst_saved_model_path);

// Creates a pass that inserts CalibrationStatisticsSaverOp.
std::unique_ptr<OperationPass<ModuleOp>>
CreateInsertCalibrationStatisticsSaverPass(
    StringRef calibration_data_dir,
    const std::vector<std::string>& aggregator_ops_to_ignore);

// Adds generated pass default constructors or options definitions.
#define GEN_PASS_DECL
// Adds generated pass registration functions.

  repeated RepresentativeDatasetConfig representative_datasets = 3;

  // The path to save calibration statistics data. If not set, use a temporary
  // directory.
  string calibration_data_dir = 4;

  // Whether to reuse the existing calibration data in `calibration_data_dir`.
  // Default to False.
  bool force_regenerate_calibration_data = 5;
}

// Quantization configuration for StableHLO Quantizer. This is the primary

        calibration_options=qc.CalibrationOptions(
            calibration_method=_CalibrationMethod.CALIBRATION_METHOD_MIN_MAX,
            calibration_data_dir=calibration_data_dir,
        ),
    )

    # Run quantization the first time, calibration is expected to be run.
    with self.assertLogs(level='INFO') as info_logs:
      quantization.quantize_saved_model(

      )

    if not calib_opts.calibration_parameters.num_bins:
      calib_opts.calibration_parameters.num_bins = 512

  if calib_opts.calibration_data_dir:
    save_model.create_empty_output_dir(
        calib_opts.calibration_data_dir,
        overwrite=calib_opts.force_regenerate_calibration_data,
    )


def _populate_quantization_options_default_values(