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### Current progress:
- General
- [x] Random color distortion (from SimCLR)
- [x] Random Gaussian blur (from SimCLR)
- [x] Random multi-crop (from SwAV)
- [x] InfoNCE loss
- [ ] Momentum encoder
- [ ] Selective Kernel (SK) convolution layer (used in SimCLR v2)
- [x] LARS optimizer
- [x] Consine annealing with linear warmup scheduler
- [x] Linear scheduler (for torch<=1.9)
- [x] CSV logger
- [x] TensorBoard logger
- [x] Checkpoint saving and restoring
- [x] Command line parameter parser
- [x] YAML parameter parser
- [x] PyTorch workflow encapsulation
- [x] Dedicated evaluation script
- [ ] Detailed readme file
- [ ] Data Parallel
- [ ] Distributed Data Parallel
- [ ] Global batch normalization
- [ ] Shuffling batch normalization
- Supervised baseline
- [x] ResNet
- [ ] ViT
- [x] CIFAR-10
- [x] CIFAR-100
- [x] ImageNet-1k
- Self-supervised baseline
- [x] SimCLR (contrastive, ResNet)
- [ ] MoCo v2 (contrastive, ResNet)
- [ ] MoCo v3 (contrastive, ViT)
- [ ] BYOL (non-contrastive, ResNet)
- [ ] DINO (self-distillation, ViT)
To be continued ...
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