laoyao0822
187b700406
EAGLE verification can pass torch scalar tensors through the speculative tree traversal before calling grammar backends. xgrammar/tvm_ffi requires Python int token ids, so normalize traversal indices and draft token ids at the boundary while leaving tensor storage unchanged. Constraint: xgrammar/tvm_ffi rejects torch scalar tensors for GrammarMatcher.accept_token Rejected: Coerce tokens inside every grammar backend | the invalid value originates in speculative traversal and should be fixed before backend dispatch Confidence: high Scope-risk: narrow Directive: Keep grammar backend calls scalar-Python typed; do not pass torch scalar tensors through accept_token Tested: remote g0034 cjy-glm5-new PYTHONPATH=python python -m pytest -q test/registered/unit/speculative/test_spec_utils.py test/registered/unit/configs/test_nsa_index_layers.py test/registered/unit/models/test_deepseek_index_skip_weight_loading.py -> 19 passed Tested: remote g0034 cjy-glm5-new py_compile for modified runtime files Not-tested: live decode replay after this commit
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.