The PyTorch-Ignite Blog

Updates, tips & best practices around PyTorch-Ignite.

• Bridging Data Science Tools with PyTorch-Ignite's Code-Generator and Nebari

  Published on September 20, 2023 – 9 mins

  Bridging Data Science Tools with PyTorch-Ignite’s Code-Generator and Nebari To the readers, I am Aryan Gupta( @guptaaryan16), an EE Junior at IIT Roorkee, and this summer, I had a chance to work on PyTorch-Ignite’s Code-Generator project, a tailor-made web application to help machine learning researchers and enthusiasts and also keeping in mind the growing Kaggle community. Crossposted from https://labs.quansight.org/blog The project itself Let’s see the project itself.

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• Sangho's Internship at Quansight with PyTorch-Ignite project

  Published on February 3, 2023 – 3 mins

  Hey, I’m Sangho Lee, a master’s student from Seoul National University. I have participated in the PyTorch-Ignite project internship at Quansight Labs, working on test code improvements and features for distributed computations.

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• GAN evaluation using FID and IS

  Published on August 11, 2021 – 14 mins

  GAN Evaluation : the Frechet Inception Distance and Inception Score metrics

  

  In this notebook, two PyTorch-Ignite’s metrics to evaluate Generative Adversarial Networks (or GAN in short) are introduced :

  • Frechet Inception Distance, details can be found in Heusel et al. 2002
  • Inception Score, details can be found in Barratt et al. 2018

  See here for more details about the implementation of the metrics in PyTorch-Ignite.

  Most of the code here is from DCGAN example in pytorch/examples. In addition to the original tutorial, this notebook will use in-built GAN based metric in ignite.metrics to evaluate Frechet Inception Distnace and Inception Score and showcase other metric based features in ignite.

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• Introducing PyTorch-Ignite's Code Generator v0.2.0

  Published on July 16, 2021 – 3 mins

  

  Along with the PyTorch-Ignite 0.4.5 release, we are excited to announce the new release of the web application for generating PyTorch-Ignite’s training pipelines. This blog post is an overview of the key features and updates of the Code Generator v0.2.0 project release.

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• Distributed Training Made Easy with PyTorch-Ignite

  Published on June 28, 2021 – 5 mins

  

  Writing agnostic distributed code that supports different platforms, hardware configurations (GPUs, TPUs) and communication frameworks is tedious. In this blog, we will discuss how PyTorch-Ignite solves this problem with minimal code change.

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• Introduction to PyTorch-Ignite

  Published on September 10, 2020 – 24 mins

  

  This post is a general introduction of PyTorch-Ignite. It intends to give a brief but illustrative overview of what PyTorch-Ignite can offer for Deep Learning enthusiasts, professionals and researchers. Following the same philosophy as PyTorch, PyTorch-Ignite aims to keep it simple, flexible and extensible but performant and scalable.

  Throughout this tutorial, we will introduce the basic concepts of PyTorch-Ignite with the training and evaluation of a MNIST classifier as a beginner application case. We also assume that the reader is familiar with PyTorch.

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