How to plugin a PJRT/common runtime device to Tensorflow?
### Issue type

Support

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

Yes

### Source

source

### TensorFlow version

2.13.1

### Custom code

Yes

### OS platform and distribution

_No response_

### Mobile device

_No response_

### Python version

_No response_

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

Hi all, I am trying to plugin a PJRT device to tensorflow. I saw https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/framework/load_library.py#L160, but that seems to be for the StreamExecutor C API.

I also took a look at https://github.com/tensorflow/tensorflow/blob/6c20138314183635f70dfff454d065f25e833ff1/tensorflow/core/common_runtime/pluggable_device/pluggable_device_plugin_init.cc#L75, which is what I think is what want to call. Is there a python binding for this function or am I supposed to call it directly?

Jax has something like this listed in step 3 here: https://github.com/openxla/xla/blob/b3745173ea3d15306663c8a6f2124da8efea4289/xla/pjrt/c/docs/pjrt_integration_guide.md
Is there something similar for TensorFlow?

Thanks for the help.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf #If I understand correctly a properly plugged in library should be able to be detected on import.
```


### Relevant log output

_No response_