Barlow Twins, a New Benchmarking Module and Updated Documentation

Barlow Twins, a New Benchmarking Module and Updated Documentation

Barlow Twins (@AdrianArnaiz)

An implementation of the Barlow Twins architecture and loss for self-supervised learning is added. The approach measures the cross-correlation matrix between the outputs of two identical networks and making it as similar to the unit matrix as possible.

Thank you @AdrianArnaiz for your contribution

Benchmarking Module

A benchmarking module is added for simpler evaluation of models using kNN callback.

API Updates: Lightly Platform

You can now easily download your datasets from the Lightly Platform using the CLI:

lightly-download token=123 dataset_id=xyz output_dir=store/dataset/here
lightly-download token=123 dataset_id=xyz tag_name=my-tag output_dir=store/tag/here

Minor Updates and Fixes

Updated documentation and docstrings to make working with lightly simpler.
transforms can now be passed directly to the LightlyDataset. Learn more here.
Minor bug fixes and improvements.

Models

• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020