I'm using Anaconda (in Ubuntu 18.04) and I have an environment with Keras (and tensorflow-gpu) installed. Here are the different versions:
- Keras: 2.2.4
- Tensorflow-GPU: 1.15.0
- CuDNN: 7.6.5 for Cuda10.0.0
- CudaToolKit: 10.0.130
The version are chosen by Conda, but I'm wondering why it downloaded 10.0 when nvidia-smi shows me that my cuda should be (or is?) 10.1:
NVIDIA-SMI 435.21 Driver Version: 435.21 CUDA Version: 10.1
But, fun fact, when I do nvcc --version:
Cuda compilation tools, release 9.1, V9.1.85
So here comes my question(s): what version of Cuda am I using? What version of Cuda should I be using? Does Anaconda handle Cuda by environment?
PS: (this is not my question, but why I ask it)
I'm asking that because I'm running into this issue:
tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
I looked for an solution (could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR) but none of the answer I tried worked (deleting files, running in sudo, etc) so I think it's a compatibility issue