/agnostic-equilibrium-propagation

Primary LanguagePython

Agnostic Equilibrium Propagation

This repository contains code to produce simulations of Agnostic Equilibrium Propagation on Hopfield-like networks.

The code uses PyTorch, TorchVision and TensorBoard.

Getting started

  • Download the code from GitHub:
git clone https://github.com/bscellier/agnostic-equilibrium-propagation
cd agnostic-equilibrium-propagation
  • To train a Hopfield-like network (with 1 hidden layer by default) on MNIST with Agnostic Eqprop, run the command:
python run.py --dataset='MNIST' --architecture='1h' --method='centered' --verbose
  • To run Tensorboard, use the command:
tensorboard --logdir=runs/MNIST/1h/
  • Once the model is trained, start the GUI by running the command:
python run_gui.py --dataset='MNIST' --architecture='1h'