Comments (1)
We initially tried to use mixed precision, but we also ended up with divergence during training. This problem should not happen with full precision. Also, based on our knowledge, since our work is targeting high resolution results, we must use full precision.
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Related Issues (20)
- Not getting the same quality as the hugging face web demo model HOT 2
- Train with another shape HOT 1
- Unexpected keys in state_dict when trying inference HOT 1
- Model difference between Res2Net50 Backbone and Res2Net50 [DUTS-TR] trained checkpoint HOT 3
- Unable to reproduce models and Increasing validation loss HOT 1
- `base_size` and `stage` parameters are not used for encoder and decoder HOT 6
- unable to load jit model HOT 2
- Some confusion about dynamic_resize HOT 2
- Image mask alignment problem HOT 4
- train custom dataset HOT 2
- Multiple masks area HOT 1
- InSPyReNet for mask refinement? HOT 1
- Error/Warning about get_root_logger and load_checkpoint HOT 7
- Fine tuning HOT 9
- InSPyReNet_SwinB_DIS5K_LR Result Download Failed HOT 1
- HR CustomDataset Finetuning HOT 2
- Is this undertrained HOT 1
- Downloading InSPyReNet models and testing them...
- inspyrenet is the best architecture of image segmentation i've used so far, please keep upgrading
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