New sgl-deep-gemm wheels persist cubins, but SGLang was still replaying the full warmup envelope after every restart. The wrapper also translated SGLANG_DG_* env after importing deep_gemm, so the wheel could observe stale cache settings.\n\nMove DeepGEMM JIT env preparation before the first import, bridge the current SGLANG_DG_USE_NVRTC spelling, replace dense M walks with category-specific sparse M grids, and add a SGLang-side warmup manifest under the DeepGEMM cache dir. A manifest hit skips only the SGLang replay loop; missing or stale cache entries still force warmup and refresh the manifest.\n\nConstraint: sgl-deep-gemm 0.1.2 removed the compile-mode API, so dense 1..m_max loops launch real kernels.\nConstraint: DeepGEMM cache keys include compiler flags such as the deep_gemm include path; path-stable environments are still required for cross-container cache hits.\nRejected: SGLANG_JIT_DEEPGEMM_PRECOMPILE=0 | bypasses warmup instead of making cache reuse correct.\nRejected: Enable per-process cache dirs by default | isolates corruption but defeats persistent cross-process cache reuse.\nConfidence: medium\nScope-risk: moderate\nDirective: Do not reintroduce dense DeepGEMM warmup for new wheels unless compile-mode support is verified on the target wheel.\nTested: Local py_compile for jit_cache.py configurer.py compile_utils.py model_runner.py\nTested: Local pytest test/registered/unit/layers/test_deep_gemm_jit_cache.py (6 passed)\nTested: Remote g0034 cjy-glm5-new py_compile for same files\nTested: Remote g0034 cjy-glm5-new pytest test/registered/unit/layers/test_deep_gemm_jit_cache.py (6 passed)\nTested: Remote env probe verified SGLANG_DG_CACHE_DIR and SGLANG_DG_USE_NVRTC bridge to DG_JIT_* before configurer completes\nNot-tested: Full decode cold-cache/hot-cache restart timing and manifest-hit ETE log validation
Unit Tests
Component-level tests that do not launch a server or load model weights. Tests can use CPU or GPU — the key criterion is no server process.
Quick Start
- Find the source file under
python/sglang/srt/. - Create the corresponding test here, mirroring the source tree:
srt/mem_cache/radix_cache.py → unit/mem_cache/test_radix_cache.py srt/sampling/sampling_params.py → unit/sampling/test_sampling_params.py - Register for CI at the top of the file (after imports, before test classes):
from sglang.test.ci.ci_register import register_cpu_ci register_cpu_ci(est_time=5, suite="stage-a-test-cpu") # or: register_cuda_ci(est_time=10, suite="stage-b-test-1-gpu-small") - Run locally:
pytest test/registered/unit/ -v # all unit tests pytest test/registered/unit/mem_cache/ -v # one module - Run with coverage:
# summary pytest test/registered/unit/ --cov --cov-config=.coveragerc -v # PR incremental check (require ≥60% on changed lines) pytest test/registered/unit/ --cov --cov-config=.coveragerc --cov-report=xml diff-cover coverage.xml --compare-branch=origin/main --fail-under=60
Example
"""Unit tests for <module> — no server, no model loading."""
from sglang.test.ci.ci_register import register_cpu_ci
register_cpu_ci(est_time=5, suite="stage-a-test-cpu")
import unittest
from sglang.srt.<module> import TargetClass
from sglang.test.test_utils import CustomTestCase
class TestTargetClass(CustomTestCase):
def test_basic_behavior(self):
obj = TargetClass(...)
self.assertEqual(obj.method(), expected)
if __name__ == "__main__":
unittest.main()
Rules
- No
popen_launch_server()orEngine(...). - No model weight loading.
- Use
CustomTestCase(fromsglang.test.test_utils, adds CI retry). - Use
unittest.mockfor dependencies that are expensive to construct.