pytorch-metric-learning and MagnetLoss-PyTorch

About pytorch-metric-learning

KevinMusgrave/pytorch-metric-learning

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Provides 9 independent modules—including loss functions (TripletMarginLoss, ArcFaceLoss, etc.), hard pair miners, distance metrics, and reducers—that compose into customizable training pipelines. Automatically converts between triplet and pair representations, supports self-supervised learning via augmentation pairs, and includes built-in trainers and evaluation utilities for metric learning workflows. Integrates seamlessly with standard PyTorch training loops and includes pre-built dataset loaders for common benchmarks like CUB-200 and Stanford Online Products.

About MagnetLoss-PyTorch

vithursant/MagnetLoss-PyTorch

PyTorch implementation of a deep metric learning technique called "Magnet Loss" from Facebook AI Research (FAIR) in ICLR 2016.