[FPQuant] MXFP8 and MXFP4 backwards support
Author: BlackSamorez
Pull request: yes

# What does this PR do?

This PR adds MXFP4 and MXFP8 backwards support in combination with MXFP4 forward, allowing for lightning-fast QAT on Blackwell GPUs.

It's blocked by `QuTLASS v0.2.0` and `fp_quant v0.3.0` release we're hoping to release within a day or two.

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Models:

- text models: @ArthurZucker @Cyrilvallez
- vision models: @yonigozlan @molbap
- audio models: @eustlb @ebezzam @vasqu
- multimodal models: @zucchini-nlp
- graph models: @clefourrier

Library:

- generate: @zucchini-nlp (visual-language models) or @gante (all others)
- continuous batching: @remi-or @ArthurZucker @McPatate
- pipelines: @Rocketknight1
- tokenizers: @ArthurZucker and @itazap
- trainer: @SunMarc
- attention: @vasqu @ArthurZucker @CyrilVallez
- model loading (from pretrained, etc): @CyrilVallez
- distributed: @3outeille @ArthurZucker
- CIs: @ydshieh

Integrations:

- ray/raytune: @richardliaw, @amogkam
- Big Model Inference: @SunMarc
- quantization: @SunMarc @MekkCyber
- kernels: @MekkCyber @drbh
- peft: @BenjaminBossan @githubnemo

Devices/Backends:

- AMD ROCm: @ivarflakstad
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@SunMarc 

Comments:
`FP-Quant v0.3.1` has been [released](https://github.com/IST-DASLab/FP-Quant/releases/tag/v0.3.1).
`QuTLASS v0.2.0` has been [released](https://github.com/IST-DASLab/qutlass/releases/tag/v0.2.0).

This PR is ready to merge.

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: fp_quant_integration

@SunMarc @ArthurZucker ?

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