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[Bugfix][LoRA] Fix LoRA bug after supporting Qwen3-Next (#3044)

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### What this PR does / why we need it?
LoRA e2e test uses ilama-3.2-1B model. It uses transformers.py model
files. Its self-attention layer names end with "\*.attn", not
"\*.self_attn".

There are some other model attention layer names end with "*.attn", such
as baichuan.py, bert.py.

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

### How was this patch tested?
pytest -sv tests/e2e/singlecard/test_ilama_lora.py
pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py

- vLLM version: v0.10.2
- vLLM main:
17b4c6685c

---------

Signed-off-by: paulyu12 <507435917@qq.com>
This commit is contained in:
yupeng
2025-09-26 11:12:45 +08:00
committed by GitHub
parent 8406aafaff
commit 9caf6fbaf5
2 changed files with 35 additions and 2 deletions
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4
.github/workflows/_e2e_test.yaml vendored
View File

@@ -92,7 +92,7 @@ jobs:
pytest -sv tests/e2e/singlecard/test_chunked.py
pytest -sv tests/e2e/singlecard/test_embedding.py
pytest -sv tests/e2e/singlecard/test_guided_decoding.py
#pytest -sv tests/e2e/singlecard/test_ilama_lora.py
pytest -sv tests/e2e/singlecard/test_ilama_lora.py
pytest -sv tests/e2e/singlecard/test_profile_execute_duration.py
pytest -sv tests/e2e/singlecard/test_quantization.py
pytest -sv tests/e2e/singlecard/test_sampler.py
@@ -174,7 +174,7 @@ jobs:
# external_launcher test is not stable enough. Fix it later
# pytest -sv tests/e2e/multicard/test_external_launcher.py
pytest -sv tests/e2e/multicard/test_fused_moe_allgather_ep.py
#pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
pytest -sv tests/e2e/multicard/test_ilama_lora_tp2.py
# To avoid oom, we need to run the test in a single process.
pytest -sv tests/e2e/multicard/test_offline_inference_distributed.py::test_models_distributed_QwQ

33
vllm_ascend/lora/utils.py
View File

@@ -6,11 +6,15 @@ from transformers import PretrainedConfig
from vllm.config import LoRAConfig
from vllm.lora.layers import (ColumnParallelLinearWithLoRA,
MergedColumnParallelLinearWithLoRA,
MergedQKVParallelLinearWithLoRA,
QKVParallelLinearWithLoRA,
RowParallelLinearWithLoRA,
VocabParallelEmbeddingWithLoRA)
from vllm.lora.layers.utils import _not_fully_sharded_can_replace
from vllm_ascend.ops.linear import (AscendColumnParallelLinear,
AscendMergedColumnParallelLinear,
AscendQKVParallelLinear,
AscendRowParallelLinear)
from vllm_ascend.ops.vocab_parallel_embedding import \
AscendVocabParallelEmbedding
@@ -69,9 +73,38 @@ class AscendVocabParallelEmbeddingWithLoRA(VocabParallelEmbeddingWithLoRA):
return type(source_layer) is AscendVocabParallelEmbedding
class AscendQKVParallelLinearWithLoRA(QKVParallelLinearWithLoRA):
@classmethod
@_not_fully_sharded_can_replace
def can_replace_layer(cls, source_layer: nn.Module,
lora_config: LoRAConfig, packed_modules_list: list,
model_config: Optional[PretrainedConfig]) -> bool:
return type(source_layer) is AscendQKVParallelLinear and len(
packed_modules_list) == 1
class AscendMergedQKVParallelLinearWithLoRA(MergedQKVParallelLinearWithLoRA):
@classmethod
@_not_fully_sharded_can_replace
def can_replace_layer(
cls,
source_layer: nn.Module,
lora_config: LoRAConfig,
packed_modules_list: list,
model_config: Optional[PretrainedConfig],
) -> bool:
return (type(source_layer) is AscendQKVParallelLinear
and len(packed_modules_list) == 3)
def refresh_all_lora_classes():
vllm.lora.utils._all_lora_classes.add(AscendColumnParallelLinearWithLoRA)
vllm.lora.utils._all_lora_classes.add(
AscendMergedColumnParallelLinearWithLoRA)
vllm.lora.utils._all_lora_classes.add(AscendRowParallelLinearWithLoRA)
vllm.lora.utils._all_lora_classes.add(AscendVocabParallelEmbeddingWithLoRA)
vllm.lora.utils._all_lora_classes.add(AscendQKVParallelLinearWithLoRA)
vllm.lora.utils._all_lora_classes.add(
AscendMergedQKVParallelLinearWithLoRA)