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[refact] unified soc_version code (#4359)

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### What this PR does / why we need it?

Currently, there are two paths to judge the chip type in code,
`get_ascend_soc_version` use `get_soc_version` api in torch_npu, and
`is_310p` `use _build_info.__soc_version__`, which generate when
install. We need to unify the two paths.

We need to unify these codes based on the following points:

1. We need to ensure consistency in chip type judgment between compiling
and running states;
2. In compiling state, we need chip type to complete op's compilation,
but in running state, we only need device
type(910B/910_93/310P/910_95/etc) to make code branch judgement;
3. In compiling state, torch_npu may not have been installed yet, so we
can't use torch_npu's api.

Based on the above points, we have made the following changes:

1. When user set env `SOC_VERSION`, use it; when not set, query
soc_version by `npu-smi`;
2. generate device_type based on soc_version when compiling, and write
`__device_type__` instead of `__soc_version__` in `_build_info.py`;
3. In running state, use `__device_type__` to judge code branch.

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

When not set env `SOC_VERSION`, it will not be `ASCEND910B1` by default,
we will query soc_version by `npu-smi`. And env `SOC_VERSION` must be in
the list `soc_to_device` in `setup.py`.

- vLLM version: v0.11.0
- vLLM main:
2918c1b49c

Signed-off-by: zzzzwwjj <1183291235@qq.com>
This commit is contained in:
zzzzwwjj
2025-11-26 14:28:55 +08:00
committed by GitHub
parent a91e76cd84
commit 136ea9ff56
42 changed files with 361 additions and 243 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
tests/ut/ops/test_fused_moe.py
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@@ -29,7 +29,7 @@ from vllm_ascend.ops.fused_moe.fused_moe import (
AscendFusedMoE, AscendUnquantizedFusedMoEMethod)
from vllm_ascend.ops.fused_moe.moe_mlp import (cumsum_group_list,
unified_apply_mlp)
from vllm_ascend.utils import AscendSocVersion, adapt_patch
from vllm_ascend.utils import AscendDeviceType, adapt_patch
adapt_patch(True)
@@ -129,7 +129,7 @@ def mock_dist_env(mocker: MockerFixture):
return_value=mock_forward_context_obj), \
patch('vllm_ascend.ops.fused_moe.prepare_finalize.get_forward_context',
return_value=mock_forward_context_obj), \
patch("vllm_ascend.utils.get_ascend_soc_version", return_value=AscendSocVersion.A3), \
patch("vllm_ascend.utils.get_ascend_device_type", return_value=AscendDeviceType._910_93), \
patch('vllm_ascend.ops.fused_moe.moe_mlp.get_forward_context',
return_value=mock_forward_context_obj), \
patch('vllm_ascend.ops.fused_moe.moe_comm_method.MC2CommImpl._get_token_dispatcher',
@@ -323,22 +323,21 @@ class TestCumsumGroupList(TestBase):
class TestUnifiedApplyMLP(TestBase):
@patch('vllm_ascend.ops.fused_moe.moe_mlp.get_forward_context')
@patch('vllm_ascend.ops.fused_moe.moe_mlp.is_310p')
@patch('vllm_ascend.utils.get_ascend_device_type',
return_value=AscendDeviceType._910_93)
@patch('torch_npu.npu_grouped_matmul')
@patch('torch_npu.npu_dynamic_quant')
@patch('torch_npu.npu_dequant_swiglu_quant')
def test_unified_apply_mlp_with_quantization_mc2(self, mock_npu_dequant,
mock_npu_dynamic_quant,
mock_npu_grouped_matmul,
mock_is_310p,
mock_soc_version,
mock_get_forward_context):
mock_forward_context = MagicMock()
mock_forward_context.moe_comm_type = MoECommType.MC2
mock_get_forward_context.return_value = mock_forward_context
mock_is_310p.return_value = False
mock_npu_dynamic_quant.return_value = (torch.randint(-128,
127, (10, 20),
dtype=torch.int8),
@@ -387,7 +386,8 @@ class TestUnifiedApplyMLP(TestBase):
self.assertEqual(result.dtype, torch.bfloat16)
@patch('vllm_ascend.ops.fused_moe.moe_mlp.is_310p')
@patch('vllm_ascend.utils.get_ascend_device_type',
return_value=AscendDeviceType._910_93)
@patch('torch_npu.npu_grouped_matmul')
@patch('torch_npu.npu_swiglu')
@patch('torch_npu.npu_dynamic_quant')
@@ -395,9 +395,7 @@ class TestUnifiedApplyMLP(TestBase):
mock_npu_dynamic_quant,
mock_npu_swiglu,
mock_npu_grouped_matmul,
mock_is_310p):
mock_is_310p.return_value = False
mock_soc_version):
mock_npu_grouped_matmul.side_effect = [[
torch.randn(10, 40, dtype=torch.float16)
], [torch.randn(10, 20, dtype=torch.float16)]]
@@ -490,15 +488,14 @@ class TestUnifiedApplyMLP(TestBase):
self.assertEqual(result.shape, hidden_states_shape)
self.assertEqual(result.dtype, torch.bfloat16)
@patch('vllm_ascend.ops.fused_moe.moe_mlp.is_310p')
@patch('vllm_ascend.utils.get_ascend_device_type',
return_value=AscendDeviceType._310P)
@patch('torch_npu.npu_grouped_matmul')
@patch('torch_npu.npu_swiglu')
@patch('torch_npu.npu_dynamic_quant')
def test_unified_apply_mlp_without_quantization_310p(
self, mock_npu_dynamic_quant, mock_npu_swiglu,
mock_npu_grouped_matmul, mock_is_310p):
mock_is_310p.return_value = True
mock_npu_grouped_matmul, mock_soc_version):
mock_gmm1_out = torch.randn(10, 40, dtype=torch.float16)
mock_gmm2_out = torch.randn(10, 20, dtype=torch.float16)
mock_npu_grouped_matmul.side_effect = [[mock_gmm1_out],
@@ -527,8 +524,6 @@ class TestUnifiedApplyMLP(TestBase):
topk_scales=topk_scales,
with_quant=False)
mock_is_310p.assert_called_once()
self.assertEqual(mock_npu_grouped_matmul.call_count, 2)
mock_npu_swiglu.assert_called_once()