- Python >= 3.6
- PyTorch >= 1.0.1
- torchvision
- tensorboardX
- YACS
$ python train.py model.block_type basic model.depth 110 run.outdir results
$ python train.py model.block_type basic model.depth 110 model.remove_first_relu True model.add_last_bn True run.outdir results
| Model | Test Error (median of 3 runs) | Test Error (in paper) | Training Time |
|---|---|---|---|
| ResNet-preact-110 | 6.47 | 6.37 (median of 5 runs) | 3h05m |
| ResNet-preact-164 bottleneck | 5.90 | 5.46 (median of 5 runs) | 4h01m |
- He, Kaiming, et al. "Deep residual learning for image recognition." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016. arXiv:1512.03385
- He, Kaiming, et al. "Identity mappings in deep residual networks." European Conference on Computer Vision. Springer International Publishing, 2016. arXiv:1603.05027, Torch implementation