GPU problem for CUDA 11.0 and cuDNN 8.0.2 - tensorflow

Question

I have the CUDA 11.0 and cuDNN 8.0.2, which are the recommended setup
I have tensorflow-gpu 2.3 and keras 2.4
However the GPUs are not used and I don't know why.
by giving the following command lines
sess = tf.test.is_gpu_available(cuda_only=False, min_cuda_compute_capability=None)
print("GPU available? ", sess)
built = tf.test.is_built_with_cuda()
print("tf is built with CUDA? ", built)
gpus = tf.config.list_physical_devices('GPU')
cpus = tf.config.list_physical_devices('CPU')
print("Num GPUs used: ", len(gpus))
print("Num CPUs used: ", len(cpus))
print(tf.sysconfig.get_build_info())
The output is the following:
GPU available? False
tf is built with CUDA? True
Num GPUs used: 0
Num CPUs used: 1
{'cuda_version': '10.1', 'cudnn_version': '7', 'cuda_compute_capabilities': ['sm_35', 'sm_37', 'sm_52', 'sm_60', 'sm_61', 'compute_70'], 'cpu_compiler': '/usr/bin/gcc-5', 'is_rocm_build': False, 'is_cuda_build': True}
it comes with the following error:
W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcudart.so.10.1'; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7
W tensorflow/core/common_runtime/gpu/gpu_device.cc:1753] 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.

Answer 1

As stated in Tensorflow documentation. The software requirements are as follows.
Nvidia gpu drivers - 418.x or higher
Cuda - 10.1 (TensorFlow >= 2.1.0)
cuDNN - 7.6
See Link
You must have a python version between 3.5 - 3.8.
Along with that you need Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019.
You can download that here. Link
Check the full system requirements here Link
Don't forget to add cuda and cudnn in your system path. See Link

Answer 2

This solution clears the issue completely in my case even my system is set up with CUDA 10.2. Tensorflow probably requires something from CUDA 10.1, I guess.
conda install cudatoolkit=10.1
Check https://github.com/tensorflow/tensorflow/issues/38578#issuecomment-710104168