From 10b67aa7a1708e9ecc470844f47c6b1347c5c0d4 Mon Sep 17 00:00:00 2001 From: ashwini rathi Date: Mon, 31 Aug 2026 11:33:48 +0530 Subject: [PATCH] xpu: move prefill-only model tests to the nightly-xpu-1-gpu grid (#36814) --- .../registered/xpu/test_xpu_classification.py | 2 +- test/registered/xpu/test_xpu_embedding.py | 2 +- test/registered/xpu/test_xpu_rerank.py | 22 +------------------ test/registered/xpu/test_xpu_reward.py | 2 +- 4 files changed, 4 insertions(+), 24 deletions(-) diff --git a/test/registered/xpu/test_xpu_classification.py b/test/registered/xpu/test_xpu_classification.py index 0018a4c80..de9d4952c 100644 --- a/test/registered/xpu/test_xpu_classification.py +++ b/test/registered/xpu/test_xpu_classification.py @@ -14,7 +14,7 @@ from sglang.test.ci.ci_register import register_xpu_ci from sglang.test.runners import HFRunner, SRTRunner from sglang.test.test_utils import CustomTestCase, empty_gpu_cache -register_xpu_ci(est_time=120, suite="stage-b-test-1-gpu-xpu") +register_xpu_ci(est_time=120, suite="nightly-xpu-1-gpu", nightly=True) MODEL_PATH = "jason9693/Qwen2.5-1.5B-apeach" TP_SIZE = 1 diff --git a/test/registered/xpu/test_xpu_embedding.py b/test/registered/xpu/test_xpu_embedding.py index 2ff0a11a5..a940efefc 100644 --- a/test/registered/xpu/test_xpu_embedding.py +++ b/test/registered/xpu/test_xpu_embedding.py @@ -17,7 +17,7 @@ from sglang.test.ci.ci_register import register_xpu_ci from sglang.test.runners import DEFAULT_PROMPTS, HFRunner, SRTRunner from sglang.test.test_utils import CustomTestCase, empty_gpu_cache, get_similarities -register_xpu_ci(est_time=180, suite="stage-b-test-1-gpu-xpu") +register_xpu_ci(est_time=180, suite="nightly-xpu-1-gpu", nightly=True) MODEL_PATH = "Alibaba-NLP/gte-Qwen2-1.5B-instruct" TP_SIZE = 1 diff --git a/test/registered/xpu/test_xpu_rerank.py b/test/registered/xpu/test_xpu_rerank.py index afbe8ea99..b67abe388 100644 --- a/test/registered/xpu/test_xpu_rerank.py +++ b/test/registered/xpu/test_xpu_rerank.py @@ -23,18 +23,7 @@ from sglang.test.ci.ci_register import register_xpu_ci from sglang.test.runners import TEST_RERANK_QUERY_DOCS, HFRunner, SRTRunner from sglang.test.test_utils import CustomTestCase, empty_gpu_cache - -def _xpu_total_gib() -> float: - if not torch.xpu.is_available(): - return 0.0 - return torch.xpu.get_device_properties(0).total_memory / (1024**3) - - -# fp32+Triton fits on B60 (22GiB) but hangs on B580 (~12GiB). -_LARGE_XPU_VRAM_GIB = 20.0 -_HAS_LARGE_XPU = _xpu_total_gib() >= _LARGE_XPU_VRAM_GIB - -register_xpu_ci(est_time=180, suite="stage-b-test-1-gpu-xpu") +register_xpu_ci(est_time=180, suite="nightly-xpu-1-gpu", nightly=True) MODEL_PATH = "Qwen/Qwen3-Reranker-0.6B" TP_SIZE = 1 @@ -168,10 +157,6 @@ class TestXPUDecoderRerank(CustomTestCase): self._assert_close_scores(prompts) -# Ported from test/manual/prefill_only/test_cross_encoder_models.py. -# fp32+triton fits on B60 (22GiB) but OOMs on B580 (~12GiB); bf16+intel_xpu on -# this encoder model does not match HF (tracked separately), so on <20GiB XPU -# the class is skipped rather than shipping a knowingly-wrong config. CROSS_ENCODER_MODEL_PATH = "BAAI/bge-reranker-v2-m3" CROSS_ENCODER_TP_SIZE = 1 CROSS_ENCODER_SCORE_TOLERANCE = 1e-2 @@ -180,11 +165,6 @@ CROSS_ENCODER_ATTENTION_BACKEND = "triton" CROSS_ENCODER_MEM_FRACTION_STATIC = 0.65 -@unittest.skipUnless( - _HAS_LARGE_XPU, - "bge-reranker-v2-m3 fp32+triton OOMs on <20GiB XPU (B580); " - "bf16+intel_xpu on this encoder produces wrong scores.", -) class TestXPUCrossEncoderRerank(CustomTestCase): @classmethod def setUpClass(cls): diff --git a/test/registered/xpu/test_xpu_reward.py b/test/registered/xpu/test_xpu_reward.py index 710406ed2..007b39ca2 100644 --- a/test/registered/xpu/test_xpu_reward.py +++ b/test/registered/xpu/test_xpu_reward.py @@ -15,7 +15,7 @@ from sglang.test.ci.ci_register import register_xpu_ci from sglang.test.runners import HFRunner, SRTRunner from sglang.test.test_utils import CustomTestCase, empty_gpu_cache -register_xpu_ci(est_time=60, suite="stage-b-test-1-gpu-xpu") +register_xpu_ci(est_time=60, suite="nightly-xpu-1-gpu", nightly=True) MODEL_PATH = "Skywork/Skywork-Reward-V2-Qwen3-0.6B" TP_SIZE = 1