Ignite Documentation

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
  • you get a training loop with metrics, early-stopping, model checkpointing and other features without the boilerplate

Below we show a side-by-side comparison of using pure pytorch and using ignite to create a training loop to train and validate your model with occasional checkpointing:

https://raw.githubusercontent.com/pytorch/ignite/master/assets/ignite_vs_bare_pytorch.png

As you can see, the code is more concise and readable with ignite. Furthermore, adding additional metrics, or things like early stopping is a breeze in ignite, but can start to rapidly increase the complexity of your code when “rolling your own” training loop.

Installation

From pip:

pip install pytorch-ignite

From conda:

conda install ignite -c pytorch

From source:

You can clone the source from github and run

python setup.py install