[CI] Fix sanity evaluation and diffusion test suite blockers (#39892)
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@@ -1,7 +1,7 @@
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"""Stage-a basic sanity: small-but-broad server coverage that downstream
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stages depend on. Multiple sanity-kit mixins driving one shared server,
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covering protocol, decode correctness, scheduler stress, occupancy, and
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hellaswag accuracy."""
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MMLU accuracy."""
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import unittest
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@@ -10,8 +10,8 @@ from sglang.test.ci.ci_register import register_amd_ci, register_cuda_ci
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from sglang.test.kits.basic_api_contract_kit import BasicAPIContractMixin
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from sglang.test.kits.basic_decode_correctness_kit import BasicDecodeCorrectnessMixin
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from sglang.test.kits.basic_scheduler_stress_kit import BasicSchedulerStressMixin
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from sglang.test.kits.eval_accuracy_kit import _run_sgl_eval
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from sglang.test.kits.fwd_occupancy_kit import FwdOccupancyMixin
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from sglang.test.kits.hellaswag_kit import HellaswagMixin
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from sglang.test.test_utils import (
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DEFAULT_MODEL_NAME_FOR_TEST,
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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@@ -29,7 +29,6 @@ class TestBasicSanity(
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BasicDecodeCorrectnessMixin,
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BasicSchedulerStressMixin,
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FwdOccupancyMixin,
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HellaswagMixin,
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CustomTestCase,
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):
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served_model_name = DEFAULT_MODEL_NAME_FOR_TEST
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@@ -57,6 +56,18 @@ class TestBasicSanity(
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env={"SGLANG_ENABLE_METRICS_DEVICE_TIMER": "1"},
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)
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def test_accuracy_floor(self):
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_run_sgl_eval(
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self,
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eval_name="mmlu",
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score_threshold=0.60,
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num_examples=200,
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num_threads=64,
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thinking=False,
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max_tokens=256,
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temperature=0,
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)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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+1
-1
@@ -16,7 +16,7 @@ from sglang.multimodal_gen.runtime.models.dits.flux_2 import (
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.test_utils import CustomTestCase
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register_cuda_ci(est_time=13, stage="base-b", runner_config="1-gpu-small")
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register_cuda_ci(est_time=13, stage="base-b", runner_config="diffusion-unit-1-gpu-h100")
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def _fp8_linear(input_scale: float) -> nn.Module:
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+1
-1
@@ -16,7 +16,7 @@ from sglang.multimodal_gen.runtime.models.dits.qwen_image import (
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from sglang.test.ci.ci_register import register_cuda_ci
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from sglang.test.test_utils import CustomTestCase
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register_cuda_ci(est_time=12, stage="base-b", runner_config="1-gpu-small")
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register_cuda_ci(est_time=12, stage="base-b", runner_config="diffusion-unit-1-gpu-h100")
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def _fp8_linear(input_scale: float) -> nn.Module:
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