For python 3 and above. This is a toy implementation and should be treated as so.
The LINE algorithm was proposed in 2015 by Jian Tang.
This is a PyTorch implementation, which can be trained on a GPU - following your hardware. At the cost of speed, it also is trainable on CPU.
It is recommended to run the model within a virtualenv.
Beforehand, install the required dependencies:
$ (env) pip install -r requirements.txt
Run:
python ./train.py -g ./data/erdosrenyi.edgelist -save ./model.pt -lossdata ./loss.pkl -epochs 10
Available hyperparameters are:
--order: Order 1 or 2 for the LINE algorithm.--negativepower: Power used for raising the nodes out-degree distribution.--negsamplesize: number of negative examples used. Defaults to 5.--batchsize: batchsize during training.--epochs: Number of epochs for training.--learning_rate: Learning rate aggressiveness.