performance on deeplab_jpu

[alphaccw]

Hi,
Thank you for the awesome code.
I test the deeplab +jpu without changing anything on 4xgeforce 1080, cuda 9.0, torch 1.0.0
#train
CUDA_VISIBLE_DEVICES=4,5,6,7 python train.py --dataset pcontext --model deeplab --jpu --aux --backbone resnet50 --checkname deeplab_res50_pcontext_deeplabv3
#test
CUDA_VISIBLE_DEVICES=4,5,6,7 python test.py --dataset pcontext --model deeplab --jpu --aux --backbone resnet50 --resume ./runs/pcontext/deeplab/deeplab_res50_pcontext_deeplabv3/model_best.pth.tar --checkname deeplab_res50_pcontext_deeplabv3 --split val --mode testval
The model_best.pth.tar is the same as checkpoint.pth.tar in my case.
Ther performance i get is pixAcc: 0.7868, mIoU: 0.4904. Compare to Table 1, there is 1% drop (50.07 from table 1).

Do I miss sth or this is normal?

Thank you

[wuhuikai]

The training and testing process is the same as ours.