f6415170f7f90124e9cdb9ccd37cd867852b7657,train.py,,,#,19

Before Change

os.makedirs(args.save_path, exist_ok=True)

running_loss = 0.0
train_begin = time.time()
for epoch in range(1, model_args.num_epochs + 1):
    for i, batch in enumerate(dataloader):
        optimizer.zero_grad()

After Change

        if i % 100 == 0:
            // print current time, running average, learning rate, iteration, epoch
            print("[{}][Epoch: {:3d}][Iter: {:6d}][Loss: {:6f}][lr: {:7f}]".format(
                datetime.datetime.utcnow() - train_begin, epoch,
                    (epoch - 1) * args.iter_per_epoch + i, running_loss,
                    optimizer.param_groups[0]["lr"]))

Instances