Torchair graph812 cov

[NicholasTao]

What this PR does / why we need it?

Does this PR introduce any user-facing change?

How was this patch tested?

• vLLM version: v0.10.0
• vLLM main: vllm-project/vllm@0ca2393

[gemini-code-assist]

Code Review

This pull request adds support for Qwen models with torchair, including new model files, tests, and configuration changes. My review focuses on several critical issues. I've identified a typo in a test patch target that would cause it to fail. More importantly, I found two critical bugs in the rotary_embedding implementation: one causing a tensor shape mismatch due to incorrect unsqueeze operations, and another related to an incorrect monkey-patch target that would prevent the new rotary embedding logic from being used. These issues need to be addressed to ensure the correctness of the new functionality.

[gemini-code-assist]

The target string for patch seems incorrect. 'mockif._get_fused_moe_state' will likely cause a ModuleNotFoundError because mockif is not a valid module. Based on the imports, you probably intended to patch _get_fused_moe_state from vllm_ascend.ascend_forward_context.

Suggested change

	with patch('mockif._get_fused_moe_state', side_effect=stubbed_get_state):
	with patch('vllm_ascend.ascend_forward_context._get_fused_moe_state', side_effect=stubbed_get_state):

[gemini-code-assist]

The unsqueeze(1) calls on query and key introduce an extra dimension, which leads to an incorrect output shape from rope_forward. The attention mechanism expects a tensor of shape (num_tokens, num_heads * head_size), but this implementation will produce a tensor with an extra dimension of size 1, e.g., (num_tokens, 1, num_heads * head_size). This will cause a shape mismatch error in the subsequent attention computation. The unsqueeze calls on cos and sin should also be adjusted to a single unsqueeze to ensure correct broadcasting.

Suggested change

	cos = cos.unsqueeze(-2).unsqueeze(-2)
	sin = sin.unsqueeze(-2).unsqueeze(-2)
	query = query.unsqueeze(1)
	key = key.unsqueeze(1)
	q_embed, k_embed = torch_npu.npu_apply_rotary_pos_emb(query, key, cos, sin)
	cos = cos.unsqueeze(-2)
	sin = sin.unsqueeze(-2)
	q_embed, k_embed = torch_npu.npu_apply_rotary_pos_emb(query, key, cos, sin)

[gemini-code-assist]

You are monkey-patching RotaryEmbedding.forward_oot, but RotaryEmbedding instances are called via their forward method. To correctly override the rotary embedding logic, you should patch RotaryEmbedding.forward. Using forward_oot will not have the desired effect as it's not the standard method called.

Suggested change

	RotaryEmbedding.forward_oot = rope_forward
	RotaryEmbedding.forward = rope_forward

[github-actions]

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[codecov]

Codecov Report

❌ Patch coverage is 77.67442% with 48 lines in your changes missing coverage. Please review.
✅ Project coverage is 75.77%. Comparing base (c611291) to head (f759f5e).
⚠️ Report is 27 commits behind head on main.

Files with missing lines	Patch %	Lines
vllm_ascend/models/qwen3_moe.py	31.74%	43 Missing ⚠️
vllm_ascend/ops/rotary_embedding.py	89.58%	5 Missing ⚠️

❌ Your patch check has failed because the patch coverage (77.67%) is below the target coverage (100.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2337      +/-   ##
==========================================
- Coverage   76.09%   75.77%   -0.32%     
==========================================
  Files         114      118       +4     
  Lines       13103    13731     +628     
==========================================
+ Hits         9971    10405     +434     
- Misses       3132     3326     +194     

Flag	Coverage Δ
unittests	75.77% <77.67%> (-0.32%)	⬇️

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[github-actions]

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