f8b4f1915e
W3 needs batch-size>1 extends to use packed valid tokens while preserving per-request page boundaries. The local out_cache_loc planner now validates against the batch plan's request lengths instead of the first request's scalar split metadata, then reuses the existing batch split helper to produce this rank's logical/physical cache locs. Direct-write failures inside the CP shared-KV contract now fail fast instead of silently falling back to legacy index/MLA stores. This exposes allocator, owner-lane, page-alignment, and shape-contract bugs early for both bs=1 and bs>1. Constraint: bs>1 batching must not pad short requests to the longest request; only per-request page-boundary padding is allowed. Rejected: Keep bs=1 compatibility fallback | it hides CP shared-KV contract violations and caused repeated slow-path ambiguity. Rejected: Pad batch to max request length | wastes compute and complicates cache validity for short extends. Confidence: high Scope-risk: moderate Directive: CP shared-KV contract errors should stay fail-fast; do not reintroduce silent direct-write fallback without ETE evidence and explicit warning semantics. Tested: Remote g0034 py_compile for utils.py nsa_indexer.py forward_mla.py Tested: Remote g0034 PYTHONPATH=python pytest test/registered/unit/layers/test_nsa_cp_utils.py -> 43 passed Tested: Remote g0034 PYTHONPATH=python pytest test_nsa_cp_utils.py test_cp_shared_kv_layout.py test_cp_shared_kv_runtime.py -> 170 passed, 2 subtests passed Not-tested: Full ETE bs>1 serving run with live traffic
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.