9eb9d82b51
The CP in-seq NSA indexer path was constructing a CUDA validity mask around each fp8_mqa_logits call, synchronizing it back with .item(), and then rebuilding small CUDA tensors before topk. The valid rows are always a contiguous prefix because ke_offset is monotonic, so the count can be derived from existing CP metadata and the path can use slices instead of boolean gather/scatter. RAGGED topk now reuses the zero row-start vector as the per-row offset override for the single-segment case to avoid cumsum/repeat_interleave metadata kernels after MQA. Constraint: CP shared KV prefill still needs to preserve prev/next causal visibility and topk transform semantics. Rejected: Add a new Triton range-builder first | the Python-side synchronization and boolean indexing were the larger immediate risk, and kernel work should be profiled after this smaller change. Confidence: medium Scope-risk: moderate Directive: Do not reintroduce GPU mask .item() or CPU-created CUDA tensors in the fp8_mqa_logits hot path without profiler evidence. Tested: python3 -m py_compile python/sglang/srt/layers/attention/nsa/nsa_indexer.py test/registered/unit/layers/test_nsa_cp_utils.py Tested: g0034 docker /sgl-workspace/sglang-tai python3 test/registered/unit/layers/test_nsa_cp_utils.py -> Ran 22 tests OK Not-tested: full GLM5 PD server throughput/profiler run
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.