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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 14, 05:30 UTC

[CI] Retry flaky fp8 cutlass mla tests (#24536)

Signed-off-by: Nick Hill <nhill@redhat.com>

Nick Hill committed Sep 9, 2025 at 20:33 UTC 7e7db04310922f45524d4bfbe72f1dc7205ae7d6
1 file changed +7 -1
tests/kernels/test_cutlass_mla_decode.py
+7 -1
@@ -49,7 +49,13 @@ CUTLASS_MLA_UNSUPPORTED_REASON = \
49 @pytest.mark.parametrize("block_size", [64])
50 @pytest.mark.parametrize("causal", [True])
51 @pytest.mark.parametrize("varlen", [False, True])
52 -@pytest.mark.parametrize("torch_dtype", [torch.bfloat16, torch.float8_e4m3fn])
52 +@pytest.mark.parametrize(
53 + "torch_dtype",
54 + [
55 + torch.bfloat16,
56 + # fp8 can have occasional precision-related failures.
57 + pytest.param(torch.float8_e4m3fn, marks=pytest.mark.flaky(reruns=2))
58 + ])
59 @torch.inference_mode()
60 def test_cutlass_mla_decode(b, s_q, mean_sk, h_q, h_kv, d, dv, block_size,
61 causal, varlen, torch_dtype):