### What this PR does / why we need it?
Add e2e test cases for the Qwen-VL model adaptation to Ascend 310p
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: gcw_61wqY8cy <wanghengkang1@huawei.com>
### What this PR does / why we need it?
This pull request resolves an attention accuracy issue by enhancing the
AttentionMaskBuilder310 to correctly handle the maximum model length.
The change ensures that the attention mask generation process is
properly parameterized by the model's configuration, rather than relying
on a fixed internal value. This leads to more accurate attention mask
creation, which is crucial for the correct functioning of the attention
mechanism.
Update fused_moe to main branch.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Qwen3 dense mode & moe model e2e test
- vLLM version: v0.15.0
- vLLM main:
83b47f67b1
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
### What this PR does / why we need it?
This pull request significantly enhances the test suite by adding new
end-to-end test cases for Qwen3 models on the 310P hardware platform.
The primary goal is to ensure the stability and correctness of these
models under diverse operational conditions, including various
parallelism strategies, data types, and quantization methods.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
E2E test
- vLLM version: v0.15.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0
---------
Signed-off-by: pu-zhe <zpuaa@outlook.com>
