This repository implements the proposed models in the paper https://arxiv.org/abs/1905.03806. It also contains scripts to reproduce the results of the model DeepGLO reported in the paper.
- The repository assumes that you have Pytorch installed with CUDA support. Please follow the instructions at https://pytorch.org/ to install the correct version for your system.
- The other required packages are numpy, scikit-learn, scipy, pandas and matplotlib. Please install these packages before using this package.
- The TCN (LeveledInit) model is implemented in DeepGLO.LocalModel
- The overall model is implemented in DeepGLO.DeepGLO
All the input arguments are commented in the source files and usage instructions can be found in the scripts /run_scripts/run_<dataset>.py.
The datasets can be downloaded by the following commands:
cd datasets
bash download-data.sh
- In order to reproduce the results from the paper in the normalized setting, execute the commands:
python run_scripts/run_<dataset>.py --normalize True
- In order to reproduce the results from the paper in the unnormalized setting, execute the commands:
python run_scripts/run_<dataset>.py --normalize False
Here, dataset can be replaced by the corresponding dataset. For instance for the electricity dataset, the command can be:
python run_scripts/run_electricity.py --normalize False
This repository follows the BSD license.