docs/sprint_log.md

Sprint Log

@model-expansion-preflight-2025-08-21

Goal: Reinforce training script contracts and registry hook without behavior changes. Changes:

• Reproducibility seeds (python/numpy/torch/cuda).
• Optional cuDNN deterministic settings. -Typo fix: "Reseample" -> "Resample".
• Diagnostics fix: per-fold accuracy logs use correct variable.
• Explicit dtypes in TensorDataset (float32/long). Tests:
• Preprocess: ✅
• Train (figure2, 1 epoch): ✅
• Inference smoke: ✅ Notes: Baseline intact; high CV variance due to class imbalance recorded for later migration.

@model-expansion-registry-2025-08-21

Goal: Make model lookup a single source of truth and expose dynamic choices for CLI/infra. Changes:

• Added models/registry.py with choices() and build() helpers.
• scripts/train_model.py imports registry, uses choices() for argparse and build() for contruction.
• Removed direct model selection logic from training script. Tests:
• Train (figure2) via registry: ✅
• Inference unchanged paths: ✅ Notes: Artifacts remain outputs/{model}_model.pth to avoid breaking validator; inference arch flag to be added next.

@model-expansion-resnet18vision-2025-08-21

Goal: Introduce a second architecture and prove multi-model training/inference via shared registry. Changes: models/resnet18_vision.py (1D), registry entry, run_inference.py --arch. Tests: Train (1 epoch) -> outputs/resnet18vision_model.pth; Inference JSON ✅ Notes: Backward compatibility preserved (--arch defaults to figure2).