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Remove unused row_idx in token_dispatcher (#3442)

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### What this PR does / why we need it?
The `row_idx` parameter is no longer used since
PR[#2689](https://github.com/vllm-project/vllm-ascend/pull/2689), so
remove it across multiple files to remove unnecessary calculations and
parameter passing.

### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
accuracy test passed for Qwen3 235B and DeepSeek V3 671B after this PR.


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

---------

Signed-off-by: CaranLic <740821011@qq.com>
This commit is contained in:
CaranLic
2025-10-15 09:08:31 +08:00
committed by GitHub
parent 3642b64afc
commit 15b2e5c995
11 changed files with 37 additions and 88 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
tests/ut/ops/test_token_dispatcher.py
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@@ -58,7 +58,6 @@ class TestTokenDispatcherWithMC2(TestBase):
kwargs = {"with_quant": False, "top_k": 8, "num_experts": 128}
self.dispatcher = TokenDispatcherWithMC2(**kwargs)
self.row_idx = torch.arange(10, dtype=torch.int32)
def tearDown(self):
self.mc2_group_patch.stop()
@@ -96,7 +95,7 @@ class TestTokenDispatcherWithMC2(TestBase):
(None, None)) as mock_dispatch:
output = self.dispatcher.token_dispatch(hidden_states,
topk_weights, topk_ids,
self.row_idx, expert_map)
expert_map)
mock_dispatch.assert_called_once()
self.assertEqual(output["group_list_type"],
0) # group_list_type == 0
@@ -117,7 +116,6 @@ class TestTokenDispatcherWithMC2(TestBase):
self.dispatcher.token_dispatch(self.hidden_states,
self.topk_weights,
torch.randint(0, 8, (10, 1)),
self.row_idx,
torch.tensor(
[0, 1, 2, 3, 4, 5, 6, 7]),
shared_experts=self.shared_experts)
@@ -181,7 +179,6 @@ class TestTokenDispatcherWithAllGather(TestBase):
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]))
self.row_idx = torch.arange(10, dtype=torch.int32)
self.patcher_npu_moe_token_unpermute = patch(
'torch_npu.npu_moe_token_unpermute')
self.mock_npu_moe_token_unpermute = self.patcher_npu_moe_token_unpermute.start(
@@ -198,7 +195,7 @@ class TestTokenDispatcherWithAllGather(TestBase):
topk_ids = torch.tensor([[0, 1], [1, 2], [2, 3]])
results = self.dispatcher.token_dispatch(hidden_states, topk_weights,
topk_ids, self.row_idx, None)
topk_ids, None)
# Verify npu_moe_init_routing is called
self.mock_npu_moe_init_routing_v2.assert_called_once()
@@ -213,7 +210,7 @@ class TestTokenDispatcherWithAllGather(TestBase):
topk_ids = torch.tensor([[0, 1], [1, 2], [2, 3]])
results = self.dispatcher.token_dispatch(hidden_states, topk_weights,
topk_ids, self.row_idx, None)
topk_ids, None)
# Verify npu_moe_init_routing is called
self.mock_npu_moe_init_routing_v2.assert_called_once()
@@ -237,7 +234,7 @@ class TestTokenDispatcherWithAllGather(TestBase):
results = self.dispatcher_quant.token_dispatch(hidden_states,
topk_weights, topk_ids,
self.row_idx, None)
None)
self.assertEqual(results["group_list_type"], 1)
@@ -258,7 +255,6 @@ class TestTokenDispatcherWithAllGather(TestBase):
results = self.dispatcher_quant.token_dispatch(hidden_states,
topk_weights,
topk_ids,
self.row_idx,
None,
with_quant=True)
@@ -401,7 +397,6 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
num_experts=4,
num_local_experts=2,
with_quant=False)
self.row_idx = torch.arange(10, dtype=torch.int32)
def test_token_dispatch(self):
hidden_states = torch.randn(8, 16)
@@ -416,7 +411,6 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
result = self.dispatcher.token_dispatch(hidden_states=hidden_states,
topk_weights=topk_weights,
topk_ids=topk_ids,
row_idx=self.row_idx,
expert_map=expert_map)
self.assertIsNotNone(result["hidden_states"])
@@ -463,7 +457,6 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
result = self.dispatcher.token_dispatch(hidden_states=hidden_states,
topk_weights=topk_weights,
topk_ids=topk_ids,
row_idx=self.row_idx,
expert_map=expert_map,
with_quant=True)
@@ -492,7 +485,6 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
result = self.dispatcher.token_dispatch(hidden_states=hidden_states,
topk_weights=topk_weights,
topk_ids=topk_ids,
row_idx=self.row_idx,
expert_map=expert_map,
with_quant=True)
@@ -515,7 +507,6 @@ class TestTokenDispatcherWithAll2AllV(TestBase):
result = self.dispatcher.token_dispatch(hidden_states=hidden_states,
topk_weights=topk_weights,
topk_ids=topk_ids,
row_idx=self.row_idx,
expert_map=expert_map,
log2phy=log2phy)