5e5ac5e2e7
The shared-KV prefill path now optionally calls tai_kernel.nsa_prefill.fused_store_mla_kv before falling back to logical_locs_to_physical plus set_mla_kv_buffer. The fast path supports packed FP8 and BF16/FP16 direct KV buffers, while debug mode and kernel failures still preserve the existing fallback behavior. Success logging was removed after path verification because per-layer/per-rank logs are too noisy in normal server runs. Constraint: Runtime must remain safe when tai-kernel is absent or debug checks are enabled Rejected: Keep success logs permanently | floods prefill logs once every rank/layer starts using the fast path Confidence: high Scope-risk: moderate Directive: Keep fallback warnings; do not re-add per-layer success logs outside explicit debug instrumentation Tested: g0034 container python -m py_compile python/sglang/srt/layers/attention/nsa/cp_shared_kv_runtime.py Tested: g0034 container PYTHONPATH=python pytest -q test/registered/unit/mem_cache/test_cp_shared_kv_runtime.py -q (40 passed) Not-tested: Full multi-node PD server throughput after log removal
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.