Multi-Task Learning as a Bargaining Game

Related tags

Deep Learningnash-mtl
Overview

Nash-MTL

Official implementation of "Multi-Task Learning as a Bargaining Game".

Setup environment

conda create -n nashmtl python=3.9.7
conda activate nashmtl
conda install pytorch==1.9.0 torchvision==0.10.0 torchaudio==0.9.0 cudatoolkit=10.2 -c pytorch
conda install pyg -c pyg -c conda-forge

Next -> cd to the unzipped folder i.e. cd RUN -> pip install -e .

QM9 Experiment

To run Nash-MTL:

cd experiments/quantum_chemistry
python trainer.py --method=nashmtl

To train using another MTL method simply replace 'nashmtl' with one of ['cagrad', 'pcgrad', 'mgda', 'ls', 'uw', 'scaleinvls'].

Owner
Aviv Navon
Data Scientist @ Aiola // PhD Student @ BIU
Aviv Navon
GitHub Repository
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