Per-layer prefill-to-decode transfer now finishes per request/rank/chunk, so success-path INFO logs can dominate production logs and hide actual failures. Keep successful finish breakdown and completion messages at DEBUG while preserving nonzero finish status as WARNING. Constraint: Per-layer transfer is a hot path under CP shared-KV and may produce many batch completions per request. Rejected: Disable CP per-layer transfer logging entirely | failures still need visible warning-level evidence. Confidence: high Scope-risk: narrow Directive: Do not promote successful per-request transfer completion logs back to INFO without rate limiting. Tested: PYTHONPATH=python python -m pytest -q test/registered/unit/disaggregation/test_cp_per_layer_transfer.py::TestPerLayerTransferContext::test_successful_finish_does_not_emit_hot_path_info_log Tested: python -m py_compile python/sglang/srt/disaggregation/cp_per_layer_transfer.py python/sglang/srt/disaggregation/mooncake/conn.py Not-tested: Full local disaggregation suite blocked by missing local orjson dependency. Co-authored-by: OmX <omx@oh-my-codex.dev>
Registered Tests
Tests under this directory are auto-discovered by run_suite.py via CI registration decorators.
Where Should I Put My New Test?
No server / engine launch required
| What you're testing | Directory | Requires |
|---|---|---|
| Component logic in isolation (cache, scheduler, config, parser, etc.) | unit/<module>/ |
CPU or GPU |
| CUDA kernel correctness | kernels/ |
GPU |
Server / engine launch required (E2E)
| What you're testing | Directory | Requires |
|---|---|---|
| Model inference correctness | models/, 4-gpu-models/, 8-gpu-models/ |
GPU |
| Feature-specific (OpenAI API, LoRA, speculative, distributed, VLM, etc.) | openai_server/, lora/, spec/, distributed/, ... |
GPU |
| Benchmarks (performance, accuracy, stress) | benchmark/ |
GPU |
| Platform-specific | amd/, ascend/ |
Vendor GPU |
See unit/README.md for unit test conventions.