Not a particularly satisfying answer, but solved by removing all NVIDIA packages and installing the NVIDIA Data Science Stack from scratch, then using its Conda environment to run kerass
in R.
export CUDA_HOME=/usr/local/cuda
export PATH="/usr/local/cuda/bin:$PATH"
export LD_LIBRARY_PATH=/usr/lib/cuda/lib64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=/usr/lib/cuda/include:$LD_LIBRARY_PATH
W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /home/nickopotamus/.local/share/r-miniconda/envs/r-reticulate/lib:/usr/lib/R/lib::/lib:/usr/lib/x86_64-linux-gnu:/usr/lib/jvm/default-java/lib/server
/home/nickopotamus/.local/share/r-miniconda/envs/r-reticulate/lib/libcudart.so.11.0
/home/nickopotamus/anaconda3/pkgs/cudatoolkit-11.3.1-h2bc3f7f_2/lib/libcudart.so.11.0
/home/nickopotamus/anaconda3/pkgs/cudatoolkit-11.2.0-h73cb219_8/lib/libcudart.so.11.0
/home/nickopotamus/anaconda3/pkgs/cudatoolkit-11.2.72-h2bc3f7f_0/lib/libcudart.so.11.0
/usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudart.so.11.0
The top entry at least appears to be in the path that the error is searching, so I'm at a bit of a loss as to what to try next. Is it a conflict with the other anaconda packages (which I can't seem to remove), or am I simply being oblivious to a quick-fix?
Edit: Solved by using the NVIDIA Data Science Stack to install everything from scratch.
Not a particularly satisfying answer, but solved by removing all NVIDIA packages and installing the NVIDIA Data Science Stack from scratch, then using its Conda environment to run kerass
in R.
It seems that you have cuda 10 installed, and not version 11 which is what TensorFlow is looking for. It has rather specific requirements to get working.
Tensorflow 2.4.1 requires cuda 11 and cudnn 8 (see GPU table of requirements here). I would suggest checking also, your nvidia driver version, 450.x or higher is required.
This is the TensorFlow official documentations on how to get all requirements installed for GPU training/inference, look under which OS you are running.
If you just wanted to update cuda via conda, you could do a
conda install cudatoolkit=11.0.