Installing CUDA (with kernel driver, CuDNN, Tensorflow/PyTorch) has not been easy for me either. Usually you want to have the latest version of all of them. But

Installing CUDA (with kernel driver, CuDNN, Tensorflow/PyTorch) has not been easy for me either. Usually you want to have the latest version of all of them. But sometimes the very latest version of these packages is not yet supported by the other. This is where it get difficult. Also the fact that the CUDA instruction from TensorFlow [1] still are at Ubuntu 18.04 does not help. In my experience installing PyTorch with CUDA is easier than TensorFlow (and much better documented). The best experience, in my opinion, is however with CUDA and Flux.jl or Knet.jl on Julia. All you need there is the kernel driver (and julia). CUDA and CuDNN will be installed per default if necessary. I am wondering why CUDA is not simply a pip-installable package (like it is in Julia or in Conda). [1] https://www.tensorflow.org/install/gpu https://www.tensorflow.org/install/gpu