Tensorflow GPU：错误说。dll 文件未找到，但确实存在

Question

I've been trying to get CUDA to work with TensorFlow for a while now because the neural nets I've been building are now taking hours to train on my CPU, and it'd be great to get that big speed boost. However, whenever I try to use it with TensorFlow (it works with PyTorch, but I want to learn multiple APIs), it tells me that one of the.dll files needed to run CUDA doesn't exist, when it actually does.

I've downloaded and replaced that.dll with other versions from dll-files.com. I've tried uninstalling and reinstalling TensorFlow, CUDA, and cuDNN. I've tried different versions of CUDA, but that only caused all the.dll files to not be found (and yes, I did change the CUDA_PATH value). I've tried switching the PATH between C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0 and C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0\bin to see if that changed anything.

If anyone could help with this, that would be much appreciated.

The errors I get when I run tf.test.is_gpu_available()

The file existing

Answer 1

Have you checked if your TF version was compatible with your CUDA version?

Check the compatibility matrix here: https://www.tensorflow.org/install/source#tested_build_configurations

Unless you compile TF from source, CUDA 11 is not supported yet.

In any case, I would avoid downloading dll from the website you mentioned.

Answer 2

Try installing a different older version of the CUDA toolkit on top of the version you have installed already. It fixed it for me however I also had to import all the previous dlls from the latest cuDNN toolkit into the new legacy CUDA toolkit installs as well.