PyTorch is a flexible machine learning library for building deep learning models that can perform a wide range of tasks such as image recognition and language processing. This guide walks through cloning the PyTorch source repository, building a container image for either CPU or GPU systems, and pushing the finished image to a container registry. By the end, you'll have a custom PyTorch container image built from source and published to a registry, ready to pull into any Docker-compatible environment.

Prerequisites

A server with Docker installed (a GPU-enabled server with the NVIDIA Container Toolkit if you're building the GPU image).

Access to the server using SSH as a non-root user with sudo privileges.

Start the Docker service.

$ sudo systemctl start docker

Add the non-root user to the Docker group. For example, linuxuser .

$ sudo usermod -aG docker linuxuser

Switch to the user:

$ su - linuxuser

1. Set Up the Server

1.…