Add update expected / unexpected keys api to DiffusersQuantizer

[Disty0]

What does this PR do?

Adds update_expected_keys and update_unexpected_keys APIs to DiffusersQuantizer.
Makes load_model_dict_into_meta compatible with updated unexpected / expected keys added in DiffusersQuantizer.

Fixes #12470

Before submitting

• This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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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.

Core library:

• General functionalities: @sayakpaul @yiyixuxu @DN6

[Disty0]

Here is a use case of this PR with SDNQ:

pip install git+https://github.com/Disty0/sdnq

import torch
import diffusers
from sdnq import SDNQConfig # import sdnq to register it into diffusers and transformers

pipe = diffusers.FluxPipeline.from_pretrained("Disty0/FLUX.1-dev-SDNQ-uint4-svd-r32", torch_dtype=torch.bfloat16)

if (
    hasattr(pipe.text_encoder_2.encoder.block[0].layer[0].SelfAttention.k, "scale")
    and pipe.text_encoder_2.encoder.block[0].layer[0].SelfAttention.k.scale.device.type != "meta"
    and hasattr(pipe.transformer.single_transformer_blocks[0].attn.to_k, "scale")
    and pipe.transformer.single_transformer_blocks[0].attn.to_k.scale.device.type != "meta"
):
    print("SDNQ model loaded succesfully")
else:
    print("SDNQ model failed to load")
    exit()

pipe.enable_model_cpu_offload()
prompt = "A cat holding a sign that says hello world"
image = pipe(
    prompt,
    height=1024,
    width=1024,
    guidance_scale=3.5,
    num_inference_steps=50,
    max_sequence_length=512,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev-sdnq-uint4-svd-r32.png")

(This result is generated with an Intel ARC A770 with FP64 Rope downcasted to FP32 to make it work on Alchemist as it doesn't support FP64.)