To setup a GPU- Supportfor Nvidia and Tensor flow you need these things
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You should have nvidia device drivers installed.
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Check nvidia-smi it should be working.if it is not working dont worry follow the steps
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You need to downlod CUDA and cuDNN
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Before downloading CUDA and cuDNN check for the comptability with the tensorflow version
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Here will be installing tensorflow 2.9.0 so we need to download CUDA 11.2 and cuDNN 8.1
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Go to https://developer.nvidia.com/cuda-downloads then archive or directly to https://developer.nvidia.com/cuda-toolkit-archive
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Select the version thatis 11.2 we will click on 11.2.2 which is the ist as in
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Select Linux then x86 then ubuntu then 20.04 then run file you will get the two steps as below
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Exectute these two in your ubuntu shell. The first one will download the file and second one for installation.
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Wait for the menu to pop up and continue the type accept.
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if your nvidia-smi was not working the check the Driver and CUDA Toolkit11.2. you do not need Samples Demo Suite and Documentation
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You now have CUDA installed and now you need cuDNN
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Download cuDNN from this https://developer.nvidia.com/rdp/cudnn-archive
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Select the compatible version for tensorflow2.9 we need 8.1
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Click on the link and download the for Linux(x86_64) if you have 64. A tar file will be download
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Unzip the tar file by thefollowing command
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tar -xvf file_name
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You will now have a cuda folder in created in the current directory and the files are extracted there
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Type these three commands but remeber to check you have cuda folder in you current directory.
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sudo cp cuda/include/cudnn*.h /usr/local/cuda/include
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sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64
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sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
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open .bashrc file using nano
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nano ~/.bashrc
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add these two lines at the end of the file
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export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}$
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export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
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save it and close it.
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Restart the terminal and check
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nvidia-smi
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nvcc -V
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both shod be working
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now create an python environment
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sudo apt-get install -y python3-pip
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sudo apt-get install -y python3-venv
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python -m venv environemnt_name
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activate your environment
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source environment_name/bin/activate
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using pip install tensorflow-gpu 2.9.0
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pip install tensorflow-gpu==2.9.0
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now you have tensorflow-gpu2.9.0 CUDA 11.2 and cuDNN 8.1 installed
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wile installing tensorflow-gpu you might get the error of protobuf version comptability issue
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Solve that using
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pip install --upgrade protobuf==3.11
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That is all