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()

namespace calibrator {

void CalibrationStatisticsCollectorMinMax::ClearData() {
  // global_min will be updated by std::min(global_min, input_value) so
  // it is initialized with the value numeric_limits<float>::max().
  min_max_statistics_.set_global_min(std::numeric_limits<float>::max());

  // global_max will be updated by std::max(global_max, input_value) so it
  // is initialized with the value numeric_limits<float>::lowest().

// Calibration algorithm's collecting statistics.
// NEXT_ID: 4
message CalibrationStatistics {
  message MinMaxStatistics {
    // global minimum of all sample datasets.
    float global_min = 1;

    // global maximum of all sample datasets.
    float global_max = 2;
  }

  message AverageMinMaxStatistics {
    // sum of batch's minimum in each sample dataset.
    float min_sum = 1;

        calibration_method=_CalibrationMethod.CALIBRATION_METHOD_MIN_MAX
    )
    statistics = calib_stats_pb2.CalibrationStatistics()
    statistics.min_max_statistics.global_min = 1.0
    statistics.min_max_statistics.global_max = 5.0

    min_value, max_value = calibration_algorithm.get_min_max_value(
        statistics, calib_opts
    )
    self.assertAllEqual((min_value, max_value), (1.0, 5.0))