laoyao0822
8be4a3a8b5
CP shared-KV performance debugging depends on seeing when the runtime leaves the intended TAI, IPC, prefetch, or current-reuse paths. This change makes those misses visible through standardized warning markers while keeping per-reason log limits to avoid per-layer log floods.\n\nThe warnings intentionally distinguish fallback from fail-fast: unsupported correctness-sensitive states still raise, while performance-path misses emit [CP_SHARED_KV_FALLBACK] with the concrete reason.\n\nConstraint: Production ETE debugging needs visible fallback evidence without enabling heavy debug mode, which can itself disable fast paths.\nRejected: Rely only on optional MLA prefetch debug logs | they are env-gated, layer-limited, and miss non-prefetch TAI/IPC/current-reuse fallbacks.\nRejected: Log every per-layer event without limits | would drown useful transfer/cache diagnostics under steady-state traffic.\nConfidence: high\nScope-risk: moderate\nDirective: Do not remove these fallback warnings unless an equivalent low-noise observability path exists for every fast-path miss.\nTested: local py_compile for touched files; local git diff --check for touched files; remote g0034 py_compile and pytest for test_nsa_cp_utils.py, test_cp_shared_kv_layout.py, test_cp_shared_kv_runtime.py passed before commit (156 passed, 5 warnings, 2 subtests passed).\nNot-tested: full ETE serving traffic after warning additions.
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.