[Misc] Add ignored layers for fp8 quantization

[mgoin]

FIX #6592

Allows for ignored layers in fp8.py, like already implemented for compressed-tensors and fbgemm_fp8.
Implements the requested refactor in the above PR:

We should not make this type of logic in llama.py because it will be too difficult to maintain
Instead, let's have Fp8Config.get_quant_method(layer) extend to have the layer_name passed. Then, if the layer_name is in the ignored list we can return UnquantizedLinearMethod() from this function

[github-actions]

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[mgoin]

/ready