Create the arange tensor on device for enabling CUDA-Graph for Clip Encoder


# What does this PR do?
This PR changes the allocation of a tensor at the [modeling_clip.py](https://github.com/huggingface/transformers/blob/main/src/transformers/models/clip/modeling_clip.py#L665) to happen at device side, to be able to use CUDA-Graph at DeepSpeed-Inference, which can help improve the performance for the Stable-Diffusion model inference. Here is the [PR ](https://github.com/microsoft/DeepSpeed/pull/2381)that includes the optimization for improving the SD performance.

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [ ] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [ ] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [ ] Did you write any new necessary tests?


## Who can review?

@patrickvonplaten, @stas00 
_The documentation is not available anymore as the PR was closed or merged._