Tensorflow 2.2 GPU - which cuDNN library to install?

Question

I have successfully installed CUDA driver, cuDNN libraries and tensorflow. But when running a test program that simply imports tensorflow, I get an error. The error seems to suggest I have the wrong version of cuDNN libraries installed. I'd appreciate some help on this. And if I need to downgrade cuDNN, how do I do it?

Tensorflow version: 2.2 GPU OS: Ubuntu 16.04.6 LTS (GNU/Linux 4.4.0-184-generic x86_64) nvcc -V shows the following info:

nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Tue_Aug_11_14:27:32_CDT_2015
Cuda compilation tools, release 7.5, V7.5.17

nvidia-smi shows the following info:

Fri Jun 12 17:16:38 2020       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.36.06    Driver Version: 450.36.06    CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 980 Ti  Off  | 00000000:02:00.0 Off |                  N/A |
| 22%   27C    P8    17W / 250W |     74MiB /  6083MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1489      G   /usr/lib/xorg/Xorg                 71MiB |
+-----------------------------------------------------------------------------+

cuDNN successfully installed following instructions https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#download, but I think I installed version 11.0.

Error message when the program tries to import tensorflow (python 3.6)

2020-06-12 17:21:38.131160: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:02:00.0 name: GeForce GTX 980 Ti computeCapability: 5.2
coreClock: 1.228GHz coreCount: 22 deviceMemorySize: 5.94GiB deviceMemoryBandwidth: 313.37GiB/s
2020-06-12 17:21:38.131384: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2020-06-12 17:21:38.131498: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcublas.so.10'; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory
2020-06-12 17:21:38.133367: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-06-12 17:21:38.133807: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-06-12 17:21:38.137813: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-06-12 17:21:38.137958: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcusparse.so.10'; dlerror: libcusparse.so.10: cannot open shared object file: No such file or directory
2020-06-12 17:21:38.138063: W tensorflow/stream_executor/platform/default/dso_loader.cc:55] Could not load dynamic library 'libcudnn.so.7'; dlerror: libcudnn.so.7: cannot open shared object file: No such file or directory
2020-06-12 17:21:38.138085: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1598] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2020-06-12 17:21:38.138114: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-06-12 17:21:38.138131: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2020-06-12 17:21:38.138152: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 

Answer 1

Going by the following, for tensorflow 2.2 you need CUDA 10.1 and cuDNN 7.4:

https://www.tensorflow.org/install/source_windows#tested_build_configurations

CUDA archive/legacy releases: https://developer.nvidia.com/cuda-toolkit-archive

cuDNN archive, which you have to make an nvidia account to access: https://developer.nvidia.com/rdp/cudnn-archive

Of peculiar note is that there is no cuDNN within the 7.4 releases which is compatible with 10.1, so I would try the 7.5.0. Installing cuDNN is simply a matter of copying the files that you download into the folder where you installed CUDA (in their respective folders).