EngineX/xc-llm-ascend
3
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[1/N][Refactor] Refactor code to adapt with vllm main (#3612)

Browse Source 
### What this PR does / why we need it?
This is the step 1 of refactoring code to adapt with vllm main, and this
pr aligned with
17c540a993

1. refactor deepseek to the latest code arch as of
17c540a993
 
2. bunches of fixes due to vllm changes
- Fix `AscendScheduler` `__post_init__`, caused by
https://github.com/vllm-project/vllm/pull/25075
- Fix `AscendScheduler` init got an unexpected arg `block_size`, caused
by https://github.com/vllm-project/vllm/pull/26296
- Fix `KVCacheManager` `get_num_common_prefix_blocks` arg, caused by
https://github.com/vllm-project/vllm/pull/23485
- Fix `MLAAttention` import,caused by
https://github.com/vllm-project/vllm/pull/25103
- Fix `SharedFusedMoE` import, caused by
https://github.com/vllm-project/vllm/pull/26145
- Fix `LazyLoader` improt, caused by
https://github.com/vllm-project/vllm/pull/27022
- Fix `vllm.utils.swap_dict_values` improt, caused by
https://github.com/vllm-project/vllm/pull/26990
- Fix `Backend` enum import, caused by
https://github.com/vllm-project/vllm/pull/25893
- Fix `CompilationLevel` renaming to `CompilationMode` issue introduced
by https://github.com/vllm-project/vllm/pull/26355
- Fix fused_moe ops, caused by
https://github.com/vllm-project/vllm/pull/24097
- Fix bert model because of `inputs_embeds`, caused by
https://github.com/vllm-project/vllm/pull/25922
- Fix MRope because of `get_input_positions_tensor` to
`get_mrope_input_positions`, caused by
https://github.com/vllm-project/vllm/pull/24172
- Fix `splitting_ops` changes introduced by
https://github.com/vllm-project/vllm/pull/25845
- Fix multi-modality changes introduced by
https://github.com/vllm-project/vllm/issues/16229
- Fix lora bias dropping issue introduced by
https://github.com/vllm-project/vllm/pull/25807
- Fix structured ouput break introduced by
https://github.com/vllm-project/vllm/issues/26737

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

### How was this patch tested?
CI passed with existing test.


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: MengqingCao <cmq0113@163.com>
Signed-off-by: Icey <1790571317@qq.com>
Co-authored-by: Icey <1790571317@qq.com>
This commit is contained in:
Mengqing Cao
2025-10-24 16:55:08 +08:00
committed by GitHub
parent ec9ec78b53
commit cea0755b07
47 changed files with 1189 additions and 493 deletions
Download Patch File Download Diff File Expand all files Collapse all files

