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Fix sgl-kernel ci test (#8284)

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This commit is contained in:
Ke Bao
2025-07-23 14:01:47 +08:00
committed by GitHub
parent e2d66f60c8
commit e885bfdc6a
1 changed files with 4 additions and 4 deletions
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8
sgl-kernel/tests/test_moe_fused_gate.py
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@@ -10,7 +10,6 @@ from sglang.srt.layers.moe.topk import biased_grouped_topk
list(range(1, 10)) list(range(1, 10))
+ [16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 16384, 32768, 65536], + [16, 32, 64, 128, 256, 512, 1024, 2048, 4096, 8192, 16384, 32768, 65536],
) )
@pytest.mark.parametrize("dtype", [torch.float16, torch.float32, torch.bfloat16])
@pytest.mark.parametrize( @pytest.mark.parametrize(
"params", "params",
[ [
@@ -20,13 +19,14 @@ from sglang.srt.layers.moe.topk import biased_grouped_topk
], ],
) )
@pytest.mark.parametrize("num_fused_shared_experts", [0, 1, 2]) @pytest.mark.parametrize("num_fused_shared_experts", [0, 1, 2])
def test_moe_fused_gate_combined(seq_length, dtype, params, num_fused_shared_experts): def test_moe_fused_gate_combined(seq_length, params, num_fused_shared_experts):
num_experts, num_expert_group, topk_group, topk = params num_experts, num_expert_group, topk_group, topk = params
dtype = torch.float32
torch.manual_seed(seq_length) torch.manual_seed(seq_length)
tensor = torch.rand((seq_length, num_experts)).to(dtype).cuda() tensor = torch.rand((seq_length, num_experts), dtype=dtype, device="cuda")
scores = tensor.clone() scores = tensor.clone()
bias = torch.rand(num_experts).to(dtype).cuda() bias = torch.rand(num_experts, dtype=dtype, device="cuda")
topk = topk + num_fused_shared_experts topk = topk + num_fused_shared_experts
output, indices = moe_fused_gate( output, indices = moe_fused_gate(