Comments (3)
JeffWang987
commented on September 16, 2024
It is strange that using bs=4@2GPU produces worse results than bs=2@4GPU. Here are some suggestions to deal with the problem:
(1) Use sync_bn (torch.nn.SyncBatchNorm.convert_sync_batchnorm).
(2) Carefully tune the LR, our training strategy may not work for bs=4@2GPU.
(3) Check the torch/cuda version.
And for the highly overconfidence issue, I will investigate later (Currently I'm preparing other DDLs).
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ThanTT
commented on September 16, 2024
@alexrich021 Hi, i want to know have you solved the highly overconfidence problem? I meet a similar situation with you.
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ToscanaGoGithub
commented on September 16, 2024
@ThanTT @alexrich021 Hi, i want to know have you solved the highly overconfidence problem? I meet a similar situation with you.
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Related Issues (20)
- LICENSE HOT 1
- question about pretrained model HOT 2
- Where is the script for evaluation on tt?
- Multi-scale camera projection matrices
- Rectified_raw cannot be downloaded
- whether parameters other than images are required？ HOT 1
- Is DeformConvPack necessary when I train? HOT 1
- ValueError: cannot select an axis to squeeze out which has size not equal to one
- Training jammed on epoch 1 HOT 1
- Why Epipolar ?
- Are DTU results reported in the paper trained on 640 or 1280? HOT 4
- Test only generate 4 ply files
- RUN train_mvs4.py HOT 1
- Is there any other way to download the dataset? HOT 3
- Fine tuning on other datasets
- Potential for Stereo Matching？ HOT 1
- A qustion about mono depth HOT 2
- The output .ply. Could you explain what are they ? HOT 1
- question about test_mvs4.py
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