From 8f14bdd66cb002b2f89265b2a578ad93249089c9 Mon Sep 17 00:00:00 2001 From: skal Date: Thu, 26 Mar 2026 07:03:01 +0100 Subject: feat(cnn_v3): upgrade architecture to enc_channels=[8,16] MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 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. --- cnn_v3/docs/gen_architecture_png.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) (limited to 'cnn_v3/docs/gen_architecture_png.py') diff --git a/cnn_v3/docs/gen_architecture_png.py b/cnn_v3/docs/gen_architecture_png.py index bd60a97..1c2ff65 100644 --- a/cnn_v3/docs/gen_architecture_png.py +++ b/cnn_v3/docs/gen_architecture_png.py @@ -108,20 +108,20 @@ def dim_label(x, y, txt): box(EX, Y_IN, BW, BH_IO, C_IO, 'G-Buffer Features', '20 channels · full res') -box(EX, Y_E0, BW, BH, C_ENC, 'enc0 Conv(20→4, 3×3) + FiLM + ReLU', - 'full res · 4 ch') +box(EX, Y_E0, BW, BH, C_ENC, 'enc0 Conv(20→8, 3×3) + FiLM + ReLU', + 'full res · 8 ch') -box(EX, Y_E1, BW, BH, C_ENC, 'enc1 Conv(4→8, 3×3) + FiLM + ReLU', - '½ res · 8 ch · (AvgPool↓ on input)') +box(EX, Y_E1, BW, BH, C_ENC, 'enc1 Conv(8→16, 3×3) + FiLM + ReLU', + '½ res · 16 ch · (AvgPool↓ on input)') box(BX, Y_BN, BW_BN, BH_BN, C_BN, - 'bottleneck Conv(8→8, 3×3, dilation=2) + ReLU', - '¼ res · 8 ch · no FiLM · effective RF ≈ 10 px @ ½res') + 'bottleneck Conv(16→16, 3×3, dilation=2) + ReLU', + '¼ res · 16 ch · no FiLM · effective RF ≈ 10 px @ ½res') -box(DX, Y_D1, BW, BH, C_DEC, 'dec1 Conv(16→4, 3×3) + FiLM + ReLU', - '½ res · 4 ch · (upsample↑ + cat enc1 skip)') +box(DX, Y_D1, BW, BH, C_DEC, 'dec1 Conv(32→8, 3×3) + FiLM + ReLU', + '½ res · 8 ch · (upsample↑ + cat enc1 skip)') -box(DX, Y_D0, BW, BH, C_DEC, 'dec0 Conv(8→4, 3×3) + FiLM + sigmoid', +box(DX, Y_D0, BW, BH, C_DEC, 'dec0 Conv(16→4, 3×3) + FiLM + sigmoid', 'full res · 4 ch · (upsample↑ + cat enc0 skip)') box(DX, Y_OUT, BW, BH_IO, C_IO, 'RGBA Output', -- cgit v1.2.3