message: MLPerf logging fixes
diff: @@ -1811,8 +1811,7 @@ void Model::fit(int num_epochs, int max_iter, int display, int eval_interval, in
  HCTR_LOG_S(INFO, ROOT) << "Evaluation source file: " << reader_params_.eval_source << std::endl;
  if (solver_.perf_logging) {
  - HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "train_epoch_start",
  - 0); // just 1 epoch. perf logger
  + HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "epoch_start", 0);
  }
  this->start_data_reading();
  @@ -1883,8 +1882,6 @@ void Model::fit(int num_epochs, int max_iter, int display, int eval_interval, in
  size_t train_samples =
  static_cast<size_t>(iter + 1) * static_cast<size_t>(solver_.batchsize);
  - std::string epoch_num_str = std::to_string(float(iter) / max_iter);
  -
  HCTR_LOG_S(INFO, WORLD)
  << "Hit target accuracy AUC " << auc_threshold << " at " << iter << "/"
  << max_iter << " iterations with batchsize " << solver_.batchsize << " in "
  @@ -1893,9 +1890,9 @@ void Model::fit(int num_epochs, int max_iter, int display, int eval_interval, in
  << (float(iter) * solver_.batchsize / timer.elapsedSeconds()) << " records/s."
  << std::endl;
  - HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "eval_stop" + epoch_num_str);
  + HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "eval_stop", float(iter) / max_iter);
  - HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "train_epoch_end", 1);
  + HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "epoch_stop", 1);
  HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "run_stop");
  HCTR_LOG_ARGS(timer_log.elapsedMilliseconds(), "train_samples", train_samples);
  