A PyTorch based implementation of Tree-LSTM from Kai Sheng Tai's paper Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks.
- PyTorch Deep learning library
- tqdm: display progress bar
- meowlogtool: a logger that write everything on console to file
- Java >= 8 (for Stanford CoreNLP utilities)
- Python >= 3
First run the script ./fetch_and_preprocess.sh
This downloads the following data:
- Stanford Sentiment Treebank (sentiment classification task)
- Glove word vectors (Common Crawl 840B) -- Warning: this is a 2GB download!
and the following libraries:
python sentiment.py --name <name_of_log_file> --model_name <constituency|dependency> --epochs 10