start.rst

Start With pykg2vec

In order to install pykg2vec, you will need setup the following libraries:

• python >=3.6 (recommended)
• pytorch>= 1.5

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All dependent packages (requirements.txt) will be installed automatically when setting up pykg2vec.

• networkx>=2.2
• setuptools>=40.8.0
• matplotlib>=3.0.3
• numpy>=1.16.2
• seaborn>=0.9.0
• scikit_learn>=0.20.3
• hyperopt>=0.1.2
• progressbar2>=3.39.3
• pathlib>=1.0.1
• pandas>=0.24.2

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Installation Guide

1. Setup a Virtual Environment: we encourage you to use anaconda to work with pykg2vec:

   (base) $ conda create --name pykg2vec python=3.6
   (base) $ conda activate pykg2vec

2. Setup Pytorch: we encourage to use pytorch with GPU support for good training performance. However, a CPU version also runs. The following sample commands are for setting up pytorch:

   # if you have a GPU with CUDA 10.1 installed
   (pykg2vec) $ conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
   # or cpu-only
   (pykg2vec) $ conda install pytorch torchvision cpuonly -c pytorch

3. Setup Pykg2vec:

   (pykg2vec) $ git clone https://github.com/Sujit-O/pykg2vec.git
   (pykg2vec) $ cd pykg2vec
   (pykg2vec) $ python setup.py install

4. Validate the Installation: try the examples under /examples folder. :

   # train TransE using benchmark dataset fb15k (use pykg2vec-train.exe on Windows)
   (pykg2vec) $ pykg2vec-train -mn transe -ds fb15k