controlnet_sd3 parameters updated

[bigbraindump]

What does this PR do?

Adds 2 additional expected parameters dual_attention_layers and qk_norm to the SDControlNetModel class. The necessary parameters are defined by the SD3Transformer2DModel introduced in SD3.

Fixes #9974

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?
• Did you read our philosophy doc (important for complex PRs)?
• Was this discussed/approved via a GitHub issue or the forum? 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, and
  here are tips on formatting docstrings.
• Did you write any new necessary tests?

Who can review?

@sayakpaul

[sayakpaul]

While I understand this will enable the community to do ControlNet SD3.5 training / inference, it might be also nice to check if there's an existing one already. No worries if not.

[bigbraindump]

ah i see, misunderstood the question on the issue. there only seems to be pr #8566 addressing controlnet SD3 training.