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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

[Bugfix] Fix test_mixtral_moe (#24371)

Jee Jee Li committed Sep 7, 2025 at 00:32 UTC 7555d6b34af1aad14786a9451ff69968316a3ab4
1 file changed +2 -2
tests/kernels/moe/test_moe.py
+2 -2
@@ -371,8 +371,8 @@ def test_fused_moe_wn16(m: int, n: int, k: int, e: int, topk: int,
371 @pytest.mark.parametrize(
372 "use_rocm_aiter", [True, False] if current_platform.is_rocm() else [False])
373 @torch.inference_mode()
374 -def test_mixtral_moe(dtype: torch.dtype, padding: bool, use_rocm_aiter: bool,
375 - monkeypatch):
374 +def test_mixtral_moe(dist_init, dtype: torch.dtype, padding: bool,
375 + use_rocm_aiter: bool, monkeypatch):
376 """Make sure our Mixtral MoE implementation agrees with the one from
377 huggingface."""
378