d21952b903
Centralize the IndexCache skip formula and thread the resulting active logical index layers into NSA KV pools. HiCache now skips only the indexer H2D/D2H payload for inactive target layers while preserving per-layer MLA KV transfer, keeping allocation shape unchanged for this phase. Constraint: P0-P2 must not compact device or host allocation yet; prefill/decode state transfer still has no logical layer-id metadata. Rejected: Recompute the skip formula separately in mem_cache | formula drift would corrupt cache or waste transfers when offset/pattern settings change. Rejected: Skip whole-layer HiCache load/backup | MLA KV remains required for every attention layer. Confidence: medium Scope-risk: moderate Directive: Before enabling compact state buffers or compact allocation, add layer-id metadata validation to PD transfer. Tested: Local py_compile for touched files; remote pytest in g0034 container: test_nsa_index_layers.py and TestNSAIndexerPageIndices, 20 passed. Not-tested: ETE replay/GSM8K with --nsa-index-topk-freq 4; PD state-transfer compaction remains unimplemented.
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.