[Feature] Qwen3 next support sp.

[weijinqian0]

• vLLM version: v0.10.2
• vLLM main: vllm-project/vllm@releases/v0.11.0

[github-actions]

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[gemini-code-assist]

Code Review

This pull request adds support for sequence parallelism (SP) for the Qwen3-Next model. The changes involve refactoring linear parallel operations, adding SP-specific logic in the model's decoder layer, and introducing a new AscendGemmaRMSNorm layer. My review has identified two critical bugs: one in the new AscendGemmaRMSNorm layer definition that would cause runtime errors due to an incorrect method signature, and another in the refactored linear op dispatcher which has a function call signature mismatch, also leading to a TypeError. These issues need to be addressed to ensure correctness.

[gemini-code-assist]

The forward_oot method in AscendGemmaRMSNorm is incorrectly defined as a static method with a mismatched signature. It should be an instance method, and its signature should match the forward method it's overriding, which is (self, x, residual=None). The current implementation will lead to incorrect argument passing at runtime, as the variance_epsilon parameter in the signature will receive the x tensor, and the x parameter will receive the residual tensor. The variance_epsilon should be accessed from self.variance_epsilon instead of being a parameter.

Suggested change

	@staticmethod
	def forward_oot(
	self,
	variance_epsilon: float,
	x: torch.Tensor,
	residual: Optional[torch.Tensor] = None,
	) -> Union[torch.Tensor, tuple[torch.Tensor, torch.Tensor]]:
	"""PyTorch-native implementation equivalent to forward()."""
	return self.forward_static(self.weight.data, self.variance_epsilon, x,
	residual)
	def forward_oot(
	self,
	x: torch.Tensor,
	residual: Optional[torch.Tensor] = None,
	) -> Union[torch.Tensor, tuple[torch.Tensor, torch.Tensor]]:
	"""PyTorch-native implementation equivalent to forward()."""
	return self.forward_static(self.weight.data, self.variance_epsilon, x,
	residual)

[gemini-code-assist]

The signature of _get_column_parallel_op is (disable_tp, prefix, layer), but it is called as _get_column_parallel_op(prefix, layer) in get_parallel_op at line 463. This mismatch will cause a TypeError at runtime. The disable_tp parameter is not used within the function and should be removed from the signature to match the call site.

Suggested change

	def _get_column_parallel_op(
	disable_tp, prefix, layer
	) -> Tuple[Optional[Union[MLPColumnParallelOp, SequenceMergedColumnParallelOp,
	SequenceQKVParallelOp]], int, int]:
	def _get_column_parallel_op(
	prefix, layer
	) -> Tuple[Optional[Union[MLPColumnParallelOp, SequenceMergedColumnParallelOp,
	SequenceQKVParallelOp]], int, int]:

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.