why `pred.exp()`?

[SauceCat]

Thanks for the nice implementation :cat: :100:, I have a small question:

https://github.com/chenjun2hao/DDRNet.pytorch/blob/bc0e193e87ead839dbc715c48e6bfb059cf21b27/lib/datasets/base_dataset.py#L222 Why pred.exp() in inference? The real scores should be softmax(pred, dim=1) right? Just wonder what is the usage of adding exp() here, is it for visualization?