Files
sglang/test/registered
laoyao0822andOmX c551623ca8 Keep CP shared-KV cache hits page-aligned without short fallback
CP shared KV and HiCache need a stable contract where physical cache coverage is page-aligned, while scheduler/radix-visible hit length remains the valid token length. This records the contract, adds page-aligned extent metadata, keeps owner assignment on actual tail pages instead of short-prefix fallback, and updates partial current reuse tests around tail-page masking.

Constraint: CP owner lanes operate on page units while scheduler and radix hit accounting must remain token-valid.

Rejected: Pad short suffixes to cp_size or 2*cp_size pages | wastes KV capacity and can turn a small tail into a much larger physical span.

Rejected: Silent direct-write or prefetch fallback | production fallback must be warning-visible for diagnosis.

Confidence: medium

Scope-risk: moderate

Directive: Do not reintroduce replicated short-radix fallback without checking docs/advanced_features/nsa_prefill_cp_page_aligned_cache_contract.md.

Tested: local py_compile for touched runtime, utility, owner, and unit-test files.

Tested: remote g0034 container three-file suite: 122 passed, 5 warnings.

Not-tested: full local pytest, blocked by missing runtime dependencies such as orjson.

Not-tested: CUDA E2E runtime for this commit.

Co-authored-by: OmX <omx@oh-my-codex.dev>
2026-05-29 05:04:50 +08:00
..
2026-03-21 17:10:35 +08:00
2025-11-26 13:24:39 -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.