> People who have had to deal with processes that rebuilt images for each environment, can you tell me what was different in each image? Tensorflow used to gen

> People who have had to deal with processes that rebuilt images for each environment, can you tell me what was different in each image? Tensorflow used to generate multiple images for different use cases: cpu only, GPU, cpu with Jupyterhub, GPU with Jupyterhub. So each release would generate minimum 4x container builds. CPU only images were useful for local testing of ml code at CLI (does it run) when a GPU might no be available. Jupyterhub variants for simple GUI for development work. GPU for obvious reasons (run the damn thing). I can’t remember if they used to do builds for their release against multiple CUDA / CuDNN versions… that might have been PyTorch.