The NVIDIA NGC container catalog has a broad range of GPU-optimised containers for common activities such as deep learning. How does one find what is inside the Docker images?
For example, I require an image with Pytorch 1.4 and Python 3.6 or 3.7, but the Pytorch tags go from pytorch:17.10 to pytorch:21.06-py3 (where xx.xx is the container version). Is there somewhere a list of what is installed in each container, or even better the container Dockerfile that was used to build the images?
You can do a high level inspection of the image using:
docker history <IMAGE> also at one point I've used this tool:
https://github.com/wagoodman/dive which was quite nice in order to inspect different layers.
So basically you can inspect each layer to see the instructions used in order to build that specific image and search for commands that have been used to install different packages
The details of pytorch NGC containers are listed at PyTorch Release Notes at the bottom of the pytorch NGC page.
All other deep learning frameworks related documentation is also at NVIDIA Deep Learning Frameworks.
