[Models] Prevent CUDA sync in Qwen2.5-VL

[lgeiger]

This is a followup to #24443 from @david6666666

When I profiled Qwen2.5-VL it seems like an implicit CUDA sync is still happening during the indexing:

vllm/vllm/model_executor/models/qwen2_5_vl.py

Line 826 in 59d5d2c

hidden_states = hidden_states[reverse_indices, :]

This is because reverse_indices now is computed on CPU and needs to be copied in a blocking way to the GPU before the indexing operation can happen.

This PR copies the reverse_indices to the GPU in a non blocking removing this sync. An alternative would be to call invert_permutation on the window_index GPU tensor which would run it on GPU. Since it's a simple indexing operation it's probably not worth doing on GPU.

I ran end2end benchmarks on the lmarena-ai/VisionArena-Chat dataset but didn't see any changes in performance which I don't quite understand. However, the profile clearly shows that the CUDA sync is gone with this change which is a good thing in general and might be relevant with bit multimodal inputs.

Related to #23884, so tagging @ywang96 for review.

[gemini-code-assist]

Code Review

This pull request introduces a performance optimization for the Qwen2.5-VL model by eliminating an implicit CUDA synchronization. The change correctly uses pinned memory for a CPU-based tensor (reverse_indices) and then performs a non-blocking copy to the GPU. This is a standard and effective technique to improve performance by avoiding stalls in the CUDA stream. The implementation appears correct and directly addresses the issue described. I have not identified any issues of high or critical severity in these changes.

[lgeiger]

Merging main to re-trigger failing CI