Metric Learning Python Packages

pytorch-metric-learning

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

catalyst

Accelerated deep learning R&D

metric-learn

Metric learning algorithms in Python

tfsim-nightly

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

disent

🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib

finetuner

:dart: Task-oriented embedding tuning for BERT, CLIP, etc.

tensorflow-similarity

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

open-metric-learning

Metric learning and retrieval pipelines, models and zoo.

pylmnn

Large Margin Nearest Neighbors implementation in python

metric-learning-layers

A simple PyTorch package that includes the most common metric learning layers

powerful-benchmarker

A library for ML benchmarking. It's powerful.

quaterion

Blazing fast framework for fine-tuning similarity learning models

tomotwin-cryoet

cryo-ET particle picking by representation and metric learning

ggml-ot

Improve Optimal Transport applications by Global Ground Metric Learning (published at AISTATS2025). This package supports single-cell data in Anndata format and generic array-like data.

scmdml

A multitask deep metric learning-based framework for single cell assignment based on multiple references

tf-metric-learning

Minimalistic TensorFlow2+ deep metric/similarity learning library with loss functions, miners, and utils as embedding projector.

gedml

Generalized Deep Metric Learning.

chesspos

Embedding based chess position search and embedding learning for chess positions

kernelmethods

Foundational library for Kernel methods in pattern analysis and machine learning

wsingular

Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".

pytorchcml

PyTorchCML is a library of PyTorch implementations of matrix factorization (MF) and collaborative metric learning (CML), algorithms used in recommendation systems and data mining.

mtsc

A multitask deep metric learning-based framework for single cell assignment based on multiple references

ssrlib

Framework for unsupervised and self-supervised learning & embeddings analysis

catalyst-pdm

Accelerated deep learning R&D