From c1ebe5fe46e977f1046a70d6503e544db06e82cd Mon Sep 17 00:00:00 2001 From: Crissman Loomis Date: Tue, 21 Jan 2020 14:55:08 +0900 Subject: [PATCH] Include Optuna integration badge in README.rst MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Hi! Optuna (optuna.org) is a new hyperparameter optimization library, and we’ve written an Optuna integration module for PyTorch Ignite to make it easy to search for good hyperparameter settings and prune unpromising trials. We’re looking for ways to let PyTorch Ignite users know this is available and thought a badge to show Optuna integration is available would be helpful. Here’s some documentation on pruning integrations: https://optuna.readthedocs.io/en/latest/tutorial/pruning.html If there are other ways you would recommend reaching out to PyTorch Ignite users to let them know about Optuna, please let us know. Thanks! --- README.rst | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.rst b/README.rst index 566625e61401..c0edd70b37f7 100644 --- a/README.rst +++ b/README.rst @@ -13,6 +13,9 @@ Ignite .. image:: https://img.shields.io/badge/dynamic/json.svg?label=docs&url=https%3A%2F%2Fpypi.org%2Fpypi%2Fpytorch-ignite%2Fjson&query=%24.info.version&colorB=brightgreen&prefix=v :target: https://pytorch.org/ignite/index.html +.. image:: https://img.shields.io/badge/Optuna-integrated-blue + :target: https://optuna.org + Ignite is a high-level library to help with training neural networks in PyTorch. - ignite helps you write compact but full-featured training loops in a few lines of code