89f2c2b125815fc11849ae110b4b561de81894d2,examples/text_classification/train.py,,train,#Any#Any#Any#,30

Before Change

            progress = processed_lines / float(num_lines)
            lr = lr_ * (1 - progress)
            // SGD
            for p in model.parameters():
                p.data.add_(p.grad.data * -lr)
                p.grad.detach_()
                p.grad.zero_()
            if processed_lines % 1024:
                sys.stderr.write(
                    "\rProgress: {:3.0f}% lr: {:3.3f} loss: {:3.3f}".format(
                        progress * 100, lr, loss))

After Change

    data = DataLoader(data_, batch_size=batch_size, shuffle=True,
                      collate_fn=generate_batch, num_workers=args.num_workers)
    optimizer = torch.optim.SGD(model.parameters(), lr=lr_)
    scheduler = torch.optim.lr_scheduler.StepLR(optimizer, 1, gamma=args.lr_gamma)
    num_lines = num_epochs * len(data)
    for epoch in range(num_epochs):
        for i, (text, offsets, cls) in enumerate(data):

Instances