151
tests/ut/test_platform.py
View File

@@ -1,19 +1,19 @@
import importlib
import unittest
from datetime import timedelta
from unittest.mock import MagicMock, patch
import pytest
import torch
from torch.distributed import ProcessGroup
from torch.distributed.distributed_c10d import PrefixStore
from vllm.config import CompilationLevel
from vllm.config.compilation import CUDAGraphMode
from vllm.platforms import PlatformEnum
from tests.ut.base import TestBase
from vllm_ascend.platform import NPUPlatform
from vllm_ascend.utils import ASCEND_QUANTIZATION_METHOD
from vllm_ascend.utils import ASCEND_QUANTIZATION_METHOD, vllm_version_is
if vllm_version_is("0.11.0"):
from vllm.config.compilation import CompilationLevel
else:
from vllm.config.compilation import CompilationMode
class TestNPUPlatform(TestBase):
@@ -249,6 +249,7 @@ class TestNPUPlatform(TestBase):
vllm_config.parallel_config.enable_expert_parallel = False
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
# Use importlib.reload to reload the platform module, ensuring the mocked init_ascend_config method is used.
# Without this reload, when calling self.platform.check_and_update_config,
@@ -277,6 +278,7 @@ class TestNPUPlatform(TestBase):
vllm_config.model_config = None
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
with self.assertLogs(logger="vllm", level="WARNING") as cm:
from vllm_ascend import platform
@@ -300,6 +302,7 @@ class TestNPUPlatform(TestBase):
vllm_config.model_config.enforce_eager = True
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
with self.assertLogs(logger="vllm", level="INFO") as cm:
from vllm_ascend import platform
@@ -308,10 +311,18 @@ class TestNPUPlatform(TestBase):
self.platform.check_and_update_config(vllm_config)
self.assertTrue("Compilation disabled, using eager mode by default" in
cm.output[0])
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
if vllm_version_is("0.11.0"):
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
else:
self.assertEqual(
vllm_config.compilation_config.mode,
CompilationMode.NONE,
)
self.assertEqual(
vllm_config.compilation_config.cudagraph_mode,
CUDAGraphMode.NONE,
@@ -330,9 +341,14 @@ class TestNPUPlatform(TestBase):
)
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.model_config.enforce_eager = False
vllm_config.compilation_config.level = CompilationLevel.DYNAMO_ONCE
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
if vllm_version_is("0.11.0"):
vllm_config.compilation_config.level = CompilationLevel.DYNAMO_ONCE
else:
vllm_config.compilation_config.mode = CompilationMode.DYNAMO_TRACE_ONCE
with self.assertLogs(logger="vllm", level="WARNING") as cm:
from vllm_ascend import platform
@@ -340,10 +356,16 @@ class TestNPUPlatform(TestBase):
importlib.reload(platform)
self.platform.check_and_update_config(vllm_config)
self.assertTrue("NPU does not support" in cm.output[0])
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
if vllm_version_is("0.11.0"):
self.assertEqual(
vllm_config.compilation_config.level,
CompilationMode.NONE,
)
else:
self.assertEqual(
vllm_config.compilation_config.mode,
CompilationMode.NONE,
)
self.assertEqual(
vllm_config.compilation_config.cudagraph_mode,
CUDAGraphMode.NONE,
@@ -370,10 +392,17 @@ class TestNPUPlatform(TestBase):
self.assertTrue(
"cudagraph_mode is not support on NPU. falling back to NONE" in
cm.output[0])
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
if vllm_version_is("0.11.0"):
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
else:
self.assertEqual(
vllm_config.compilation_config.mode,
CompilationMode.NONE,
)
self.assertEqual(
vllm_config.compilation_config.cudagraph_mode,
CUDAGraphMode.NONE,
@@ -393,9 +422,14 @@ class TestNPUPlatform(TestBase):
mock_init_ascend.return_value = mock_ascend_config
vllm_config = TestNPUPlatform.mock_vllm_config()
vllm_config.model_config.enforce_eager = False
vllm_config.compilation_config.level = CompilationLevel.PIECEWISE
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
if vllm_version_is("0.11.0"):
vllm_config.compilation_config.level = CompilationLevel.PIECEWISE
else:
vllm_config.compilation_config.mode = CompilationMode.VLLM_COMPILE
with self.assertLogs(logger="vllm", level="INFO") as cm:
from vllm_ascend import platform
@@ -403,10 +437,17 @@ class TestNPUPlatform(TestBase):
importlib.reload(platform)
self.platform.check_and_update_config(vllm_config)
self.assertTrue("Torchair compilation enabled" in cm.output[0])
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
if vllm_version_is("0.11.0"):
self.assertEqual(
vllm_config.compilation_config.level,
CompilationLevel.NO_COMPILATION,
)
else:
self.assertEqual(
vllm_config.compilation_config.mode,
CompilationMode.NONE,
)
self.assertEqual(
vllm_config.compilation_config.cudagraph_mode,
CUDAGraphMode.NONE,
@@ -428,6 +469,7 @@ class TestNPUPlatform(TestBase):
vllm_config.cache_config.enable_prefix_caching = True
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
from vllm_ascend import platform
@@ -452,6 +494,7 @@ class TestNPUPlatform(TestBase):
vllm_config.parallel_config.worker_cls = "auto"
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
from vllm_ascend import platform
@@ -489,6 +532,7 @@ class TestNPUPlatform(TestBase):
vllm_config.parallel_config.tensor_parallel_size = 1
mock_init_recompute.return_value = MagicMock()
vllm_config.scheduler_config = MagicMock()
from vllm_ascend import platform
importlib.reload(platform)
@@ -609,8 +653,12 @@ class TestNPUPlatform(TestBase):
def test_get_punica_wrapper(self):
result = self.platform.get_punica_wrapper()
self.assertEqual(result,
"vllm_ascend.lora.punica_npu.PunicaWrapperNPU")
if vllm_version_is("0.11.0"):
self.assertEqual(
result, "vllm_ascend.lora.punica_npu.PunicaWrapperNPU0110")
else:
self.assertEqual(result,
"vllm_ascend.lora.punica_npu.PunicaWrapperNPU")
@patch("torch.npu.reset_peak_memory_stats")
@patch("torch.npu.max_memory_allocated")
@@ -674,54 +722,3 @@ class TestNPUPlatform(TestBase):
self.platform.get_static_graph_wrapper_cls(),
"vllm_ascend.compilation.acl_graph.ACLGraphWrapper",
)
@patch("torch.distributed.is_hccl_available", return_value=True)
@patch("torch_npu._C._distributed_c10d.ProcessGroupHCCL")
@patch("torch.distributed.ProcessGroup")
def test_successful_initialization(self, mock_pg, mock_pg_hccl, _):
mock_prefix = MagicMock(spec=PrefixStore)
mock_backend = MagicMock()
mock_pg_hccl.return_value = mock_backend
group_rank = 0
group_size = 4
mock_pg_instance = MagicMock(spec=ProcessGroup)
mock_pg.return_value = mock_pg_instance
# Use importlib.reload() to force-reload the platform module and ensure the mocked ProcessGroup is used.
# Without this reload, when executing self.platform.stateless_init_device_torch_dist_pg(),
# it would invoke the original unmocked ProcessGroup implementation instead of our test mock,
# which would cause the unit test to fail.
from vllm_ascend import platform
importlib.reload(platform)
result = self.platform.stateless_init_device_torch_dist_pg(
backend="hccl",
prefix_store=mock_prefix,
group_rank=group_rank,
group_size=group_size,
timeout=timedelta(seconds=30),
)
mock_pg.assert_called_once_with(mock_prefix, group_rank, group_size)
mock_pg_hccl.assert_called_once_with(mock_prefix, group_rank,
group_size, unittest.mock.ANY)
mock_backend._set_sequence_number_for_group.assert_called_once()
mock_pg_instance._register_backend.assert_called_once_with(
torch.device("npu"), unittest.mock.ANY, mock_backend)
self.assertEqual(result, mock_pg_instance)
@patch("torch.distributed.is_hccl_available", return_value=False)
def test_hccl_unavailable(self, _):
with self.assertRaises(AssertionError):
from vllm_ascend import platform
importlib.reload(platform)
self.platform.stateless_init_device_torch_dist_pg(
backend="hccl",
prefix_store=MagicMock(),
group_rank=0,
group_size=4,
timeout=timedelta(seconds=30),
)