lucidrains / lucidrains/vector-quantize-pytorch
about BSQ Loss
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 4k
- Forks
- 338
- PR merge metrics
- No merged PRs in 30d
Description
hi, I'm trying to use BSQ to train my model, and the curve of BSQ loss as follows. Is normal? I wonder that why the loss is negative at the beginning and then increases gradually? Looking forward to your reply!
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the BSQ loss implementation and reproducing the training curve shown in the attachment. Check whether the loss definition permits negative values and whether its increase is expected; done means a documented explanation or a minimal reproduction if the behavior is incorrect.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100