Commit Graph

6 Commits

Author SHA1 Message Date
linfeng-yuan
68d8d20ca2 [misc] move mxfp_compat into device to decouple from quantization init chain (#6918)
### What this PR does / why we need it?
`mxfp_compat` only provides dtype/symbol compatibility helpers for
different `torch_npu` versions, but it was placed under
`vllm_ascend.quantization`. Importing it from device/ops paths could
trigger `quantization/__init__.py` and pull in heavy quantization method
dependencies, increasing startup coupling and causing import-cycle risk
(especially on 310P paths).

### Does this PR introduce _any_ user-facing change?
No functional behavior change intended.

### How was this patch tested?
CI passed.

- vLLM version: v0.16.0
- vLLM main:
15d76f74e2

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2026-03-02 18:17:01 +08:00
Icey
ee59429015 upgrade main to 0212 (#6712)
### What this PR does / why we need it?
Fixes `transformers_utils/processors/__init__` import error, due to
https://github.com/vllm-project/vllm/pull/33247
Fixes Fused MoE break introduced by `MoERunner abstraction,` due to
https://github.com/vllm-project/vllm/pull/32344

> delete AscendMoERunnere when
https://github.com/vllm-project/vllm/pull/35178 is merged

Fixes `Make Qwen3VL compatible with Transformers v5`, due to
https://github.com/vllm-project/vllm/pull/34262

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main:
9562912cea

---------

Signed-off-by: wxsIcey <1790571317@qq.com>
2026-02-25 09:17:29 +08:00
pu-zhe
a8e951e6f5 [Feat] 310p supports PrefillCacheHit State (#6756)
### What this PR does / why we need it?
This PR extends the Ascend 310P attention backend to support the
`PrefillCacheHit` state. Previously, only `PrefillNoCache`,
`DecodeOnly`, and `ChunkedPrefill` were supported.
This PR handles this state by routing it to the existing
`forward_chunked_prefill_310` implementation, which is suitable for this
scenario.
The changes also include refactoring the main `forward_impl` dispatch
method for better clarity and updating unit tests to cover the new state
and ensure correctness.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Accuracy test when chunked prefill is disabled.
- vLLM version: v0.15.0
- vLLM main:
9562912cea

---------

Signed-off-by: pu-zhe <zpuaa@outlook.com>
2026-02-24 16:48:05 +08:00
debuger
c1618a0427 [Bugfix]Fix the compatibility issue of may_reinitialize_input_batch (#6290)
### What this PR does / why we need it?
Added a check in the may_reinitialize_input_batch method to verify
whether the backend implements the get_supported_block_size method

### Does this PR introduce _any_ user-facing change?
no user-facing change

### How was this patch tested?
Only a few lines of code within the methods were modified, and the
format check test has been passed.
- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

---------

Signed-off-by: Debuuuuger <huangzr@cmbchina.com>
Signed-off-by: debuger <102402761+huangazazaz@users.noreply.github.com>
Signed-off-by: Debuuuuger <12110718@mail.sustech.edu.cn>
Co-authored-by: Debuuuuger <huangzr@cmbchina.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
2026-02-02 19:16:26 +08:00
pu-zhe
57fd6e4bd9 [Refact.]: refactoring 310p-kv cache allocator, align with main branch (#6270)
### What this PR does / why we need it?
refactoring 310p-kv cache allocator, align with main branch

vLLM version: v0.14.0
vLLM main: https://github.com/vllm-project/vllm-ascend/pull/6270
Qwen2.5-7B E2E Test

---------

Signed-off-by: pu-zhe <puzhe1@h-partners.com>
Signed-off-by: pu-zhe <zpuaa@outlook.com>
Co-authored-by: pu-zhe <puzhe1@h-partners.com>
2026-01-27 16:26:48 +08:00
Shaoxu Cheng
fbae41697e [310P]: refactoring for 310p kvcache and some ops class (#6117)
### What this PR does / why we need it?
* Refactor the LayerNorm and activation operator classes to decouple the
310P device implementation from the main branch.
* Refactor `mm_encoder_attention` on 310P to use the
`torch_npu._npu_flash_attention_unpad` operator.
* Refactor the QKV inputs in the prefill stage of `attention_v1` on 310P
so they are no longer padded to 16× alignment.
* Refactor `model_runner` on 310P to align the KV-cache initialization
logic with the mainline implementation.

### Does this PR introduce _any_ user-facing change?
NO

### How was this patch tested?
use the e2e tests.

- vLLM version: v0.13.0
- vLLM main:
d68209402d

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
2026-01-24 20:34:29 +08:00