342c552ab3
CP shared-KV bs>1 uses cp_shared_kv_prefill_max_total_extend_tokens as its grouping admission limit, but the generic max_prefill_tokens budget could still stop batching earlier. Raise only the legacy input-token admission budget for this CP path while keeping allocator-owned capacity checks unchanged. Constraint: CP shared-KV bs>1 needs large cache-hit batches without relying on the generic max_prefill_tokens default. Constraint: Allocator capacity must remain enforced by rem_total_tokens, cur_rem_tokens, and prepare_for_extend(). Rejected: Increase server-wide max_prefill_tokens | would change generic scheduler behavior and non-CP paths. Confidence: high Scope-risk: narrow Directive: Do not use max_prefill_tokens as the CP shared-KV bs>1 grouping limit; use the CP-specific total extend token knob. Tested: Local py_compile for schedule_policy.py and test_prefill_adder.py. Tested: Remote pytest targeted CP PrefillAdder cases: 5 passed. Tested: Remote pytest test/registered/unit/managers/test_prefill_adder.py: 16 passed. Not-tested: Full ETE replay after this scheduler-only change.
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.