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DOCKER PYTORCH SET FOR MAC HOW TO
DOCKER PYTORCH SET FOR MAC CODE

Sounds good? Well, then let’s get started. Finally, we are gonna get into “the how’s” and dig into making all of the magic happen. Then I’ll go over “ the why’s” so that you get an understanding of the motivation for using each of those components. The structure of this post will be as follows: I begin by describing my motivation for writing this article in the first place - the “ multi-CUDA experience” 😱 ️ - a horrible place in the space-time-continuum that nobody should ever have to visit.Īfterwards I will answer some questions that you might have: I’ll start by explaining the different components of the project - “ the what’s” - so that you get an idea of what each part does.

DOCKER PYTORCH SET FOR MAC HOW TO

And even better: we’re gonna learn how to use VSCode to debug our network, without needing to rebuild our container even if we change the source code! In this post, I’m going to show you how you can train a PyTorch deep neural network on the MNIST data set inside a Docker container which I’ll build and run using Docker Compose. I found it very easy to configure for debugging Docker containers.

DOCKER PYTORCH SET FOR MAC CODE

Visual Studio Code (VSCode) is an open source code editor which can be extended with a lot of plugins.

Conda is an open-source system for packaging and managing application dependencies inside dedicated environments.

Docker Compose is a tool that enables you to run multiple containers as services at the same time.

Containers are somehow similar to virtual machines, but other than them they use the same Linux kernel as the host computer that they are running on.

Docker is a containerization solution which lets you build and run application within containers.

To get the most out of this tutorial, you need to have some prior experience with Python and Data Science / Deep Neural Networks.

If you want to skip the tutorial and jump straight to the code: here it is.

In this tutorial I’m gonna show you how you can debug a PyTorch neural network model running inside a Docker container using VSCode.