ZImageTransformer2D: Only build attention mask if seqlens are not equal

[Beinsezii]

What does this PR do?

Fixes a small performance regression for Z Image Turbo.

Basically just sets attn_mask to None when it would otherwise be all ones, which is always the case for Z Image Turbo where guidance_scale==1 for typical usage.

On an H100 this improves performance by about 4%, using AttentionBackendName._NATIVE_CUDNN.

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?

@yiyixuxu or @sayakpaul probably

[sayakpaul]

Cc: @JerryWu-code who contributed the model.

[Beinsezii]

More relevant with new higher compute model

[Beinsezii]

We've been running this in production for Turbo for a while