Setting nvidia-driver to work with tensorflow 2.15 [GPU] 
@andvsilva These errors suggest conflicts between different implementations of cuDNN, cuFFT, and cuBLAS libraries. 
Please verify that CUDA environment variables like CUDA_HOME and CUDA_VISIBLE_DEVICES are set correctly.
Also please do ensure you have the latest NVIDIA drivers installed for your GPU. 
I tried to replicate this on colab, please find the [gist](https://colab.research.google.com/gist/sushreebarsa/34a237fbfd90c3102aa6987a58f6e4b6/untitled933.ipynb#scrollTo=qzOkxZu-lWyX) here.
Thank you! This issue is stale because it has been open for 7 days with no activity. It will be closed if no further activity occurs. Thank you. This issue was closed because it has been inactive for 7 days since being marked as stale. Please reopen if you'd like to work on this further. Are you satisfied with the resolution of your issue?
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### Issue type

Bug

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

2.15

### Custom code

Yes

### OS platform and distribution

"Ubuntu 23.04

### Mobile device

"Ubuntu 23.04

### Python version

Python 3.11.4

### Bazel version

bazel 6.1.0

### GCC/compiler version

gcc (Ubuntu 12.3.0-1ubuntu1~23.04) 12.3.0

### CUDA/cuDNN version

CUDA Version: 12.3

### GPU model and memory

NVIDIA GeForce GTX 750 Ti

### Current behavior?

I trying to use GPU with tensorflow in jupyter notebook.

pre-req: https://www.tensorflow.org/install/source#gpu 

from terminal:

```Wed Feb 14 18:16:03 2024       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 545.29.06              Driver Version: 545.29.06    CUDA Version: 12.3     |
|-----------------------------------------+----------------------+----------------------+
| 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  NVIDIA GeForce GTX 750 Ti      Off | 00000000:01:00.0  On |                  N/A |
| 33%   37C    P8               1W /  38W |    436MiB /  4096MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
                                                                                         
+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|    0   N/A  N/A      2553      G   /usr/lib/xorg/Xorg                          187MiB |
|    0   N/A  N/A      2695      G   /usr/bin/gnome-shell                         26MiB |
|    0   N/A  N/A      3356      G   ...sion,SpareRendererForSitePerProcess       53MiB |
|    0   N/A  N/A      3743      G   ...onEnabled --variations-seed-version      129MiB |
|    0   N/A  N/A     42678      C   /usr/bin/python3                             27MiB |
+---------------------------------------------------------------------------------------+
```

```
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243

$ python --version         
Python 3.11.4

~ ⌚ 18:14:55
$ bazel --version
bazel 6.1.0

~ ⌚ 18:15:05
$ gcc --version
gcc (Ubuntu 12.3.0-1ubuntu1~23.04) 12.3.0
Copyright (C) 2022 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

$ cat /etc/os-release             
PRETTY_NAME="Ubuntu 23.04"
NAME="Ubuntu"
VERSION_ID="23.04"
VERSION="23.04 (Lunar Lobster)"
VERSION_CODENAME=lunar
ID=ubuntu
ID_LIKE=debian
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
UBUNTU_CODENAME=lunar
LOGO=ubuntu-logo


```




### Standalone code to reproduce the issue

```shell
import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())

## OUTPUT:
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
```


### Relevant log output

```shell
2024-02-14 17:58:40.696088: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-02-14 17:58:40.696166: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-02-14 17:58:40.829634: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-02-14 17:58:40.984397: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-02-14 17:58:43.234200: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2.15.0
2024-02-14 17:58:44.809184: I external/local_xla/xla/stream_executor/cuda/cuda_executor.cc:901] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero. See more at https://github.com/torvalds/linux/blob/v6.0/Documentation/ABI/testing/sysfs-bus-pci#L344-L355
2024-02-14 17:58:45.101985: W tensorflow/core/common_runtime/gpu/gpu_device.cc:2256] 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...
```
