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C++:
- cnn_v3_effect.cc: fix declare_nodes comment (output node declared by caller)
- cnn_v3_effect.cc: add TODO(phase-7) marker for FiLM MLP replacement
WGSL:
- cnn_v3_bottleneck.wgsl: consolidate _pad fields onto one line, explain why
array<u32,3> is invalid in uniform address space
- cnn_v3_enc0.wgsl: fix "12xu8" → "12ch u8norm" in header comment
- cnn_v3_dec0.wgsl: clarify parity note (sigmoid after FiLM+ReLU, not raw conv)
- cnn_v3_common.wgsl: clarify unpack_8ch pack layout (low/high 16 bits)
Python:
- cnn_v3_utils.py: replace PIL-based _upsample_nearest (uint8 round-trip) with
pure numpy index arithmetic; rename _resize_rgb → _resize_img (handles any
channel count); add comment on normal zero-pad workaround
- export_cnn_v3_weights.py: add cross-ref to cnn_v3_effect.cc constants;
clarify weight count comments with Conv notation
Test:
- test_cnn_v3_parity.cc: enc0/dec1 layer failures now return 0 (were print-only)
handoff(Gemini): CNN v3 review complete, 36/36 tests passing.
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5 compute shaders + cnn_v3/common snippet:
enc0: Conv(20→4,3×3) + FiLM + ReLU full-res
enc1: AvgPool + Conv(4→8,3×3) + FiLM + ReLU half-res
bottleneck: AvgPool + Conv(8→8,1×1) + ReLU quarter-res
dec1: NearestUp + cat(enc1) + Conv(16→4) + FiLM half-res
dec0: NearestUp + cat(enc0) + Conv(8→4) + FiLM + Sigmoid full-res
Parity rules: zero-pad conv, AvgPool down, NearestUp, FiLM after
conv+bias, skip=concat, OIHW weights+bias layout. Matches PyTorch
train_cnn_v3.py forward() exactly.
Registered in workspaces/main/assets.txt + src/effects/shaders.cc.
Weight layout + Params struct documented in cnn_v3/docs/HOWTO.md §7.
Next: Phase 4 — C++ CNNv3Effect + FiLM uniform upload.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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G-buffer (Phase 1):
- Add NodeTypes GBUF_ALBEDO/DEPTH32/R8/RGBA32UINT to NodeRegistry
- GBufferEffect: MRT raster pass (albedo+normal_mat+depth) + pack compute
- Shaders: gbuf_raster.wgsl (MRT), gbuf_pack.wgsl (feature packing, 32B/px)
- Shadow/SDF passes stubbed (placeholder textures), CMake integration deferred
Training infrastructure (Phase 2):
- blender_export.py: headless EXR export with all G-buffer render passes
- pack_blender_sample.py: EXR → per-channel PNGs (oct-normals, 1/z depth)
- pack_photo_sample.py: photo → zero-filled G-buffer sample layout
handoff(Gemini): G-buffer phases 3-5 remain (U-Net shaders, CNNv3Effect, parity)
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