Poincaré Embeddings for Learning Hierarchical Representations
Poincaré Embeddings for Learning Hierarchical Representations
PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
Installation
Simply clone this repository via
git clone https://github.com/facebookresearch/poincare-embeddings.git
cd poincare-embeddings
conda env create -f environment.yml
source activate poincare
python setup.py build_ext --inplace
Example: Embedding WordNet Mammals
To embed the transitive closure of the WordNet mammals subtree, first generate the data via
cd wordnet
python transitive_closure.py
This will generate the transitive closure of the full noun hierarchy as well as of the mammals subtree of WordNet.
To embed the mammals subtree in the reconstruction setting (i.e., without missing data), go to the root directory of the project and run
./train-mammals.sh
This shell script includes the appropriate parameter settings for the mammals subtree and saves the trained model as mammals.pth.