"Skipping registering GPU devices"...message in JupyterLab v 3.6.3
@MessDeveloper,
Could you please confirm whether you are trying to execute the mentioned code on the base environment or the CUDA, tensorflow installed environment. Also make sure to execute the code in the environment where you installed the tensorflow and CUDA.

I tried to execute in our local environment and it was executed without any issue/error. Thank you! 

 Have the same issue  :

2024-02-24 17:46:11.024256: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-24 17:46:11.044842: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-24 17:46:11.045061: 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.
2024-02-24 17:46:11.491969: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
>>> gpus = tf.config.experimental.list_physical_devices('GPU')
2024-02-24 17:46:11.976038: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:995] 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
2024-02-24 17:46:11.992328: 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..

whereas NVIDIA-SMI 545.23.08              Driver Version: 545.23.08    CUDA Version: 12.3
installed and 
nvidia-tensorrt           99.0.0                   pypi_0    pypi
tensorboard               2.13.0                   pypi_0    pypi
tensorboard-data-server   0.7.2                    pypi_0    pypi
tensorboard-plugin-wit    1.8.1                    pypi_0    pypi
tensorboardx              2.6.2.2                  pypi_0    pypi
tensorflow-gpu            2.8.0                    pypi_0    pypi
tensorrt                  8.6.1.post1              pypi_0    pypi
tensorrt-bindings         8.6.1                    pypi_0    pypi
tensorrt-libs             8.6.1                    pypi_0    pypi
 > @MessDeveloper, Could you please confirm whether you are trying to execute the mentioned code on the base environment or the CUDA, tensorflow installed environment. Also make sure to execute the code in the environment where you installed the tensorflow and CUDA.
> 
> I tried to execute in our local environment and it was executed without any issue/error. Thank you!

Hello, despite appearing as a "base" environment in the screenshot, I'm running it in a specially created TensorFlow environment under Anaconda Navigator and running JupyterLab, I believe that dependences were downloaded, such as CUDA, how can I check it?

Thank you for your help. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62994">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62994">No</a>
 I closed it by mistake, sorry. Could you please check again?

Thanks! @MessDeveloper,
From the information provided above, I can see you are trying with the **tf-nightly**. I faced the same error with tf-nightly in the jupyter notebook. So I will check with the developer team on the same and provide more information.

![skipping gpu 2 17](https://github.com/tensorflow/tensorflow/assets/81610181/69f1a661-ce8e-4c93-b4b3-76ae1f66da96)


As a temporary workaround, you can try using the latest stable version **2.15** where it was detecting and executing the code on the GPU.

![2 15](https://github.com/tensorflow/tensorflow/assets/81610181/c5d88b86-cad2-43e1-ac01-599bd1cc823d)

Thank you!

 Hi @tilakrayal , I'm having the same problem. But in my case, CUDA libraries are loaded properly, it's just tensorflow does not detect any gpus (but it works normally with torch and nvidia-smi). Do you have any idea ?
Terminal outputs look like this:
```
(my_env) $ python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU')); print(tf.__version__)"       
2024-02-29 15:36:16.385941: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.                                                                                                                                   2024-02-29 15:36:16.435959: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.                                                                                                                                   
2024-02-29 15:36:16.436407: 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.         
2024-02-29 15:36:19.414065: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT          
2024-02-29 15:36:24.877011: 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...                                                                                                  []                                                                                                                                   
2.13.1 
``` @thangld201,
For tensorflow v2.13 you can try installing cuda toolkit and cudnn, & update the LD_LIBRARY_PATH and it works.
``` python
> conda activate tf
> conda install cudatoolkit=11.8
> export LD_LIBRARY_PATH="$HOME/miniconda3/envs/tf-test/lib"
> conda install cudnn=8.6
```
And also please follow the tested build configurations which are compatible for tensorflow v2.13
https://www.tensorflow.org/install/source#gpu
Thank you!


 @tilakrayal, I forgot to add cudnn to LD_LIBRARY_PATH, when I updated the following:
```
LD_LIBRARY_PATH=$CONDA_PREFIX/lib/python3.8/site-packages/nvidia/cudnn/lib:$LD_LIBRARY_PATH
```
Gpus were detected!

 @thangld201,
Thank you for the response! 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?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62994">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/62994">No</a>

### Issue type

Support

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

Yes

### Source

source

### TensorFlow version

v1.12.1-106195-g9060e62bf4e 2.17.0-dev20240219

### Custom code

No

### OS platform and distribution

Linux Ubuntu 22.04.4 LTS

### Mobile device

_No response_

### Python version

Python 3.11.5

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

12.2 / I don't know cuDNN version

### GPU model and memory

NVIDIA GeForce RTX 4070 Ti 12282MiB

### Current behavior?

While working in Jupyter Notebook throught Anaconda, when importing tensorflow I get this error. I spent a lot of money to be able to use GPU in Data Science works and I'm unable to use it at all...not sure if enviroment is OK...

Driver is:
![image](https://github.com/tensorflow/tensorflow/assets/102194556/44246d5d-a3fb-4cf3-8d78-680871caef43)

GPU model:
![image](https://github.com/tensorflow/tensorflow/assets/102194556/3e5f2fed-cf54-47eb-b437-5a1aafbc6618)


### Standalone code to reproduce the issue

```shell
import tensorflow as tf
gpus = tf.config.experimental.list_physical_devices('GPU')
for gpu in gpus:
    print("Name:", gpu.name, "  Type:", gpu.device_type)
```


### Relevant log output

```shell
2024-02-19 20:35:30.820121: I external/local_tsl/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-19 20:35:30.851745: 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
2024-02-19 20:35:30.851772: 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
2024-02-19 20:35:30.852727: 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
2024-02-19 20:35:30.857979: I external/local_tsl/tsl/cuda/cudart_stub.cc:31] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-19 20:35:30.858297: 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.
2024-02-19 20:35:31.682954: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
2024-02-19 20:35:32.799765: 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
2024-02-19 20:35:32.800463: 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...
```
