This guide will walk you through the process of creating a custom model built with Burn. We will train a simple convolutional neural network model on the MNIST dataset and prepare it for inference.

For clarity, we sometimes omit imports in our code snippets. For more details, please refer to the corresponding code in the examples/guide directory. We reproduce this example in a step-by-step fashion, from dataset creation to modeling and training in the following sections. It is recommended to use the capabilities of your IDE or text editor to automatically add the missing imports as you add the code snippets to your code.

Be sure to checkout the git branch corresponding to the version of Burn you are using to follow this guide.

The current version of Burn is 0.13.2 and the corresponding branch to checkout is release/0.13.

The code for this demo can be executed from Burn's base directory using the command:

cargo run --example guide

Key Learnings

  • Creating a project
  • Creating neural network models
  • Importing and preparing datasets
  • Training models on data
  • Choosing a backend
  • Using a model for inference