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CustomOp: test forward dispatch for grouped_topk #31530

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yewentao256 merged 2 commits into from
Jan 2, 2026
Merged

CustomOp: test forward dispatch for grouped_topk #31530

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CustomOp: test forward dispatch for grouped_topk
xinyu-intel Dec 30, 2025
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xinyu-intel Dec 30, 2025
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14 changes: 13 additions & 1 deletion tests/kernels/moe/test_grouped_topk.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,12 @@
import pytest
import torch

from vllm.config import (
CompilationConfig,
VllmConfig,
get_cached_compilation_config,
set_current_vllm_config,
)
from vllm.model_executor.layers.fused_moe.fused_moe import (
GroupedTopk,
fused_grouped_topk,
Expand Down Expand Up @@ -41,14 +47,19 @@ def test_grouped_topk(
routed_scaling_factor: float,
dtype: torch.dtype,
):
vllm_config = VllmConfig(
compilation_config=CompilationConfig(custom_ops=["all", "+grouped_topk"])
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@tjtanaa tjtanaa Dec 30, 2025

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I think we don't need to add "all" as we are only testing "grouped_topk". All will enable all custom ops. We should also test with only +grouped_topk.

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@xinyu-intel xinyu-intel Dec 31, 2025

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good catch:)

)
get_cached_compilation_config.cache_clear()

current_platform.seed_everything(0)
hidden_states = torch.randn((n_token, n_hidden), dtype=dtype, device="cuda")
gating_output = torch.randn((n_token, n_expert), dtype=dtype, device="cuda")
e_score_correction_bias = torch.randn(
(n_expert,), dtype=torch.float32, device="cuda"
)

with monkeypatch.context() as m:
with set_current_vllm_config(vllm_config), monkeypatch.context() as m:
m.setenv("VLLM_USE_FUSED_MOE_GROUPED_TOPK", "0")
grouped_topk = GroupedTopk(
topk=topk,
Expand All @@ -58,6 +69,7 @@ def test_grouped_topk(
scoring_func=scoring_func,
routed_scaling_factor=routed_scaling_factor,
)
assert grouped_topk._forward_method.__name__ == "forward_cuda"
baseline_topk_weights, baseline_topk_ids = grouped_topk(
hidden_states=hidden_states,
gating_output=gating_output,
Expand Down