Ecosystem
Tools

A PyTorch-based knowledge distillation toolkit for natural language processing

A toolbox for adversarial robustness research. It contains modules for generating adversarial examples and defending against attacks.

TorchDrift is a data and concept drift library for PyTorch. It lets you monitor your PyTorch models to see if they operate within spec.

Lightly is a computer vision framework for self-supervised learning.

State-of-the-art Natural Language Processing for PyTorch.

Catalyst helps you write compact, but full-featured deep learning and reinforcement learning pipelines with a few lines of code.

Ignite is a high-level library for training neural networks in PyTorch. It helps with writing compact, but full-featured training loops.

PFRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using PyTorch.

Fast and extensible image augmentation library for different CV tasks like classification, segmentation, object detection and pose estimation.

Captum (“comprehension” in Latin) is an open source, extensible library for model interpretability built on PyTorch.

Stable Baselines3 (SB3) is a set of reliable implementations of reinforcement learning algorithms in PyTorch.

PyTorch Geometric Temporal is a temporal (dynamic) extension library for PyTorch Geometric.

Minimalist Neural Machine Translation toolkit for educational purposes

fastai is a library that simplifies training fast and accurate neural nets using modern best practices.

A framework for elegantly configuring complex applications.

Ray is a fast and simple framework for building and running distributed applications.

ML Prediction, Planning and Simulation for Self-Driving built on PyTorch.

A modular framework for vision & language multimodal research from Facebook AI Research (FAIR).

MONAI provides domain-optimized foundational capabilities for developing healthcare imaging training workflows.

TorchIO is a set of tools to efficiently read, preprocess, sample, augment, and write 3D medical images in deep learning applications written in PyTorch.

BoTorch is a library for Bayesian Optimization. It provides a modular, extensible interface for composing Bayesian optimization primitives.

ParlAI is a unified platform for sharing, training, and evaluating dialog models across many tasks.

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

Polyaxon is a platform for building, training, and monitoring large-scale deep learning applications.

A runtime fault injection tool for PyTorch.

A deep learning library for video understanding research. Hosts various video-focused models, datasets, training pipelines and more.

Hummingbird compiles trained ML models into tensor computation for faster inference.

Flair is a very simple framework for state-of-the-art natural language processing (NLP).

TensorLy is a high level API for tensor methods and deep tensorized neural networks in Python that aims to make tensor learning simple.

Determined is a platform that helps deep learning teams train models more quickly, easily share GPU resources, and effectively collaborate.

Framework for reproducible classification of Alzheimer's Disease

NeMo: a toolkit for conversational AI.

A library for state-of-the-art self-supervised learning

Flexible and powerful tensor operations for readable and reliable code.

The PopTorch interface library is a simple wrapper for running PyTorch programs directly on Graphcore IPUs.

ONNX Runtime is a cross-platform inferencing and training accelerator.

An open source framework for deep learning on satellite and aerial imagery.

Deep Graph Library (DGL) is a Python package built for easy implementation of graph neural network model family, on top of PyTorch and other frameworks.

baal (bayesian active learning) aims to implement active learning using metrics of uncertainty derived from approximations of bayesian posteriors in neural networks.

PySyft is a Python library for encrypted, privacy preserving deep learning.

PyTorch Geometric is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds.

Kornia is a differentiable computer vision library that consists of a set of routines and differentiable modules to solve generic CV problems.

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

Forte is a toolkit for building NLP pipelines featuring composable components, convenient data interfaces, and cross-task interaction.

higher is a library which facilitates the implementation of arbitrarily complex gradient-based meta-learning algorithms and nested optimisation loops with near-vanilla PyTorch.

A generalizable application framework for segmentation, regression, and classification using PyTorch

PyKale is a PyTorch library for multimodal learning and transfer learning with deep learning and dimensionality reduction on graphs, images, texts, and videos.

AllenNLP is an open-source research library built on PyTorch for designing and evaluating deep learning models for NLP.

An open source hyperparameter optimization framework to automate hyperparameter search.

Basic Utilities for PyTorch Natural Language Processing (NLP).

A lightweight declarative PyTorch wrapper for context switching between devices, distributed modes, mixed-precision, and PyTorch extensions.

Train PyTorch models with Differential Privacy

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Machine learning metrics for distributed, scalable PyTorch applications.

AdaptDL is a resource-adaptive deep learning training and scheduling framework.

Poutyne is a Keras-like framework for PyTorch and handles much of the boilerplating code needed to train neural networks.

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

A PyTorch framework for deep learning on point clouds.

PyTorch Lightning is a Keras-like ML library for PyTorch. It leaves core training and validation logic to you and automates the rest.

CrypTen is a framework for Privacy Preserving ML. Its goal is to make secure computing techniques accessible to ML practitioners.

OpenMMLab covers a wide range of computer vision research topics including classification, detection, segmentation, and super-resolution.

PennyLane is a library for quantum ML, automatic differentiation, and optimization of hybrid quantum-classical computations.

FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes.

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

A powerful and flexible machine learning platform for drug discovery.

pystiche is a framework for Neural Style Transfer (NST) built upon PyTorch.

Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend.

PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch.

skorch is a high-level library for PyTorch that provides full scikit-learn compatibility.

ClearML is a full system ML / DL experiment manager, versioning and ML-Ops solution.

Horovod is a distributed training library for deep learning frameworks. Horovod aims to make distributed DL fast and easy to use.

GPyTorch is a Gaussian process library implemented using PyTorch, designed for creating scalable, flexible Gaussian process models.