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Relaxed equivariance dynamics

This repository contains the official implementation of our blogpost titled: Effect of equivariance on training dynamics.

Our blogpost has been published at GRaM Workshop @ ICML 2024.

Our extended blogpost can be found here.

Package contributions

To maximize convenience, reproducibility and encourage usage of our modules (models, datasets, tools), we've package some of them separately.

Setup

Make virtual environment and install dependencies:

make setup_env

Source your virtual environment:

source .venv/bin/activate

Local Usage

Reproduce the training results from a given experiment:

python -m src.train experiment=wang2024/rgcnn_triple

SLURM Usage

Pre-requisites

  • ssh into snellius
  • Move into the project root
    cd ~/development/dl2

Train model based on experiment config

Let's say you want to run the experiment at configs/experiment/wang2022/equivariance_test/convnet.yaml. You can make use of the shortcut slurmtrain as follows:

make strain experiment=wang2022/equivariance_test/convnet

If you need to modify anything, the script is at scripts/slurm/train.sh.

Print slurm logs given job id

make slurmcat id=6246500

The logs are stored at scripts/slurm_logs/slurm_output_{id}.out.