[WIP][Feature]Support using flash-attention and flash-varlen-attention on Ascend NPU
Author: FightingZhen
Pull request: yes

# What does this PR do?
Package `flash-attn` is not supported on Ascend NPU, **even can not be installed**. In that case, we can not use flash-attention or flash-varlen-attention with transformers naturally.

Additionally, through [Ascend FlashAttentionScore Document](https://www.hiascend.com/document/detail/zh/Pytorch/600/ptmoddevg/trainingmigrguide/performance_tuning_0027.html) we find that Ascend `torch_npu` package has provided flash-attention and flash-varlen-attention apis on Ascend NPU, which can play the same role as the apis in package `flash-attn`.

Therefore, this PR is for supporting using flash-attention and flash-varlen-attention on Ascend NPU. All modifications are controlled in using Ascend NPU.

## Modifications
1. Create a new file `src/transformers/utils/npu_flash_attention_utils.py` to organize necessary functions for using flash-attention and flash-varlen-attention on Ascend NPU, part of codes are copied from [flash-attn/bert_padding.py](https://github.com/Dao-AILab/flash-attention/blob/main/flash_attn/bert_padding.py). 
2. Allow `is_flash_attn_2_available`, `is_flash_attn_greater_or_equal_2_10` and `is_flash_attn_greater_or_equal` 3 functions return `True` when detecting `torch` and `torch_npu` available before detecting whether package `flash-attn` exists or not.
3. Patch `index_first_axis`, `pad_input`, `unpad_input`, `flash_attn_func`, `flash_attn_varlen_func` 5 functions online to replace same functions in package `flash-attn` when detecting `torch_npu` available.

Fixes # (issue)


## 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#create-a-pull-request),
      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?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
- speech models: @eustlb
- graph models: @clefourrier

Library:

- flax: @gante and @Rocketknight1
- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
- tensorflow: @gante and @Rocketknight1
- tokenizers: @ArthurZucker
- trainer: @muellerzr and @SunMarc
- chat templates: @Rocketknight1

Integrations:

- deepspeed: HF Trainer/Accelerate: @muellerzr
- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization (bitsandbytes, autogpt): @SunMarc @MekkCyber

Documentation: @stevhliu

HF projects:

- accelerate: [different repo](https://github.com/huggingface/accelerate)
- datasets: [different repo](https://github.com/huggingface/datasets)
- diffusers: [different repo](https://github.com/huggingface/diffusers)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Maintained examples (not research project or legacy):

- Flax: @Rocketknight1
- PyTorch: See Models above and tag the person corresponding to the modality of the example.
- TensorFlow: @Rocketknight1

 -->


Comments:
Hi 👋, thank you for opening this pull request! The pull request is converted to draft by default. When it is ready for review, please click the `Ready for review` button (at the bottom of the PR page).