This is a re-implementation of the following paper:
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks Kai Sheng Tai, Richard Socher, and Christopher Manning.
The provided implementation can achieve a test accuracy of 51.72 which is comparable with the result reported in the original paper: 51.0(±0.5).
The script will download the [SST dataset] (http://nlp.stanford.edu/sentiment/index.html) automatically, and you need to download the GloVe word vectors yourself. For the command line, you can use this.
wget http://nlp.stanford.edu/data/glove.840B.300d.zip
unzip glove.840B.300d.zip
- PyTorch 0.4.1+
- requests
- nltk
pip install torch requests nltk
python3 train.py --gpu 0
On AWS p3.2x instance, it can achieve 3.18s per epoch when setting batch size to 256.