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DenseNet

This repository is pytorch implementation of DenseNet.

Requirments

  • python >= 3.8
  • pytorch >= 1.4
  • torchvision >= 0.5
  • pandas >= 1.0

How to use

You can train DenseNet by following command.

python run.py

Training results are put in work/* (* is setting name).
When you want to train DenseNet with different hyper parameters, edit setting.yml and run bellow.

# * means setting name, default is cifar10+BC_k12.
python run.py -S *

License

This repository is MIT-Licensed.

Original Paper

G.Huang, Z.Liu, L.van der Maaten, K.Q.Weinberger. Densely Connected Convolutional Networks. IEEE Conference on Pattern Recognition and Computer Vision (CVPR), 2016.