Tensorflow 2.13.1 not detecting GPU on Jetson Orin, not built with CUDA
Hi @Paul-Mick ,

Please find the installation instructions for Tf2.13v from the history of [pip.md ](https://github.com/tensorflow/docs/blob/513d92d69cacbe9f2bda19e96045e6b836c93545/site/en/install/pip.md)file.

In Tf2.13v you need to install CUDA toolkit manually using the instructions in the attached link.

 Thanks for the reply.

The instructions in the pip.md file did not resolve my issue.

Luckily I found the solution elsewhere: the [NVIDIA Jetson Framework Installation Page](https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html)

Apparently there is a special version of Tensorflow for Jetson devices, the newest of which is 2.14.0+nv23.11.

Installing this with `pip install --extra-index-url https://developer.download.nvidia.com/compute/redist/jp/v60dp tensorflow==2.14.0+nv23.11` has Tensorflow recognizing my GPU properly.

Just wanted to post this incase others have the same issue. @Paul-Mick ,

Tensorflow officially provides installation instructions for Ubuntu only. Your [comment](https://github.com/tensorflow/tensorflow/issues/62711#issuecomment-1875936782) can help others who uses the Jetson device. Just curious to mention that in above comment you installed TF2.14v which you are not intending to earlier? 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/62711">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/62711">No</a>
 Issue fixed @SuryanarayanaY 

You are correct, I did end up installing Tensorflow 2.14 which I was not intending to. I had run into a weird issue on my AGX Orin where the ethernet adapter would go down every once in a while, and I was unable able to fix it directly.

I ended up re-flashing the Orin to JetPack 6.0DP, which supports CUDA 12.2 and cuDNN 8.9. When looking into installing Tensorflow on Jetson devices deeper I found [NVIDIA's index of Tensorflow builds for Jetson](https://developer.download.nvidia.com/compute/redist/jp), and decided to use the newest of those, which is 2.14.0+nv23.11.

I did not want to upgrade Tensorflow originally because it would have required completely restarting my project, but since that was going to happen anyhow when re-flashing my Orin upgrading became less troublesome. And using the version of Tensorflow built for Jetson fixed my original issue.
### Issue type

Bug

### 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

### Mobile device

NVIDIA Jetson AGX Orin

### Python version

3.8

### Bazel version

NA

### GCC/compiler version

NA

### CUDA/cuDNN version

CUDA 11.8/cuDNN 8.6.0.163

### GPU model and memory

NA

### Current behavior?

I am working on an object detection project and am ready to train my model, but Tensorflow does not recognize my GPU. Looking into it further, I found that my Tensorflow had been without GPU or CUDA support, just XLA support.

I had installed Tensorflow with pip.

I know that Tensorflow 2.13.1 does not have the "and-cuda" extra, so how can I specify through pip installation that Tensorflow be installed with GPU and CUDA support?

P.S. I want to avoid switching to Tensorflow 2.14.* because I am using python 3.8 which Tensorflow 2.13.1 is the last supporting version of.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

print(tf.config.list_logical_devices())
print(tf.config.list_physical_devices())
print(tf.test.is_built_with_cuda())
print(tf.test.is_built_with_gpu_support())
print(tf.test.is_built_with_rocm())
print(tf.test.is_built_with_xla())
print(tf.version.GIT_VERSION)
print(tf.version.VERSION)
```


### Relevant log output

```shell
[LogicalDevice(name='/device:CPU:0', device_type='CPU')]
[PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')]
False
False
False
True
v2.13.1-0-gf841394b
2.13.1
```
