Releases: Westlake-AI/OpenBioSeq
Releases · Westlake-AI/OpenBioSeq
OpenBioSeq Release V0.2.0
Highlight
- Support various popular backbones (ConvNets and ViTs), image datasets, popular mixup methods, and benchmarks for supervised learning. Config files are available.
- Support popular self-supervised methods (e.g., BYOL, MoCo.V3, MAE) on large-scale and small-scale datasets and self-supervised benchmarks (merged from MMSelfSup). Config files are available. Support BERT pre-training method and update config files.
- Support analyzing tools for self-supervised learning (kNN/SVM/linear metrics and t-SNE/UMAP visualization).
- Convenient usage of configs: fast configs generation by 'auto_train.py' and configs inheriting (MMCV).
- Support mixed-precision training (NVIDIA Apex or MMCV Apex).
- Refactor
openbioseq.core
and support Adan optimizer. - Add demo of gRNA inference.
Bug Fixes
- Done code refactoring follows MMSelfSup and MMClassification.