Files
sglang/test/registered
laoyao0822 6a25c312c7 Cache completed chunked prefill pages in CP HiCache
Chunked prefill was skipping prepared CP HiCache backup entirely while still inserting unfinished valid-tail radix state. That combination caused middle chunks to miss reusable host cache and repeatedly hit stale-tail split fallback paths.\n\nThis keeps CP HiCache page-granular: middle chunks now reserve/write only completed pages, and unfinished radix inserts expose only page-complete prefixes while preserving the request-owned sub-page tail in prefix_indices for later chunks.\n\nConstraint: CP HiCache radix and host residency are managed at page granularity, but chunked prefill can end on a sub-page tail.\nRejected: Continue skipping chunked backup | loses middle-chunk reuse and triggers fallback storms.\nRejected: Insert sub-page chunk tails into CP HiCache | creates stale-tail prune/split conflicts against request-owned KV.\nConfidence: medium\nScope-risk: moderate\nDirective: Do not reintroduce chunked_req backup skip; keep CP HiCache chunked inserts page-complete unless the radix/host cache contract becomes sub-page aware.\nTested: python -m py_compile python/sglang/srt/mem_cache/radix_cache.py python/sglang/srt/mem_cache/hiradix_cache.py test/registered/unit/mem_cache/test_cp_hicache_metadata.py\nTested: g0034 targeted chunked CP HiCache regression tests, 2 passed\nTested: g0034 PYTHONPATH=python python -m pytest -q test/registered/unit/mem_cache/test_cp_hicache_metadata.py, 107 passed\nNot-tested: Fresh chunked-prefill ETE traffic run after process restart
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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.