1ebde44e59
Index skip reduces the number of target layers that own NSA index state, but PD transfer and HiCache still assumed dense full-layer state buffers. This change carries explicit state layer IDs through prefill/decode registration, compacts device and host index buffers to active layers, and maps logical layer IDs to compact slots on transfer paths. The PD side fails fast when prefill/decode disagree on NSA state layer identity instead of silently truncating or copying mismatched buffers. Host direct tests now use the same CPU-index descriptor contract required by the TAI cudaMemcpyBatchAsync path, and host registered memory is unregistered on tensor finalization to avoid stale cudaHostRegister state across CUDA tests. Constraint: CP shared-KV with index_topk skip must keep target/draft state identity explicit before compacting buffers Constraint: Direct HiCache TAI transfer rejects CUDA indices to avoid hidden D2H copies on the control path Rejected: Keep full-layer L1/L2 index buffers | wastes the memory/bandwidth that index skip is meant to save Rejected: Infer state buffer order by count only | can silently corrupt cache when active layer sets differ Confidence: high Scope-risk: moderate Directive: Do not compact or reorder NSA state buffers without carrying logical layer IDs through PD registration and validating both sides Tested: Remote container py_compile for touched runtime files Tested: Remote container pytest: test_nsa_pool_host_unit.py, test_model_runner_kv_cache_mixin.py, test_cp_shared_kv_transfer_mapping.py, test_pd_state_layer_ids.py, test_cp_per_layer_transfer.py, test_cp_shared_kv_runtime.py -> 200 passed, 2 subtests passed Not-tested: Full ETE GSM8K/replay after compacted P3-P6 changes Co-authored-by: OmX <omx@oh-my-codex.dev>
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.