e6484cd61d31a38f96729a70c1f461fc18b3d8ce,examples/mnist_grid.py,,train,#Any#,97

Before Change

        optimizer.step()

        pred = output.data.max(1)[1]
        correct = pred.eq(target.data).cpu().sum()
        acc = correct / target.size(0)

        print("Epoch:", epoch, "Batch:", batch, "Loss:", loss.data[0],
              "Accuracy:", acc)

After Change

def train(epoch):
    model.train()

    if epoch == 11:
        for param_group in optimizer.param_groups:
            param_group["lr"] = 0.0001

    for batch, (data, target) in enumerate(train_loader):
        data = data.view(data.size(0), -1, 1)
        input = torch.cat([perm_input(img, perm) for img in data], dim=0)

Instances