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| author | skal <pascal.massimino@gmail.com> | 2026-03-27 07:59:00 +0100 |
|---|---|---|
| committer | skal <pascal.massimino@gmail.com> | 2026-03-27 07:59:00 +0100 |
| commit | fb13e67acbc7d7dd2974a456fcb134966c47cee0 (patch) | |
| tree | 8dd1c6df371b0ee046792680a14c8bcb3c36510b /third_party/wgpu-native | |
| parent | 8c5e41724fdfc3be24e95f48ae4b2be616404074 (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.
Diffstat (limited to 'third_party/wgpu-native')
0 files changed, 0 insertions, 0 deletions
