The official JAX implementation of Action-Angle Networks from our paper "Learning Integrable Dynamics with Action-Angle Networks".
Clone the repository:
git clone https://github.com/ameya98/ActionAngleNetworks.git
cd ActionAngleNetworks
Create and activate a virtual environment:
python -m venv .venv && source .venv/bin/activate
Install dependencies with:
pip install --upgrade pip && pip install -r requirements.txt
Start training with a configuration defined under action_angle_networks/configs/
:
python -m action_angle_networks.main --config=action_angle_networks/configs/harmonic_motion/action_angle_flow.py --workdir=./tmp/
Since the configuration is defined using config_flags, you can override hyperparameters. For example, to change the number of training steps and the batch size:
python -m action_angle_networks.main --config=action_angle_networks/configs/harmonic_motion/action_angle_flow.py --workdir=./tmp/ \
--config.num_train_steps=10 --config.batch_size=100
For more extensive changes, you can directly edit the configuration files, and even add your own.
This is a fork of my original implementation here.
Ameya Daigavane