tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
@Fchaubard,
I suspect you are trying to install the every tensorflow version on CUDA 12.4 only which is not compatible. Could you please uninstall the installed libraries and try to install  Clang 16.0.0, Bazel 5.3.0, cuDNN - 8.6,	CUDA - 11.8  for the tensorflow v2.13 and check the below process.

```python
- Make sure cuda and cudnn are installed correctly.
- Make sure $Env:CUDA_PATH is given correctly
- Make sure $Env:LD_LIBRARY_PATH is given correctly
- Make sure $Env:TF_CUDA_PATHS is given correctly
```
https://www.tensorflow.org/install/source#gpu


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

Build/Install

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

No

### Source

source

### TensorFlow version

2.13.1

### Custom code

No

### OS platform and distribution

Ubuntu 20.04.6

### Mobile device

_No response_

### Python version

3.8.10

### Bazel version

_No response_

### GCC/compiler version

9.4.0

### CUDA/cuDNN version

CUDA 12.4

### GPU model and memory

GEFORCE GTX 4090

### Current behavior?

tensorflow does not detect the CUDA drivers but they are there and added to PATH.
---
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
2024-04-30 16:29:17.328463: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 16:29:17.362495: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 16:29:17.362915: 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.
2024-04-30 16:29:18.094331: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-04-30 16:29:18.749023: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1960] 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...
[]
---
nvidia-smi returns this suggesting the drivers are there and working:

+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.78                 Driver Version: 550.78         CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| 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 RTX 4090        Off |   00000000:03:00.0 Off |                  Off |
|  0%   36C    P8             12W /  450W |      29MiB /  24564MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A      1089      G   /usr/lib/xorg/Xorg                              9MiB |
|    0   N/A  N/A      1142      G   /usr/bin/gnome-shell                            8MiB |
+-----------------------------------------------------------------------------------------+


Even pytorch recognizes the drivers without issue: 
---
Python 3.8.10 (default, Nov 22 2023, 10:22:35) 
[GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.device_count()
1
>>> torch.cuda.get_device_name(0)
'NVIDIA GeForce RTX 4090'
---

But not tensorflow? Please help! 

### Standalone code to reproduce the issue

```shell
You will need to recreate the environment and then:
pip install tensorflow
```


### Relevant log output

_No response_