Comments (2)
YoelShoshan
commented on September 21, 2024
We don't currently support this feature, and the recommended way is to re-cache all in such case (which is possibly the safest, depending on the case of course).
Feel free to:
- Propose the API change, with usage examples (no actual implementation)
- Create a PR with the desired change (only after 1 was discussed and agreed)
Thanks for the feature suggestion!
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mosheraboh
commented on September 21, 2024
I think that cacher.delete(sample_ids) should do the trick. Do you agree?
It should be very easy to implement.
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Related Issues (20)
- State of the field section missing from the fuse-med-ML paper HOT 2
- Add example to Fuse.dl section in the Fuse-med ML paper HOT 3
- urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] on CICD
- Remove `torchvision` version upper bound
- Add a flag for clearml start function to enable/disable it
- fix `LightningDeprecationWarning` HOT 1
- Fix the installation protocol so it will be compatible with A100 GPU and CCC's CUDA version HOT 2
- Uncollate is not needed and slows down training HOT 1
- Display CI output on Jenkins' console while building
- NDict API change - missing pre-existing features HOT 2
- Update hello_world.ipynb example HOT 3
- Mention in readme that FuseMedML is part of PyTorch ecosystem
- Caching should only be done on rank 0 HOT 1
- Failure in running mutliple GPUs with dp strategy for ehr_transformer HOT 1
- Support pytorch lightning 2.0.0
- backbone resnet and resnet 3d - better pretrained support
- bug in resnet3d following latest change HOT 2
- `TestCrossAttentionTransformerEncoder` randomly fails
- I got “NameError: name 'NDict' is not defined” from ndict.py, how can I fix it HOT 4
- Remove usage of `xmlrunner` package
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