cd <Repository Root>/MNIST/
python3 main.py --arch Bin_LeNet
python3 main.py --arch LeNet
cd <Repository Root>/MNIST/
python3 main.py --arch Bin_LeNet --evaluate --pretrained ./models/Bin_LeNet.best.pth # --no_cuda (Use CPU)
python3 main.py --arch LeNet --evaluate --pretrained ./models/LeNet.best.pth # --no_cuda (Use CPU)
Network |
Accuracy |
Size |
LeNet |
99.50% |
1.7 MB |
Bin_LeNet |
99.45% |
102 KB |
cd <Repository Root>/Cifar10/
python3 main.py --arch Bin_VGG16 #(11, 13, 16, 19)
python3 main.py --arch VGG16 #(11, 13, 16, 19)
cd <Repository Root>/Cifar10/
python3 main.py --arch Bin_VGG16 --evaluate --pretrained ./models/Bin_VGG16.best.pth # --no_cuda (Use CPU)
python3 main.py --arch VGG16 --evaluate --pretrained ./models/VGG16.best.pth # --no_cuda (Use CPU)
Network |
Accuracy |
Size |
VGG13 |
92.40% |
37.7 MB |
Bin_VGG13 |
88.74% |
1.3 MB |
VGG16 |
92.29% |
59.0 MB |
Bin_VGG16 |
87.78% |
2.0 MB |
Google Drive
- Ubuntu 16.04
- Python 3.5
- Pytorch 0.3.1
- CUDA 8.0
- gcc 5.4
- NVIDIA GTX 1080
- Intel i5-6500 CPU @ 3.20GHz × 4