Installation Guide¶
DGL-KE works with both Linux and macOS, and it requires Python version 3.5 or later (Python 3.4 or earlier is not tested). DGL-KE can run on both pytorch and mxnet, please refer the following pages to install pytorch or mxnet.
Install DGL¶
DGL-KE is implemented on DGL. You can install DGL using pip:
pip install dgl
or you can install DGL from source:
git clone --recursive https://github.com/dmlc/dgl.git
cd dgl
mkdir build
cd build
cmake ../
make -j4
Install DGL-KE¶
The fastest way to install DGL-KE is by using pip:
pip 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:
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 --test -adv \
--regularization_coef 1.00E-09 --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 can see the following output at the end of the training:
training takes 37.735950231552124 seconds
-------------- Test result --------------
Test average MRR : 0.47615999491724303
Test average MR : 58.97734929153053
Test average HITS@1 : 0.28428501295051717
Test average HITS@3 : 0.6277276497773865
Test average HITS@10 : 0.775862944592101
-----------------------------------------
testing takes 110.887 seconds