### What this PR does / why we need it?
Currently, there are two paths to judge the chip type in code,
`get_ascend_soc_version` use `get_soc_version` api in torch_npu, and
`is_310p` `use _build_info.__soc_version__`, which generate when
install. We need to unify the two paths.
We need to unify these codes based on the following points:
1. We need to ensure consistency in chip type judgment between compiling
and running states;
2. In compiling state, we need chip type to complete op's compilation,
but in running state, we only need device
type(910B/910_93/310P/910_95/etc) to make code branch judgement;
3. In compiling state, torch_npu may not have been installed yet, so we
can't use torch_npu's api.
Based on the above points, we have made the following changes:
1. When user set env `SOC_VERSION`, use it; when not set, query
soc_version by `npu-smi`;
2. generate device_type based on soc_version when compiling, and write
`__device_type__` instead of `__soc_version__` in `_build_info.py`;
3. In running state, use `__device_type__` to judge code branch.
### Does this PR introduce _any_ user-facing change?
When not set env `SOC_VERSION`, it will not be `ASCEND910B1` by default,
we will query soc_version by `npu-smi`. And env `SOC_VERSION` must be in
the list `soc_to_device` in `setup.py`.
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
Signed-off-by: zzzzwwjj <1183291235@qq.com>
### What this PR does / why we need it?
This PR refactors the Ascend attention implementation to align with
vLLM's core interfaces, simplifying the code and improving
maintainability.
### Key Changes:
* **Align with vLLM's Attention Interface**: The `forward` method
signature in `AscendAttentionBackendImpl` now matches the base
`AttentionImpl` in vLLM, removing the custom `trace_flag`.
* **Enable Opaque Attention Operator**: By adding `opaque_attention_op`
to `AscendPlatform`, we allow vLLM to wrap our attention kernel in its
standard `vllm.unified_attention_with_output` operator. This avoids the
need for a custom call path.
* **Remove Obsolete Code**:
* The custom op `vllm.unified_ascend_attention_with_output` has been
deleted as it is now redundant.
* The `trace_flag` and its associated logic were removed, reducing code
complexity.
* An outdated quantization branch within the attention implementation
was cleaned up.
* **Improve Readability**: Renamed output variables (`output` vs.
`intermediate_output`) and added comments to clarify the in-place nature
of the attention output.
### Does this PR introduce _any_ user-facing change?
None.
### How was this patch tested?
No extra tests needed.
- vLLM version: v0.11.0rc3
- vLLM main:
17c540a993
---------
Signed-off-by: Yizhou Liu <liu_yizhou@outlook.com>
### What this PR does / why we need it?
Fixes#3096
1. Fix kv cache initialization error of attention layer. There are some
models with layer name like `attn.attn`, instead of `self_attn`, but the
initialization of kv cache tensors only check for `self_attn` and
`attn.attn`, which leding to the error `AssertionError: Some layers are
not correctly initialized`
2. Set the default value of input arg `sampling_metadata` in
`compute_logits` for the modeling files in vllm-ascend. Thus fixing the
error `Qwen3NextForCausalLM.compute_logits() missing 1 required
positional argument: 'sampling_metadata'`
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
test locally with internlm
- vLLM version: v0.10.2
- vLLM main:
5aeb925452
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
1. Similar to #2384 , this PR add a torchair-specific modeling for
pangu.
2. Fixes a bug introduced by routed_scaling_factor in #2675 .
3. remove eager test case for pangu since there has already been a
torchair test case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- vLLM version: v0.10.1.1
- vLLM main:
6997a25ac6
---------
Signed-off-by: zengyanjia <z00883269@china.huawei.com>
Signed-off-by: Angazenn <supperccell@163.com>
Co-authored-by: zengyanjia <z00883269@china.huawei.com>
