Files
sglang/test/registered
laoyao0822 07c9544737 Preserve transferred EAGLE state past metadata-slot reuse
Decode committed EAGLE top-k and hidden-state tensors as views into reusable metadata-buffer rows. The metadata index is freed immediately after transfer commit, while the request may wait before process_prebuilt consumes the draft state. Under concurrent cache-hit traffic a later transfer can overwrite the same row, leaving output_id copied correctly but EAGLE draft state corrupted, which matches low accept length despite successful KV/state registration.

Constraint: Metadata slots are intentionally recycled right after transfer commit for throughput.

Rejected: Hold metadata slots until process_prebuilt | larger lifetime change and reduces transfer capacity; cloning the small prebuilt EAGLE state is narrower.

Confidence: high

Scope-risk: narrow

Directive: Do not store reusable metadata-buffer views on Req unless the slot lifetime is extended through all consumers.

Tested: Local py_compile for decode.py and test_decode_queue_compaction.py.

Tested: Remote g0034 container py_compile for decode.py and test_decode_queue_compaction.py.

Tested: Remote g0034 focused clone-lifetime test: 1 passed.

Tested: Remote g0034 test_decode_queue_compaction.py: 10 passed, 5 warnings.

Not-tested: ETE cache-hit accept-length validation after restarting prefill/decode with this synced code.
2026-05-30 03:36:42 +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.