Code for: Distributional Discrepancy: A Metric for Unconditional Text Generation
We suggest you run the platform under Python 3.6+ with following libs:
- tensorflow>=1.12.0
- tensorflow_hub>=0.7.0
- numpy 1.16.4
- scipy 1.3.1
- nltk 3.4.5
- colorama 0.4.1
- CUDA 7.5+ (Suggested for GPU speed up, not compulsory)
Or just type pip install -r requirements.txt
in your terminal.
git clone https://github.com/anonymous1100/Distributional-Discrepancy.git
cd Distributional-Discrepancy
# run with default setting
python main.py
#You can also change the model and data in main.py and then run main.py
data
folder: emnlp_news and image_coco datasetmodels
folder: Training codes for LSTM and GPT-2utils
folder: code for some evaluationexperiments
folder: Experimental resultsexperiments/experiment_name/tmp
folder: Generated samplesexperiments/experiment_name/output
folder: some output filesexperiments/experiment_name/ckpts
folder: Trained modelexperiments/experiment_name/summary
folder: tensorboard record
For any questions, feel free to open an issue via github, or to send me an email at
[email protected]
.