Requirements
- The project was implemented and tested in Python 3.5 and Pytorch 0.4. The higher versions should work after minor modification.
- Other common modules like numpy, pandas and seaborn for visualization.
- NVIDIA GPU and cuDNN are required to have fast speeds. For now, CUDA 8.0 with cuDNN 6.0.20 has been tested. The other versions should be working.
Datasets
Our proposed Chinese Character dataset is accessible on link
Implementation details
data preparation
build train/validation/test sets,
1-make_chinese1_list.py
2-make_letter_list.py
3-make_tiny_letter_list.py
training
4-train_capital_letter_resnet20.py
5-train_chinese1_resnet20.py
6-train_tiny_letter_resnet20.py
explanation generation
7-FARCE_capital_letter.py
8-FARCE_chinese.py
9-FARCE_mnist.py
Time and Space
All experiments were run on NVIDIA TITAN Xp
| model | #GPUs | train time |
|---|---|---|
| train_mnist_resnet20 | 1 | ~10min |
| train_capital_letter_resnet20 | 1 | ~7min |
| train_chinese1_resnet20 | 1 | ~10min |
| FARCE_mnist | 1 | ~20min |
| FARCE_capital_letter | 2 | ~20min |
| FARCE_chinese | 1 | ~20min |
