Comments (1)
Hi, thanks for this question. Yes, I think there should be a torch.distributed.barrier()
here. It is interesting that I didn't encounter any errors without this torch.distributed.barrier()
.
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Related Issues (20)
- There is a bit of inconsistency between the code and the paper HOT 1
- Why Test Input Size of self-distillation phase is 1024*2048? instead of 512*1024 as before? HOT 2
- About multi-scale testing? HOT 1
- why don't you set one more label with name "others" for labels in cityscapes which do not exist in GTA5 or Sythia ? HOT 4
- Performance on Cityscapes to Cross-City HOT 3
- Problems when you save soft labels for self distill HOT 2
- Why is self-distill-training better? HOT 1
- Why do you test your distilled model at 2048, 1024 test size ?
- why is the test size different from the train size in the self-distill phase ? HOT 3
- VGG pre-trained model HOT 5
- train custom dataset HOT 5
- Soft labels or hard labels at self distillation training ? HOT 2
- How to implement the CCD in pytorch? HOT 2
- Could not reproduce results for generate_synthia_label.py and the use of its result HOT 2
- why batch_size // 2 ? HOT 1
- Freeze discriminator parameters before performing adversarial loss backward HOT 2
- GTA5 generate_gta5_label_info.py
- Why do you use tgt_soft_label.detach() in Ladv?
- How do you use thresholds in your code? HOT 1
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