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

### 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>

tests/e2e/multicard/test_qwen3_next.py

@@ -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",

tests/ut/attention/test_mla_v1.py

@@ -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)

tests/ut/models/test_qwen2_5_vl.py

@@ -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__")

tests/ut/quantization/test_w4a8_dynamic.py

@@ -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')

tests/ut/test_utils.py

@@ -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",
+        # Case when _ENABLE_NZ is already set
-                        1):
+        utils._ENABLE_NZ = True
-            self.assertTrue(utils.is_enable_nz())
+        self.assertTrue(utils.is_enable_nz())
-        with mock.patch("vllm_ascend.utils.envs_ascend.VLLM_ASCEND_ENABLE_NZ",
+
-                        0):
+        utils._ENABLE_NZ = False
-            self.assertFalse(utils.is_enable_nz())
+        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

tests/ut/worker/test_worker_v1.py

@@ -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"""

vllm_ascend/utils.py

@@ -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():
+def is_enable_nz(vllm_config: Optional[VllmConfig] = None) -> bool:
-    return envs_ascend.VLLM_ASCEND_ENABLE_NZ
+    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():

vllm_ascend/worker/worker_v1.py

@@ -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()