Constraint: Open-dataset support was not complete until imported corpora could train, build indexes, and produce eval outputs without manual path surgery
Rejected: Stop at train.py dry-run | Does not prove the retrieval/evaluation half of the workflow actually works
Confidence: high
Scope-risk: moderate
Directive: Keep future external dataset layouts self-contained and manifests-root aware across training, indexing, and evaluation paths
Tested: /usr/local/miniconda3/bin/python train.py --data data/external_ingested/synthetic_as_open_fixed/fma/manifests --output data/models_open_smoke_fixed --device cpu --epochs 1 --batch-size 2; /usr/local/miniconda3/bin/python run_demo.py build-index --data data/external_ingested/synthetic_as_open_fixed/fma/manifests --model data/models_open_smoke_fixed/best_model.pt --output data/index_open_smoke_fixed --device cpu; /usr/local/miniconda3/bin/python evaluate.py --data data/external_ingested/synthetic_as_open_fixed/fma/manifests --model data/models_open_smoke_fixed/best_model.pt --index-prefix data/index_open_smoke_fixed/reference --split test --device cpu --fast-eval --output-json reports/open-smoke-fixed/fma/eval.json; /usr/local/miniconda3/bin/python -m py_compile evaluate.py run_demo.py src/engines/ecapa_embedder.py src/engines/chromaprint_matcher.py src/data/dataset.py src/data/manifest_tools.py src/data/external_adapters.py train.py
Not-tested: Real downloaded FMA or MTG-Jamendo corpora at larger scale

cnb.bofCdSsphPA authored 2026-06-02 12:59:41 +0800