AttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no attribute '__dlpack__'
Hi there,

I do believe this will be highly valuable feature to add these dunders for better cross platform dl acceleration 

I'm interested in working on this issue and would appreciate mentorship. Could someone please guide me as I contribute to adding support for `__dlpack__` and `__dlpack_device__` to TensorFlow tensors

If so please mail me at prasanna0083@gmail.com as it will also boost me to contribute even more on the project!

Thank you,
Prasanna
 Hi @abdulasiraj ,

Could you please check this [RFC](https://github.com/tensorflow/community/blob/master/rfcs/20191016-dlpack-support.md) which may address your requirements. 

Also please refer to this API [page](https://www.tensorflow.org/api_docs/python/tf/experimental/dlpack) for currently available APIs.

If not please let us know. Thanks! Hi @SuryanarayanaY,
Thanks for your response. I've gone through RFC and APIs. `to_dlpack` and `from_dlpack` are working very fine with tensorflow but now new array_api_standard is to support `__dlpack__` and `__dlpack_device__` dunder methods for tensors. details can be seen here:
https://dmlc.github.io/dlpack/latest/python_spec.html
https://data-apis.org/array-api/latest/API_specification/generated/array_api.array.__dlpack__.html

Torch and jax supports both functions as well as dunders but numpy only supports dunders, which means we can't consume tf capsule in numpy.
### Issue type

Feature Request

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

No

### Source

source

### TensorFlow version

tf 2.12.0

### Custom code

Yes

### OS platform and distribution

google colab

### Mobile device

_No response_

### Python version

3.10.12

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current behavior?

it looks like tensorflow tesnors doesn't support `__dlpack__` and `__dlpack_device__` dunders. Not sure, If it's already something down the road map. If not, can we add these dunders to tf tensors to conform array_api_standrads?

### Standalone code to reproduce the issue

```shell
import tensorflow as tf
tensor = tf.constant([1,3,2])
tensor.__dlpack__()
```


### Relevant log output

```shell
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
[<ipython-input-3-016b1ec8a3b2>](https://localhost:8080/#) in <cell line: 1>()
----> 1 tensor.__dlpack__()

[/usr/local/lib/python3.10/dist-packages/tensorflow/python/framework/ops.py](https://localhost:8080/#) in __getattr__(self, name)
    441         np_config.enable_numpy_behavior()
    442       """)
--> 443     self.__getattribute__(name)
    444 
    445   @staticmethod

AttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no attribute '__dlpack__'
```
