tensorflow: tensorflow-gpu: Could not load dynamic library 'libcudart.so.10.1'

System information

• Have I written custom code (as opposed to using a stock example script provided in TensorFlow):

import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): ArchLinux 64bits
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): tensorflow-gpu 2.2.0rc4
• Python version: 3.8.2
• CUDA/cuDNN version: 10.2.89-5 (from Archlinux repo)

Describe the problem

TensorFlow doesn’t use my GPU because there is a bug while trying to load “libcudart.so.10.1”. My system has libcudart.so.10.2 installed All the other libraries load fine since they look for libcu***.so.10 and not 10.1

Source code / logs

Python 3.8.2 (default, Apr  8 2020, 14:31:25) 
[GCC 9.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
2020-05-03 22:17:42.422067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2020-05-03 22:17:42.471297: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-05-03 22:17:42.472040: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: 
pciBusID: 0000:09:00.0 name: GeForce GTX 1080 Ti computeCapability: 6.1
coreClock: 1.683GHz coreCount: 28 deviceMemorySize: 10.91GiB deviceMemoryBandwidth: 451.17GiB/s
2020-05-03 22:17:42.472169: 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
2020-05-03 22:17:42.473728: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2020-05-03 22:17:42.475267: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2020-05-03 22:17:42.475499: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2020-05-03 22:17:42.477078: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2020-05-03 22:17:42.478053: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2020-05-03 22:17:42.481446: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2020-05-03 22:17:42.481478: 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...
Num GPUs Available:  0

Here is the CUDA lib I have installed:

/opt/cuda/doc/man/man7/libcudart.7
/opt/cuda/doc/man/man7/libcudart.so.7
/opt/cuda/targets/x86_64-linux/lib/libcudart.so
/opt/cuda/targets/x86_64-linux/lib/libcudart.so.10
/opt/cuda/targets/x86_64-linux/lib/libcudart.so.10.2
/opt/cuda/targets/x86_64-linux/lib/libcudart.so.10.2.89
/opt/cuda/targets/x86_64-linux/lib/libcudart_static.a