5bb1fce991f89f9459efaaaa8763a5d444f9d865,training.py,,train_epoch,#,9

Before Change

        batch_time.update(time.time() - end_time)
        end_time = time.time()

        batch_logger.log({
            "epoch": epoch,
            "batch": i + 1,
            "iter": (epoch - 1) * len(data_loader) + (i + 1),
            "loss": losses.val,
            "acc": accuracies.val,
            "lr": current_lr
        })

        print("Epoch: [{0}][{1}/{2}]\t"
              "Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t"
              "Data {data_time.val:.3f} ({data_time.avg:.3f})\t"

After Change

        batch_time.update(time.time() - end_time)
        end_time = time.time()

        if batch_logger is not None:
            batch_logger.log({
                "epoch": epoch,
                "batch": i + 1,
                "iter": (epoch - 1) * len(data_loader) + (i + 1),
                "loss": losses.val,
                "acc": accuracies.val,
                "lr": current_lr
            })

        print("Epoch: [{0}][{1}/{2}]\t"
              "Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t"
              "Data {data_time.val:.3f} ({data_time.avg:.3f})\t"
              "Loss {loss.val:.4f} ({loss.avg:.4f})\t"

Instances