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:

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.

Notes

• Concepts
  • Engine
  • Events and Handlers
  • State
• Quickstart
  • Code
  • Explanation

Package Reference

• ignite.engine
• ignite.handlers
• ignite.metrics
• ignite.exceptions