This code belongs to "VAE-Stega: Linguistic Steganography Based on Variational Auto-Encoder".
- python 3
- tensorflow = 1.12
- zhusuan = 0.3.1
- gensim
- Download our corpus file movie
or tweet and put it in
./data/ - Modify
./utils/parameters.pyto adjust the hyperparameters
- Download our corpus file movie
or tweet and put it in
./data/ - Download "BERT-Base, Uncased model" (bert) and put it in
./pre/uncased_L-12_H-768_A-12 - Modify
./utils/parameters_bert.pyto adjust the hyperparameters
- VAE_LSTM-LSTM model
python vae_lstm-lstm.py- VAE_BERT-LSTM model
python vae_bert-lstm.pyThis code is based on yiyang92's vae_for_text, google-research's bert and huwenxianglyy's bert-use-demo. Many thanks!