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feat: harden governed PyTorch training programme
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2026-07-26 17:18:42 +02:00
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## 2026-07-26 - PyTorch programme clarification and training hardening
- Clarified that PyTorch governs trainable imagery models and does not replace authoritative terrain, flood, land-use, road, water or change analyses.
- Audited Tower: CUDA PyTorch runs on the RTX 4080 SUPER; only the building corpus currently has promotion evidence. The active building candidate measures roughly 0.61 mean F1 on the expanded independent portfolio and zero detections on three pure-empty background samples.
- Generalized the tile exporter with explicit canonical class, reference source and reference layer evidence so regional authorities cannot be silently mixed.
- Added fail-closed `TRAIN_REQUIRE_CUDA` behavior and PyTorch/CUDA runtime evidence to training summaries.
- Added `docs/PYTORCH_MODEL_PROGRAM.md` with the task matrix and national training waves.
- Verification: 14 focused exporter/training tests passed.
- Open: nationwide building training cannot honestly start until spatially disjoint, temporally compatible GRB/PICC/URBIS plus orthophoto samples have been materialized and reviewed.
## 2026-07-19 - GeoIntel 1.0.0 final release closeout
- Promoted the current clean `main` revision to semantic version `1.0.0` in