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I am using ubuntu 22 LTS. I want to use a different version of Cuda in the conda virtual environment. I want to use a virtual conda environment for tensorflow 1.x and another conda env for tensorflow 2.x and one environment for PyTorch. I add the version of Cuda when I created the environment. My problem is that instead of using the Cuda that is installed in the conda env (ie. conda create -n tf1 cudnn=7.6.5 cudatoolkit=10.1.243 ), it uses the system cuda. when I type the

nvcc --version
the output is:
nvcc: NVIDIA (R) Cuda compiler driver
Built on Tue_May__3_18:49:52_PDT_2022
Cuda compilation tools, release 11.7, V11.7.64
Build cuda_11.7.r11.7/compiler.31294372_0
how can I set the path to use the specific Cuda version installed in the environment and not the system?
You can set the CUDA_HOME environment variable with this command.
conda env config vars set CUDA_HOME=""
You should be able to use this command to find the path of your conda-installed CUDA library.
sudo find / -name nvcc
You might also want to look at this documentation to have environment variables set as part of the activation step.
https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#saving-environment-variables
                thank u for your answer. However, I haven't installed cuda-nvcc in the env . I have installed cudatoolkit and cudnn via conda. is there another way to find the path of cuda in the conda env?
– homa taha
                Jun 20, 2022 at 16:45
                So I just tried this on a fresh instance, and found that I had to install cuda-nvcc as well. I wonder if the issue is that cudatoolkit  and cudnn aren't install cuda-nvcc and thus aren't providing an alternative path when the conda env is activated.
– peytoncas
                Jun 20, 2022 at 18:40