I’ve been working on distroless containers for HPC users at the University of Virginia, notably achieving 99.5% reduction in image size for LightGBM and 18% reduction for TensorFlow without loss of performance. I’m wondering if distroless is of interest to the PyTorch community.
Our distroless Dockerfile can be found here 33 and the corresponding image is hosted on Docker Hub uvarc/pytorch:1.6.0-distroless.
The distroless image size is 771 MB which is about half the size of the 1.55 GB official runtime image. I tested that the distroless container with pip installation has the same performance (MNIST benchmark) on our GPU node as the official container with conda installation. I’m aware that the official one has many other conda packages, but I wonder if they are necessary for a minimal (and functional) container.
I’ve read this thread 3 on conda vs pip for pytorch, but is there a specific example that can demonstrate better performance of conda over pip? (MNIST benchmark shows equal performance.)