README.md

Neural Activation Coding

This repository contains the code for the paper "Unsupervised Representation Learning via Neural Activation Coding" published on ICML 2021.

Requirements

First install PyTorch. The code is tested on PyTorch 1.7.1.

• PyTorch

Then run

pip install -r requirements.txt

Linear Classification

To train a ResNet-50 model on CIFAR-10

python run.py --objective=nac --optimizer=lars --lr=3.0 --lr_warmup=10 batch_size=1000 epochs=1000 --weight_decay=1e-6 --flip=0.1

We used 4 TITAN RTX GPUs in our experiments.

Deep Hashing

To train a VGG-16 model on the subset of CIFAR-10

python run_hash.py --objective=nac --optimizer=lars --lr=3.0 --lr_warmup=100 batch_size=1000 epochs=2000 --weight_decay=1e-6 --flip=0.4

Acknowledgements

This repository is based on the SimCLR implementation of leftthomas