To confirm the installation was successful, check if the cuDNN version is correctly identified in your system files:
: This specific build is for CUDA 11.x. While cuDNN 8.x is generally compatible across CUDA 11.x versions, using the exact matching CUDA 11.2 toolkit is recommended for stability with frameworks like TensorFlow 2.6. cudnn-11.2-linux-x64-v8.1.1.33.tgz
Do you need help to a specific framework like TensorFlow or PyTorch? Installing cuDNN Backend on Windows To confirm the installation was successful, check if
: Ensure /usr/local/cuda/lib64 is in your LD_LIBRARY_PATH environment variable so your software can find the libraries. To confirm the installation was successful
:Ensure the files are readable by all users to avoid permission errors during model training:
