Installation Guide

This topic explains how to install DGL-KE. We recommend installing DGL-KE by using pip and from the source.

System requirements

DGL-KE works with the following operating systems:

• Ubuntu 16.04 or higher version
• macOS x

DGL-KE requires Python version 3.5 or later. Python 3.4 or earlier is not tested. Python 2 support is coming.

DGL-KE supports multiple tensor libraries as backends, e.g., PyTorch and MXNet. For requirements on backends and how to select one, see Working with different backends. As a demo, we install Pytorch using pip:

sudo pip3 install torch

Install DGL

DGL-KE is implemented on the top of DGL (0.4.3 version). You can install DGL using pip:

sudo pip3 install dgl==0.4.3

Install DGL-KE

After installing DGL, you can install DGL-KE. The fastest way to install DGL-KE is by using pip:

sudo pip3 install dglke

or you can install DGL-KE from source:

git clone https://github.com/awslabs/dgl-ke.git
cd dgl-ke/python
sudo python3 setup.py install

Have a Quick Test

Once you install DGL-KE successfully, you can test it by the following command:

# create a new workspace
mkdir my_task && cd my_task
# Train transE model on FB15k dataset
DGLBACKEND=pytorch dglke_train --model_name TransE_l2 --dataset FB15k --batch_size 1000 \
--neg_sample_size 200 --hidden_dim 400 --gamma 19.9 --lr 0.25 --max_step 500 --log_interval 100 \
--batch_size_eval 16 -adv --regularization_coef 1.00E-09 --test --num_thread 1 --num_proc 8

This command will download the FB15k dataset, train the transE model on that, and save the trained embeddings into the file. You could see the following output at the end:

-------------- Test result --------------
Test average MRR : 0.47221913961451095
Test average MR : 58.68289854581774
Test average HITS@1 : 0.2784276548560207
Test average HITS@3 : 0.6244265375564998
Test average HITS@10 : 0.7726295474936941
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