Code for reproducing Physical Reasoning Using Dynamics-Aware Models. This branch trains models that use the hand crafted loss.
A Conda virtual enviroment is provided contianing all necessary dependencies.
git clone https://github.com/facebookresearch/DynamicsAware
cd DynamicsAware
conda env create -f env.yml
source activate dynamics_aware
# You might need to replace next command with the correct
# command to install pytorch on your system if you are not running linux
# and cuda 10.2
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
pip install -e src/python
To run an experiments locally
cd agents
python python run_sweep_file.py <experiment_file> --base-dir=<basedir> -o -l
Where <experiment_file> is the experiment file to run and <basedir> is the directory where the experiment output should be
stored. For more details see agents
Dynamics-Aware Models is released under the Apache license. See LICENSE for additional details.
If you use DynamicsAware or the baseline results, please cite it
@inproceedings{ahmed2021physical,
title={Physical Reasoning Using Dynamics-Aware Models},
author={Ahmed, Eltayeb and Bakhtin, Anton and van der Maaten, Laurens and Girdhar, Rohit},
booktitle={ICML Workshop},
year={2021}
}