e4cf8d18b4
Batch-size support needs request-first CP metadata; treating a batch as one long sequence breaks page ownership, top-k ranges, and phase1 compact output collection. This adds a batch CP plan that records per-request page-aligned splits, rank-local offsets, kv/actual-seq metadata, last-token owners, and flattened descriptors for downstream allocator/runtime workstreams. The scalar full-rerange path now fail-fasts for batch metadata so bs>1 cannot silently discard the narrow-output optimization or restore hidden states with single-request assumptions. Constraint: CP shared-KV cache state is page-owned and must preserve request boundaries under bs>1. Rejected: Let bs>1 fall back to scalar full hidden rerange | it loses the phase1 communication reduction and uses wrong single-request metadata. Rejected: Add a collective to confirm batch plans | all ranks can derive the same plan from CPU metadata and config. Confidence: medium Scope-risk: moderate Directive: Do not remove batch fail-fast guards until W2/W3 consumers use CPSharedKVBatchPlan end-to-end. Tested: python -m py_compile python/sglang/srt/layers/attention/nsa/utils.py test/registered/unit/layers/test_nsa_cp_utils.py Tested: remote g0034 container PYTHONPATH=python python -m pytest -q test/registered/unit/layers/test_nsa_cp_utils.py -> 39 passed Not-tested: full ETE bs>1 CP shared-KV runtime; W2/W3 allocator/direct-write consumers are not implemented yet
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.