| [Feature] Support canonical layer training in videoalign
Co-authored-by: chenpeizhe<chenpeizhe1@huawei.com>
# message auto-generated for no-merge-commit merge:
merge master into master
[Feature] Support canonical layer training in videoalign
Created-by: chenpeizhe
Commit-by: chenpeizhe
Merged-by: ascend-robot
Description: ## Motivation
Support qwen2vl canonical model (same as transformers) in videoalign training.
## Modification
Support qwen2vl canonical model (same as transformers) in videoalign training for accuracy mode.
## Self-test (Optional)
If modifications to this PR may cause/fix function/accuracy/performance DTSs/issues, a self-inspection record needs to be attached.
## BC-breaking (Optional)
If there are compatibility issues, such as dependencies on cann/torch_npu versions, they need to be explained in the PR.
## Checklist
**Before PR**:
- [x] The new code needs to comply with the Clean Code specification.
- [x] The PR content is self-checked, and the expression can be clear and the writing standardized
**After PR**:
- [x] CLA has been signed and all committers have signed the CLA in this PR.
- [x] The ci-pipeline is passed, Code Check is passed.
See merge request: Ascend/MindSpeed-MM!1511 | 8 个月前 |
