tps://pytorchnlp.readthedocs.io)

[

  * padl 
  * ![](/assets/images/logo-github.svg)
  *   * 
Pipeline Abstractions for Deep Learning in PyTorch
](https://lf1-io.github.io/padl/)

[

  * PyPOTS 
  * ![](/assets/images/logo-github.svg)
  *   * 
A Python toolbox for data mining on Partially-Observed Time Series (POTS) and
helps engineers focus more on the core problems in rather than missing parts
in their data.  ](https://github.com/WenjieDu/PyPOTS)

[

  * Lightly 
  * ![](/assets/images/logo-github.svg)
  *   * 
Lightly is a computer vision framework for self-supervised learning.
](https://github.com/lightly-ai/lightly)

[

  * avalanche 
  * ![](/assets/images/logo-github.svg)
  *   * 
Avalanche: an End-to-End Library for Continual Learning
](http://avalanche.continualai.org)

[

  * PyTorch Lightning 
  * ![](/assets/images/logo-github.svg)
  *   * 
PyTorch Lightning is a Keras-like ML library for PyTorch. It leaves core
training and validation logic to you and automates the rest.
](https://github.com/williamFalcon/pytorch-lightning)

[

  * pytorchfi 
  * ![](/assets/images/logo-github.svg)
  *   * 
A runtime fault injection tool for PyTorch.
](https://github.com/pytorchfi/pytorchfi)

[

  * Captum 
  * ![](/assets/images/logo-github.svg)
  *   * 
Captum (“comprehension” in Latin) is an open source, extensible library for
model interpretability built on PyTorch.  ](https://captum.ai/)

[

  * MMF 
  * ![](/assets/images/logo-github.svg)
  *   * 
A modular framework for vision & language multimodal research from Facebook AI
Research (FAIR).  ](https://mmf.sh/)

[

  * PyTorch Geometric 
  * ![](/assets/images/logo-github.svg)
  *   * 
PyTorch Geometric is a library for deep learning on irregular input data such
as graphs, point clouds, and manifolds.
](https://github.com/rusty1s/pytorch_geometric)

[

  * PyKale 
  * ![](/assets/images/logo-github.svg)
  *   * 
PyKale is a PyTorch library for multimodal learning and transfer learning with
deep learning and dimensionality reduction on graphs, images, texts, and
videos.  ](https://github.com/pykale/pykale)

[

  * skorch 
  * ![](/assets/images/logo-github.svg)
  *   * 
skorch is a high-level library for PyTorch that provides full scikit-learn
compatibility.  ](https://github.com/skorch-dev/skorch)

[

  * composer 
  * ![](/assets/images/logo-github.svg)
  *   * 
library of algorithms to speed up neural network training
](https://github.com/mosaicml/composer)

[

  * ColossalAI 
  * ![](/assets/images/logo-github.svg)
  *   * 
Colossal-AI is a Unified Deep Learning System for Big Model Era
](https://www.colossalai.org/)

[

  * DGL 
  * ![](/assets/images/logo-github.svg)
  *   * 
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.
](https://www.dgl.ai)

[

  * VISSL 
  * ![](/assets/images/logo-github.svg)
  *   * 
A library for state-of-the-art self-supervised learning  ](https://vissl.ai/)

[

  * FairScale 
  * ![](/assets/images/logo-github.svg)
  *   * 
FairScale is a PyTorch extension library for high performance and large scale
training on one or multiple machines/nodes.
](https://github.com/facebookresearch/fairscale)

[

  * Catalyst 
  * ![](/assets/images/logo-github.svg)
  *   * 
Catalyst helps you write compact, but full-featured deep learning and
reinforcement learning pipelines with a few lines of code.
](https://github.com/catalyst-team/catalyst)

[

  * pomegranate 
  * ![](/assets/images/logo-github.svg)
  *   * 
pomegranate is a library of probabilistic models that is built in a modular
manner and treats all models as the probability distributions that they are.
](https://pomegranate.readthedocs.io/en/latest/)

[

  * Ignite 
  * ![](/assets/images/logo-github.svg)
  *   * 
Ignite is a high-level library for training neural networks in PyTorch. It
helps with writing compact, but full-featured training loops.
](https://github.com/pytorch/ignite)

[

  * N