96158fa110
CP shared-KV batch planning needs the immediately previous prepared batch to remain visible as a virtual prefix, but launching another batch before processing that result can leave multiple prepared plans racing against radix insertion. The event loop now processes the previous result after planning the current batch and before launching it, preserving one-batch lookback without accumulating deeper overlap state. Constraint: CP HiCache prepared batch views are inserted during process_batch_result, not at forward launch. Rejected: Process previous result before planning current batch | loses visibility of the previous pending prepared plan needed by current planning. Confidence: medium Scope-risk: moderate Directive: Do not increase non-PP overlap depth for CP shared-KV without adding pending-radix reservation semantics. Tested: Remote cjy-glm5-new pytest test/registered/unit/disaggregation/test_overlap_disagg_prefill_event_loop.py test/registered/unit/disaggregation/test_overlap_disagg_decode_event_loop.py Not-tested: Full E2E latency impact of reduced overlap depth. (cherry picked from commit 7df8723eee8203e9e334b229178e3f8bac61396a)
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.