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Double encoder capacity: enc0 4→8ch, enc1 8→16ch, bottleneck 16→16ch,
dec1 32→8ch, dec0 16→4ch. Total weights 2476→7828 f16 (~15.3 KB).
FiLM MLP output 40→72 params (L1: 16×40→16×72).
16-ch textures split into _lo/_hi rgba32uint pairs (enc1, bottleneck).
enc0 and dec1 textures changed from rgba16float to rgba32uint (8ch).
GBUF_RGBA32UINT node gains CopySrc for parity test readback.
- WGSL shaders: all 5 passes rewritten for new channel counts
- C++ CNNv3Effect: new weight offsets/sizes, 8ch uniform structs
- Web tool (shaders.js + tester.js): matching texture formats and bindings
- Parity test: readback_rgba32uint_8ch helper, updated vector counts
- Training scripts: default enc_channels=[8,16], updated docstrings
- Docs + architecture PNG regenerated
handoff(Gemini): CNN v3 [8,16] upgrade complete. All code, tests, web
tool, training scripts, and docs updated. Next: run training pass.
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- cnn_v3/tools/weights.js: new file — base64-encoded cnn_v3_weights.bin +
cnn_v3_film_mlp.bin; loaded at startup so the tool works without dropping files
- tester.js: preload() falls back to embedded weights.js constants when fetch
fails; logs "Loaded embedded" vs "Preloaded" to distinguish the two paths
- index.html: load weights.js before tester.js
- export_cnn_v3_weights.py: add --html / --html-output flags that call
update_weights_js() to regenerate weights.js after a training run
- HOW_TO_CNN.md: update pipeline diagram, §3 export commands, §7 HTML tool
section (file table, workflow, weights.js description), Appendix A
handoff(Gemini): weights.js now the canonical source for HTML tool defaults;
regenerate with `uv run export_cnn_v3_weights.py <ckpt> --output ... --html`
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