108e7d866d
The scheduler can now admit multi-request NSA in-seq CP shared-KV prefill batches only when the shared-KV bs>1 flag is explicitly enabled. The gate is still disabled by default and is scoped to CP shared-KV so ordinary CP is not widened accidentally. Batch admission is bounded by optional request-count and page-aligned extend-token limits while real memory capacity remains allocator-owned. This keeps bf16 and fp8 on the same scheduler path because dtype differences are already reflected in KV pool token/page capacity. Constraint: bs>1 runtime paths remain guarded by existing CP shared-KV fail-fast checks. Constraint: Scheduler must not duplicate bf16/fp8 byte-level capacity estimation. Rejected: Open the old CP gate unconditionally | ordinary CP would inherit an unverified shared-KV-specific batching path. Rejected: Treat the extend-token cap as a hard per-request limit | a single large request could deadlock the scheduler. Confidence: medium Scope-risk: moderate Directive: Keep CP shared-KV batching gated until ETE validates EAGLE accept length, output length, and HiCache load/backup behavior under real traffic. Tested: local py_compile for server_args, schedule_policy, scheduler, prefill_adder tests, and server_args tests. Tested: remote g0034 py_compile for the same files. Tested: remote g0034 pytest target set: 5 passed for parser, parameter validation, default single-request CP gate, enabled bs>1 gate, and page-aligned extend cap. Tested: remote g0034 pytest test_prefill_adder.py => 13 passed. Not-tested: full server_args test file has an unrelated HuggingFace DNS/config-download failure in TestPrepareServerArgs.test_prepare_server_args. Not-tested: ETE production traffic with --enable-cp-shared-kv-prefill-bs-gt1.
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.