PyTorch Pocket Reference

Chapter 1. An Introduction to PyTorch

PyTorch is one of the most popular deep learning Python libraries, and it is widely used by the AI research community. Many developers and researchers use PyTorch to accelerate deep learning research experimentation and prototyping.

In this chapter, I will give you a brief introduction to what PyTorch is and some of the features that make it popular. I’ll also show you how to install and set up your PyTorch development environment on your local machine and in the cloud. By the end of this chapter, you will be able to verify that PyTorch is properly installed and run a simple PyTorch program.

What Is PyTorch?

The PyTorch library is primarily developed by Facebook’s AI Research Lab (FAIR) and is free and open source software with over 1,700 contributors. It allows you to easily run array-based calculations, build dynamic neural networks, and perform autodifferentiation in Python with strong graphics processing unit (GPU) acceleration—all important features required for deep learning research. Although some use it for accelerated tensor computing, most use it for deep learning development.

PyTorch’s simple and flexible interface enables fast experimentation. You can load data, apply transforms, and build models with a few lines of code. Then, you have the flexibility to write customized training, validation, and test loops and deploy trained models with ease.

It has a strong ecosystem and a large user community, including universities like Stanford ...