Densely Connected Convolutional Network implementation by Chainer
Implementation by Chainer. Original paper is Densely Connected Convolutional Network.
Requirements
-
python 2.7
-
Chainer 1.19.0+ (Neural network framework)
Start training
For example, run,
python train.py --gpus 0 --batchsize 64 --dataset cifar10 --lr 0.1 --depth 100 --growth_rate 24 --split_size 4
Show possible options
python train.py --help
Sample results
- Cifar-10 (batchsize=64, depth=100, growth_rate=24, with data augmentation)
Original paper reported 3.74% validation error under the same conditions.
- Cifar-100 (batchsize=64, depth=100, growth_rate=24, with data augmentation)
Original paper reported 19.25% validation error under the same conditions.