leaveletandClaude Fable 5
87a22b17ce
from_schedule_batch built temperature/top_p/top_k/min_p (+seed) with 4-5 separate list comprehensions and one synchronous H2D copy each, plus 4 more passes for the is_all_greedy/need_* flags. Collect everything in a single pass over reqs and upload the float params as one pinned non-blocking H2D copy (disjoint device views of one buffer; filter/merge only index and cat, producing fresh tensors, so the shared buffer is safe), int32 top_k and optional int64 seeds as their own pinned copies. B300 (torch 2.11 cu130), scheduler-thread blocking time per call: bs=8: 38.8 -> 18.2 us (2.1x); bs=32: 1.9x; bs=200: 1.2x CPU-only construction at bs=200: 2890 -> 1387 us (2.1x). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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.