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authorskal <pascal.massimino@gmail.com>2026-03-27 07:59:00 +0100
committerskal <pascal.massimino@gmail.com>2026-03-27 07:59:00 +0100
commitfb13e67acbc7d7dd2974a456fcb134966c47cee0 (patch)
tree8dd1c6df371b0ee046792680a14c8bcb3c36510b /cnn_v1/docs/CNN.md
parent8c5e41724fdfc3be24e95f48ae4b2be616404074 (diff)
fix(cnn_v3): remove dec0 ReLU, load FiLM MLP at runtime
Two bugs blocking training convergence: 1. dec0 ReLU before sigmoid constrained output to [0.5,1.0] — network could never produce dark pixels. Removed F.relu in train_cnn_v3.py and max(0,…) in cnn_v3_dec0.wgsl. Test vectors regenerated. 2. set_film_params() used hardcoded heuristics instead of the trained MLP. Added CNNv3FilmMlp struct + load_film_mlp() to cnn_v3_effect.h/.cc. MLP auto-loaded from ASSET_WEIGHTS_CNN_V3_FILM_MLP at construction; Linear(5→16)→ReLU→Linear(16→72) runs CPU-side each frame. 36/36 tests pass. Parity max_err=4.88e-4 unchanged. handoff(Gemini): retrain from scratch — needs ≥50 samples (currently 11). See cnn_v3/docs/HOWTO.md §2-3.
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