HPU support
Author: IlyasMoutawwakil
Pull request: yes

# What does this PR do?

This PR introduces upstream support for HPU torch device/backend:
- HPU is the device name for Intel Gaudi Accelerators, a very powerful, energy efficient ASIC for AI workloads.
- Gaudi1 is available on [AWS](https://aws.amazon.com/ec2/instance-types/dl1/) since [2021](https://aws.amazon.com/blogs/aws/new-ec2-instances-powered-by-gaudi-accelerators-for-training-deep-learning-models/), Gaudi2/Gaudi3 on [Intel Dev Cloud](https://developer.habana.ai/intel-ai-cloud/) and soon on [IBM Cloud](https://www.intel.com/content/www/us/en/partner/showcase/ibm/overview.html). 
- The documentation of the torch device is available [here](https://docs.habana.ai/en/latest/PyTorch/Reference/PyTorch_Gaudi_Theory_of_Operations.html).

This PR focuses on enabling out of the box support in eager mode (`PT_HPU_LAZY_MODE=0`), while `optimum-habana` will continue to enable optimized paths making use of the lazy mode and advanced features of the SynapseAI software stack.


This is part of three PRs:
- Safetensors https://github.com/huggingface/safetensors/pull/578
- Accelerate https://github.com/huggingface/accelerate/pull/3378
- Transformers https://github.com/huggingface/transformers/pull/36424 (this one)

## Before submitting
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- [ ] 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.

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Models:

- text models: @ArthurZucker
- vision models: @amyeroberts, @qubvel
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- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- pipelines: @Rocketknight1
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- 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)
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Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_36424). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

@ArthurZucker @muellerzr PR is ready for review, I made sure (trainer, fsdp, deepspeed) tests ran successfully on both gaudi1 and gaudi2 in single and multi device settings.

> only thing we may want is to add an accelerate import check to flag

Added ! target version is 1.50 right ? @muellerzr