803d7e1fc61536c846c811bdee158bd21db36779,models/Pointnet2Cls.py,,,#,92

Before Change

if __name__ == "__main__":
    from torch.autograd import Variable
    model = PointnetCls()
    data = Variable(torch.randn(2, 10, 3))
    print(model(data))

After Change

    model_fn = model_fn_decorator(nn.CrossEntropyLoss())
    for _ in range(20):
        optimizer.zero_grad()
        _, loss, _ = model_fn(model, (inputs, labels))
        loss.backward()
        print(loss.data[0])
        optimizer.step()

Instances