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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 10, 12:45 UTC

[BugFix] Fix flakiness in test_eagle_dp for PyTorch 2.10 (#31915)

Signed-off-by: Richard Zou <zou3519@gmail.com>

Richard Zou committed Jan 7, 2026 at 23:04 UTC a79079feef63d7a8124782cf2eb1cd68cbde99ee
1 file changed +3 -1
tests/v1/distributed/test_eagle_dp.py
+3 -1
@@ -47,7 +47,9 @@ async def test_run_eagle_dp(monkeypatch: pytest.MonkeyPatch):
47 )
48
49 prompt = "This is a test of data parallel with eagle"
50 - num_expected_tokens = 100
50 + # This test might be flaky, see
51 + # https://github.com/vllm-project/vllm/issues/31913
52 + num_expected_tokens = 20
53 sampling_params = SamplingParams(
54 min_tokens=num_expected_tokens,
55 max_tokens=num_expected_tokens,