Fix Qwen3.5-Next RMSNormGated Initialization Error on TPU

[jrplatin]

Purpose

Similar to #33501 -- fixes the following error seen on TPU:

# CMD
vllm serve Qwen/Qwen3.5-397B-A17B-FP8 --tensor-parallel-size=8 --kv-cache-dtype=fp8 --limit-mm-per-prompt '{"image": 0, "video": 0}'

# Error
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]   File "/mnt/disks/jacobplatin/vllm/vllm/model_executor/models/qwen3_5.py", line 245, in __init__
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]     self.linear_attn = Qwen3_5GatedDeltaNet(
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]                        ^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]   File "/mnt/disks/jacobplatin/vllm/vllm/model_executor/models/qwen3_next.py", line 504, in __init__
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]     device=current_platform.current_device(),
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099]            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore pid=3259063) ERROR 03-16 20:56:27 [core.py:1099] TypeError: 'NoneType' object is not callable

Test Plan

Test Result

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[gemini-code-assist]

Code Review

This pull request resolves a TypeError encountered during the initialization of RMSNormGated for the Qwen3.5-Next model on TPUs. The issue stems from current_platform.current_device() returning None on this platform, leading to a crash. By removing the explicit device argument from the RMSNormGated constructor, the code now relies on PyTorch's default device handling, which is a more portable and robust approach. This change correctly fixes the initialization error without introducing side effects on other platforms.

[yaochengji]

Is making TPUPlatform support current_device() an alternative way to fix this issue?

[jrplatin]

@yaochengji Yep good idea and will patch in TPU Inference, thanks!