Files
sglang/test/registered
laoyao0822 c3fc3ff752 Stabilize CP shared-KV prefetch around draft cache hits
Cache-hit EAGLE/NextN draft extends can enter the draft DeepEP MoE immediately after CP shared-KV attention. The partial current-reuse path is kept for target layers, but draft cache-hit suffixes now use full materialization until draft has an explicit same-layer reuse contract. Next-layer MLA/index prefetch is also gated by the actual model depth, so the single-layer draft model does not enqueue unused next-layer async work.

The temporary stage traces used to isolate the hang are removed. The retained draft current-reuse fallback is a bounded warning because it changes the runtime path intentionally.

Constraint: EAGLE/NextN has one executable draft layer and mirrors target KV state.

Rejected: Keep partial current reuse for draft cache-hit suffixes | reproduced hangs at draft layer0 before DeepEP MoE completion.

Rejected: Keep temporary stage traces | useful for diagnosis but too noisy for normal runs.

Confidence: medium

Scope-risk: moderate

Directive: Do not re-enable draft cache-hit partial current reuse without an explicit draft same-layer reuse contract and ETE validation with CP shared KV + HiCache + EAGLE.

Tested: py_compile on edited Python files; git diff --check; temp trace grep returned no matches.

Not-tested: Local targeted pytest is blocked by missing pybase64 in this environment; full ETE after log cleanup not run.
2026-05-29 00:33:41 +08:00
..
2026-03-21 17:10:35 +08:00

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.