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23 hoursCNN v2: Alpha channel depth handling and layer visualizationskal
Training changes: - Changed p3 default depth from 0.0 to 1.0 (far plane semantics) - Extract depth from target alpha channel in both datasets - Consistent alpha-as-depth across training/validation Test tool enhancements (cnn_test): - Added load_depth_from_alpha() for R32Float depth texture - Fixed bind group layout for UnfilterableFloat sampling - Added --save-intermediates with per-channel grayscale composites - Each layer saved as 4x wide PNG (p0-p3 stacked horizontally) - Global layers_composite.png for vertical layer stack overview Investigation notes: - Static features p4-p7 ARE computed and bound correctly - Sin_20_y pattern visibility difference between tools under investigation - Binary weights timestamp (Feb 13 20:36) vs HTML tool (Feb 13 22:12) - Next: Update HTML tool with canonical binary weights handoff(Claude): HTML tool weights update pending - base64 encoded canonical weights ready in /tmp/weights_b64.txt for line 392 replacement. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2 daysRefine training script output and validationskal
1. Loss printed at every epoch with \r (no scrolling) 2. Validation only on final epoch (not all checkpoints) 3. Process all input images (not just img_000.png) Training output now shows live progress with single line update.