For Pytorch and Tensorflow, there are tags which differentiate devel and runtime, I am not quite sure what are the difference between these two, can someone help me understand that better?
Copy from nvidia-docker:
CUDA images come in three flavors and are available through the NVIDIA public hub repository.
base: starting from CUDA 9.0, contains the bare minimum (libcudart) to deploy a pre-built CUDA application.
Use this image if you want to manually select which CUDA packages you want to install.runtime: extends the base image by adding all the shared libraries from the CUDA toolkit.
Use this image if you have a pre-built application using multiple CUDA libraries.devel: extends the runtime image by adding the compiler toolchain, the debugging tools, the headers and the static libraries.
Use this image to compile a CUDA application from sources.