Align qwen-image RoPE function naming with other models

[yeahdongcn]

This PR renames the qwen-image RoPE function to apply_qwen_rope_with_xxx to align with the naming conventions used by RoPE functions in other models, improving consistency and readability across the codebase.

Testing Done

root@worker3218:/ws/scripts/platforms/mthreads_musa# ./qwen_image_i2i_2511.sh

[gemini-code-assist]

Summary of Changes

Hello @yeahdongcn, 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 focuses on improving code consistency and readability by standardizing the naming of Rotary Positional Embedding (RoPE) functions specifically for the qwen-image model. The changes involve renaming functions to follow a apply_qwen_rope_with_xxx pattern and updating all references to these functions across relevant files to ensure proper integration and maintain a uniform codebase.

Highlights

• Function Renaming for Consistency: Renamed Rotary Positional Embedding (RoPE) functions within the qwen-image model to apply_qwen_rope_with_xxx to align with established naming conventions, enhancing code readability and maintainability.
• Import and Usage Updates: Updated import statements and dictionary lookups in transformer_infer.py for the qwen-image model to reflect the new function names, ensuring correct usage of the renamed RoPE functions.
• Minor Reordering in WAN Model: Reordered entries in the rope_funcs dictionary within the wan model's transformer_infer.py for consistency, without changing function names or behavior.

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[gemini-code-assist]

Code Review

This pull request effectively improves code consistency by renaming the RoPE functions in the qwen-image model to align with the conventions used in other models. The changes are clear and contribute to better readability and maintainability. I've added one suggestion to further reduce code duplication.

[gemini-code-assist]

While renaming this function improves consistency, I noticed that its implementation is identical to apply_wan_rope_with_flashinfer in lightx2v/models/networks/wan/infer/utils.py. To improve maintainability and reduce code duplication, consider refactoring this into a single, generic function (e.g., apply_rope_with_flashinfer) and placing it in a shared utility module, such as under lightx2v/common/. Both qwen_image and wan models could then import and use this common function.