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Spinning a Docker Container with Cuda Enabled TensorFlow
Summary
This article describes how to set up a TensorFlow Docker container that utilizes GPU from the host system. First, Nvidia drivers need to be installed on the host system. Then, Docker needs to be installed. After that, Nvidia-Docker2 needs to be installed. Finally, the TensorFlow Docker container can be run.
Q&As
What is the main pain point for Deep Learning Practioners when setting up Cuda enabled Tensorflow/PyTorch?
The main pain point for Deep Learning Practioners when setting up Cuda enabled Tensorflow/PyTorch is the installation process. This can involve installing Nvidia, Cuda, cuDNN, and Tensorflow/PyTorch, each of which can be a hurdle.
What is Docker and what does it enable developers to do?
Docker is an open source containerization platform. It enables developers to package applications into containers โ standardized executable components combining application source code with the operating system (OS) libraries and dependencies required to run that code in any environment.
What is Nvidia-Docker2 and what does it help with?
Nvidia-Docker2 is a package that helps with using Cuda on Docker Container.
How do you install and set up TensorFlow in a Docker Container?
To install and set up TensorFlow in a Docker Container, you need to install Nvidia Drivers on the Host System. You can then add Dockerโs official GPG key and set up the stable repository. Update the apt package index and install the latest version of Docker Engine and containerd.io. Verify that Docker Engine is installed correctly by running the hello-world image.
How can you test to see if the GPU is available inside the Docker Container?
To test to see if the GPU is available inside the Docker Container, you can run the TensorFlow Docker container and specify the TensorFlow version that you need. You can then run a print statement to check if the GPU is available inside the docker container.
AI Comments
๐ It is very helpful for deep learning practioners to have a cuda enabled TensorFlow. This article provides a great guide on how to set one up using Docker.
๐ This article is very difficult to follow. It is hard to understand what some of the commands are supposed to do.
AI Discussion
Me: It's about spinning a Docker Container with Cuda Enabled TensorFlow.
Friend: That sounds complicated.
Me: Yeah, it is. But it's a really helpful article.
Friend: Why is it helpful?
Me: Well, it shows you how to set up a TensorFlow Docker Container that utilizes GPU from the host system.
Friend: That's helpful. I've been wanting to learn how to do that.
Me: Yeah, it's a really good article.
Action items
- Install Nvidia drivers on the host system.
- Set up a TensorFlow Docker container that utilizes GPU from the host system.
- Install Nvidia-Docker2.
Technical terms
- Docker
- an open source containerization platform that enables developers to package applications into containers
- Nvidia-Docker2
- a platform that helps users utilize Cuda on Docker containers
- TensorFlow
- an open source machine learning platform