(fix/diffusers): fix some bugs

[Cui-yshoho]

What does this PR do?

Fixes # (issue)

Adds # (feature)

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• 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 make sure to update the documentation with your changes? E.g. record bug fixes or new features in What's New. Here are the
  documentation guidelines
• Did you build and run the code without any errors?
• Did you report the running environment (NPU type/MS version) and performance in the doc? (better record it for data loading, model inference, or training tasks)
• Did you write any new necessary tests?

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[gemini-code-assist]

Summary of Changes

Hello @Cui-yshoho, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new multimodal processor for Qwen2-VL models, significantly refactors the Wan-VACE transformer architecture, and enhances several pipelines with improved type hinting and documentation. It also addresses cross-version compatibility for various pipeline tests, ensuring greater stability and robustness across different library environments. The changes aim to fix bugs and improve the overall functionality and maintainability of the mindone/diffusers components.

Highlights

• Qwen2-VL Multimodal Processor: A new Qwen2VLProcessor has been introduced in mindone.transformers to streamline the handling of multimodal inputs (images, videos, and text) for Qwen2-VL models, improving their integration and processing logic.
• Wan-VACE Transformer Enhancements: The WanVACETransformer3DModel has undergone significant refactoring, including the adoption of WanAttention and CacheMixin, along with adjustments to attention layer parameters and optimizations for tensor operations. A new runtime check for LoRA scaling has also been added.
• Pipeline Documentation and Type Consistency: Several pipelines received updates to their type hints for improved compatibility (e.g., list[Type] | None to Union[list[Type], None], ms.dtype to ms.Type). The WanVACEPipeline now includes a comprehensive usage example in its docstring.
• Cross-Version Test Compatibility: Conditional skip logic has been added to numerous pipeline tests, allowing them to adapt to different versions of the diffusers and transformers libraries and prevent failures due to API changes.

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[gemini-code-assist]

Code Review

This pull request introduces a variety of fixes and refactorings across the diffusers library. Key improvements include updating the transformer_wan_vace.py to use a new WanAttention class, correcting type hints for better compatibility (e.g., ms.dtype to ms.Type), and adding support for Qwen2VLProcessor. The changes generally enhance code quality and correctness. My review identifies one high-severity issue in pipeline_wan_vace.py where a necessary dtype conversion was removed, which could lead to runtime errors. I have provided a suggestion to fix this.

[gemini-code-assist]

The removal of .to(conditioning_latents.dtype) could introduce a dtype mismatch during the mint.cat operation on the next line. The conditioning_latents tensor has vae_dtype, while the mask tensor from prepare_masks appears to have a float32 dtype originating from the preprocess_conditions call. If vae_dtype is not float32 (e.g., bfloat16), this will likely cause a runtime error. It's safer to ensure both tensors have the same dtype before concatenation.

Suggested change

	mask = self.prepare_masks(mask, reference_images, generator)
	mask = self.prepare_masks(mask, reference_images, generator).to(conditioning_latents.dtype)

[gemini-code-assist]

The type hint for dtype has been corrected from Optional[ms.dtype] to Optional[ms.Type]. This is a good fix, as ms.Type is the correct way to hint a type class in MindSpore, whereas ms.dtype refers to an instance of a dtype. This improves type correctness and clarity.

[gemini-code-assist]

The type hint for dtype has been corrected from Optional[ms.dtype] to Optional[ms.Type]. This is a good fix, as ms.Type is the correct way to hint a type class in MindSpore, whereas ms.dtype refers to an instance of a dtype. This improves type correctness and clarity.

[gemini-code-assist]

The type hint for dtype has been corrected from Optional[ms.dtype] to Optional[ms.Type]. This is a good fix, as ms.Type is the correct way to hint a type class in MindSpore, whereas ms.dtype refers to an instance of a dtype. This improves type correctness and clarity.

[gemini-code-assist]

The type hint for dtype has been corrected from Optional[ms.dtype] to Optional[ms.Type]. This is a good fix, as ms.Type is the correct way to hint a type class in MindSpore, whereas ms.dtype refers to an instance of a dtype. This improves type correctness and clarity.

[gemini-code-assist]

The type hint for dtype has been corrected from Optional[ms.dtype] to Optional[ms.Type]. This is a good fix, as ms.Type is the correct way to hint a type class in MindSpore, whereas ms.dtype refers to an instance of a dtype. This improves type correctness and clarity.