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[BugFix] Fixes Qwen3-Next enable nz accuracy problem (#4058)

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### What this PR does / why we need it?
- Fixes Qwen3-Next enable nz accuracy problem

### Does this PR introduce _any_ user-facing change?
N/A


- vLLM version: v0.11.0
- vLLM main:
83f478bb19

---------

Signed-off-by: Icey <1790571317@qq.com>
Signed-off-by: wxsIcey <1790571317@qq.com>
This commit is contained in:
Icey
2025-11-10 20:54:57 +08:00
committed by GitHub
parent e6625bb582
commit e04a87f4be
8 changed files with 36 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
tests/e2e/multicard/test_qwen3_next.py
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@@ -20,17 +20,9 @@
Run `pytest tests/e2e/multicard/test_qwen3_next.py`.
"""
import os
from unittest.mock import patch
from tests.e2e.conftest import VllmRunner
# NZ will cause precision error in Qwen3-Next
# When it is fixed, this set-up can be removed
_IS_ENABLE_NZ = "VLLM_ASCEND_ENABLE_NZ"
@patch.dict(os.environ, {_IS_ENABLE_NZ: "0"})
def test_models_distributed_Qwen3_NEXT_TP4():
example_prompts = [
"Hello, my name is",
@@ -46,7 +38,6 @@ def test_models_distributed_Qwen3_NEXT_TP4():
del vllm_model
@patch.dict(os.environ, {_IS_ENABLE_NZ: "0"})
def test_models_distributed_Qwen3_NEXT_TP4_FULL_DECODE_ONLY():
example_prompts = [
"Hello, my name is",
@@ -66,7 +57,6 @@ def test_models_distributed_Qwen3_NEXT_TP4_FULL_DECODE_ONLY():
del vllm_model
@patch.dict(os.environ, {_IS_ENABLE_NZ: "0"})
def test_models_distributed_Qwen3_NEXT_MTP_TP4_SIMILARITY():
example_prompts = [
"Hello, my name is",

1
tests/ut/attention/test_mla_v1.py
View File

@@ -416,6 +416,7 @@ class TestAscendMLAImpl(TestBase):
self.assertEqual(q_pe.shape[1], self.impl.num_heads)
self.assertEqual(q_pe.shape[2], self.impl.qk_rope_head_dim)
@patch('vllm_ascend.utils._ENABLE_NZ', True)
@patch('torch_npu.npu_format_cast')
def test_process_weights_after_loading(self, mock_format_cast):
layer = MagicMock(spec=LinearBase)

4
tests/ut/models/test_qwen2_5_vl.py
View File

@@ -1,3 +1,5 @@
from unittest.mock import patch
import pytest
import torch
import torch.nn.functional as F
@@ -365,6 +367,7 @@ class TestAscendQwen2_5_VisionTransformer(PytestBase):
res = attention.pad_qkv_bias(torch.rand((300)))
assert res.shape[0] == 384
@patch('vllm_ascend.utils._ENABLE_NZ', True)
def test_pad_qkv_weight(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")
@@ -377,6 +380,7 @@ class TestAscendQwen2_5_VisionTransformer(PytestBase):
res = attention.pad_qkv_weight(torch.rand((300, 300)))
assert res.shape == (384, 300)
@patch('vllm_ascend.utils._ENABLE_NZ', True)
def test_pad_proj_weight(self, mocker: MockerFixture):
attention = self.init_vision_transformer(mocker)
mocker.patch("torch.nn.Module.__setattr__")

1
tests/ut/quantization/test_w4a8_dynamic.py
View File

@@ -260,6 +260,7 @@ class TestAscendW4A8DynamicFusedMoEMethod(TestBase):
requires_grad=False)
return layer
@patch('vllm_ascend.utils._ENABLE_NZ', False)
@patch('torch_npu.npu_format_cast')
@patch('torch_npu.npu_quantize')
@patch('torch.Tensor.npu')

18
tests/ut/test_utils.py
View File

@@ -46,12 +46,18 @@ class TestUtils(TestBase):
self.assertFalse(utils.is_310p())
def test_is_enable_nz(self):
with mock.patch("vllm_ascend.utils.envs_ascend.VLLM_ASCEND_ENABLE_NZ",
1):
self.assertTrue(utils.is_enable_nz())
with mock.patch("vllm_ascend.utils.envs_ascend.VLLM_ASCEND_ENABLE_NZ",
0):
self.assertFalse(utils.is_enable_nz())
# Case when _ENABLE_NZ is already set
utils._ENABLE_NZ = True
self.assertTrue(utils.is_enable_nz())
utils._ENABLE_NZ = False
self.assertFalse(utils.is_enable_nz())
# Case when _ENABLE_NZ is None and vllm_config is not provided
utils._ENABLE_NZ = None
with self.assertRaises(ValueError) as context:
utils.is_enable_nz()
self.assertIn("vllm_config must be provided", str(context.exception))
def test_sleep_mode_enabled(self):
utils._SLEEP_MODE_ENABLED = None

10
tests/ut/worker/test_worker_v1.py
View File

@@ -20,7 +20,13 @@ class TestNPUWorker(TestBase):
self.model_config_mock = MagicMock(spec=ModelConfig)
self.model_config_mock.dtype = torch.float16
self.model_config_mock.trust_remote_code = False
self.model_config_mock.hf_config = None
self.hf_config_mock = MagicMock()
self.hf_config_mock.model_type = "test_model"
if hasattr(self.hf_config_mock, 'index_topk'):
delattr(self.hf_config_mock, 'index_topk')
self.model_config_mock.hf_config = self.hf_config_mock
self.parallel_config_mock = MagicMock(spec=ParallelConfig)
@@ -272,9 +278,9 @@ class TestNPUWorker(TestBase):
self.assertIn("Sleep mode is not enabled", str(cm.exception))
@patch('vllm_ascend.utils._ENABLE_NZ', False)
@patch("vllm_ascend.worker.worker_v1.sleep_mode_enabled")
@patch("vllm_ascend.worker.worker_v1.CaMemAllocator")
@patch.dict(os.environ, {"VLLM_ASCEND_ENABLE_NZ": "0"})
def test_wake_up_mode_enabled(self, mock_allocator_class,
mock_sleep_mode_enabled):
"""Test wake_up method when sleep mode is enabled"""

11
vllm_ascend/utils.py
View File

@@ -59,6 +59,7 @@ _MIN_DP_BUFFER_SIZE = 50
_IS_MOE_MODEL = None
_ENABLE_SP = None
_HAS_LAYER_IDX = None
_ENABLE_NZ = None
def is_310p():
@@ -69,8 +70,14 @@ def is_310p():
return _IS_310P
def is_enable_nz():
return envs_ascend.VLLM_ASCEND_ENABLE_NZ
def is_enable_nz(vllm_config: Optional[VllmConfig] = None) -> bool:
global _ENABLE_NZ
if _ENABLE_NZ is None:
if not vllm_config:
raise ValueError(
"vllm_config must be provided when _ENABLE_NZ is None")
_ENABLE_NZ = envs_ascend.VLLM_ASCEND_ENABLE_NZ and vllm_config.model_config.hf_config.model_type != "qwen3_next"
return _ENABLE_NZ
def sleep_mode_enabled():

1
vllm_ascend/worker/worker_v1.py
View File

@@ -87,6 +87,7 @@ class NPUWorker(WorkerBase):
# register patch for vllm
from vllm_ascend.utils import adapt_patch
adapt_patch()
is_enable_nz(vllm_config)
# Register ops when worker init.
from vllm_ascend import ops
ops.register_dummy_fusion_op()