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[OP] Enable custom op aclnnMoeInitRoutingCustom (#5332)

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### What this PR does / why we need it?
This PR enables custom op `aclnnMoeInitRoutingCustom` introduced in PR
#5251

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

### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08

---------

Signed-off-by: QianChenxi <chenxi.qian.cq@outlook.com>
Signed-off-by: zzzzwwjj <1183291235@qq.com>
Co-authored-by: zzzzwwjj <1183291235@qq.com>
This commit is contained in:
Chenxi Qian
2026-01-09 09:35:18 +08:00
committed by GitHub
parent 595d3484c4
commit 40eb3e1836
3 changed files with 16 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
tests/e2e/singlecard/test_aclgraph_accuracy.py
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@@ -36,10 +36,10 @@ CASE_DS_ACLGRAPH = LLMTestCase(
quantization="ascend", quantization="ascend",
prompts=PROMPTS_SHORT, prompts=PROMPTS_SHORT,
golden_answers=[ golden_answers=[
'\nI am a 20 year old student from the UK. I am currently studying for a degree in English Literature and Creative Writing. I have a passion', '\nI am a 20 year old female, and I have been suffering from depression for 3 years now. I have been on medication for 2',
' a man who has been in the public eye for decades. He has been a senator, a governor, and a businessman. He has also been married to the', ' a man who has been in the public eye for decades. He has been a senator, a governor, and a businessman. He has also been married to the',
' Paris, which is also the largest city in the country. The city is located on the River Seine and is known for its beautiful architecture, museums, and art', ' Paris, which is also the largest city in the country. The city is located on the River Seine and is known for its beautiful architecture, museums, and art',
' here.\nThe future of AI is here.\nThe future of AI is here.\nThe future of AI is here.\nThe future of AI is' ' here, and it’s not what you think.\nThe future of AI is here, and it’s not what you think.\nThe future of'
], ],
) )

26
tests/ut/ops/test_token_dispatcher.py
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@@ -164,11 +164,11 @@ class TestTokenDispatcherWithAllGather(TestBase):
self.dispatcher = TokenDispatcherWithAllGather(**kwargs) self.dispatcher = TokenDispatcherWithAllGather(**kwargs)
# Mock NPU functions # Mock NPU functions
self.patcher_npu_moe_init_routing_v2 = patch( self.patcher_npu_moe_init_routing_custom = patch(
'torch_npu.npu_moe_init_routing_v2') 'torch.ops._C_ascend.npu_moe_init_routing_custom')
self.mock_npu_moe_init_routing_v2 = self.patcher_npu_moe_init_routing_v2.start( self.mock_npu_moe_init_routing_custom = self.patcher_npu_moe_init_routing_custom.start(
) )
self.mock_npu_moe_init_routing_v2.return_value = ( self.mock_npu_moe_init_routing_custom.return_value = (
torch.randn(6, 128), # sorted_hidden_states torch.randn(6, 128), # sorted_hidden_states
torch.tensor([0, 1, 2, 3, 4, 5]), # expanded_row_idx torch.tensor([0, 1, 2, 3, 4, 5]), # expanded_row_idx
torch.tensor([0, 1, 0, 1, 0, 1]), # expanded_expert_idx torch.tensor([0, 1, 0, 1, 0, 1]), # expanded_expert_idx
@@ -180,7 +180,7 @@ class TestTokenDispatcherWithAllGather(TestBase):
self.mock_npu_moe_token_unpermute.return_value = torch.randn(6, 128) self.mock_npu_moe_token_unpermute.return_value = torch.randn(6, 128)
def tearDown(self): def tearDown(self):
self.patcher_npu_moe_init_routing_v2.stop() self.patcher_npu_moe_init_routing_custom.stop()
self.patcher_npu_moe_token_unpermute.stop() self.patcher_npu_moe_token_unpermute.stop()
def test_token_dispatch_without_expert_map(self): def test_token_dispatch_without_expert_map(self):
@@ -192,8 +192,8 @@ class TestTokenDispatcherWithAllGather(TestBase):
topk_ids, None) topk_ids, None)
# Verify npu_moe_init_routing is called # Verify npu_moe_init_routing is called
self.mock_npu_moe_init_routing_v2.assert_called_once() self.mock_npu_moe_init_routing_custom.assert_called_once()
args, kwargs = self.mock_npu_moe_init_routing_v2.call_args args, kwargs = self.mock_npu_moe_init_routing_custom.call_args
self.assertEqual(results.group_list_type, 1) self.assertEqual(results.group_list_type, 1)
@@ -207,8 +207,8 @@ class TestTokenDispatcherWithAllGather(TestBase):
topk_ids, None) topk_ids, None)
# Verify npu_moe_init_routing is called # Verify npu_moe_init_routing is called
self.mock_npu_moe_init_routing_v2.assert_called_once() self.mock_npu_moe_init_routing_custom.assert_called_once()
args, kwargs = self.mock_npu_moe_init_routing_v2.call_args args, kwargs = self.mock_npu_moe_init_routing_custom.call_args
self.assertEqual(results.group_list_type, 1) self.assertEqual(results.group_list_type, 1)
@@ -366,11 +366,11 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
self.mock_npu_dynamic_quant.return_value = (torch.randn(16, 16), self.mock_npu_dynamic_quant.return_value = (torch.randn(16, 16),
torch.randn(16)) torch.randn(16))
# Mock torch_npu.npu_moe_init_routing_v2 # Mock torch.ops._C_ascend.npu_moe_init_routing_custom
patcher11 = patch('torch_npu.npu_moe_init_routing_v2') patcher11 = patch('torch.ops._C_ascend.npu_moe_init_routing_custom')
self.mock_npu_moe_init_routing_v2 = patcher11.start() self.mock_npu_moe_init_routing_custom = patcher11.start()
self.addCleanup(patcher11.stop) self.addCleanup(patcher11.stop)
self.mock_npu_moe_init_routing_v2.return_value = (torch.randn( self.mock_npu_moe_init_routing_custom.return_value = (torch.randn(
16, 16), torch.arange(16), None, torch.randn(16)) 16, 16), torch.arange(16), None, torch.randn(16))
# Mock torch.repeat_interleave # Mock torch.repeat_interleave

2
vllm_ascend/ops/fused_moe/token_dispatcher.py
View File

@@ -354,7 +354,7 @@ class TokenDispatcherWithAllGather(MoETokenDispatcher):
global_num_experts = self.num_experts_local global_num_experts = self.num_experts_local
sorted_hidden_states, expanded_row_idx, expert_tokens, pertoken_scale = ( sorted_hidden_states, expanded_row_idx, expert_tokens, pertoken_scale = (
torch_npu.npu_moe_init_routing_v2( torch.ops._C_ascend.npu_moe_init_routing_custom(
hidden_states, hidden_states,
topk_ids, topk_ids,
scale=pertoken_scale, scale=pertoken_scale,