Tutorials And Examples#

Welcome to Ivy’s tutorials webpage! Our goal is to provide you with a comprehensive learning experience on a variety of topics. We have organized our tutorials into three main sections to help you find exactly what you need.

If you are in a rush, you can jump straight into the Quickstart, a quick and general introduction to Ivy’s features and capabilities!

  • In the Learn the basics section, you will find basic and to the point tutorials to help you get started with Ivy.

  • In the Examples and Demos section, you will find start-to-finish projects and applications that showcase real-world applications of Ivy. Whether you’re a beginner or an advanced user, we’ve got you covered!

Note

Want to use Ivy locally? Check out the Get Started section of the docs!

Learn the Basics#

Transpiling Functions from PyTorch to TensorFlow

Transpiling Kornia functions to TensorFlow.

Transpiling Models from PyTorch to TensorFlow

Transpiling PyTorch models to TensorFlow.

Trace Code

Trace an efficient fully-functional graph of your ML models/code.

Lazy vs Eager

Understand the difference between eager & lazy tracing and transpilation.

How to use decorators

Learn about the different ways to use ivy’s graph tracer and transpiler.

Examples and Demos#

Accelerating PyTorch models with JAX

Accelerate your Pytorch models by converting them to JAX for faster inference.

Finetuning PyTorch Models in your TensorFlow Projects

In this demo, we finetune the PyTorch ResNet model in TensorFlow

Image and Keypoints Augmentations in Jax transpiled Kornia

In this demo, we apply augmentations to images using Jax transpiled Kornia

Denoise Image using TensorFlow transpiled Kornia

In this demo, we denoise an image using TensorFlow transpiled Kornia