Hi @charlesfr.rey, on JetPack 4.x you can just use l4t-base container, because CUDA/cuDNN/TensorRT/ect get mounted into the container from the host device by the NVIDIA Container Runtime on JetPack 4.x. So l4t-base should already have these components in it.
I believe the container image for this would be nvcr.io/nvidia/l4t-tensorrt:r8.2.1-runtime, however it would be with Python 3.6, as we build the images for the default version of Python that comes with the version of Ubuntu used (and on JetPack 4.x, that’s Ubuntu 18.04 and Python 3.6)
However, you may be able to rebuild the TensorRT Python bindings for Python 3.8, as some others on the forums have done: