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path: root/training/train_cnn.py
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32 hoursadd --save-intermediates to train.py and cnn_testskal
33 hoursfix: Move sigmoid activation to call site in CNN layer shaderskal
33 hoursfix: Replace clamp with sigmoid in CNN final layerskal
33 hoursfeat: Add early stopping to CNN trainingskal
33 hoursfix: CNN training/inference to match WGSL sliding windowskal
33 hoursformat .wgsl layer code (cosmetics)skal
42 hoursfix: Use patch-based inference to match CNN training distributionskal
42 hoursopt: Move invariant in1 calculation outside CNN convolution loopsskal
43 hoursopt: Vec4-optimize CNN convolution shaders for SIMDskal
44 hoursfeat: Add salient-point patch extraction for CNN trainingskal
45 hoursfix: Correct UV coordinate computation to match PyTorch linspaceskal
45 hoursfix: Add clamp to CNN final layer to match PyTorch trainingskal
46 hoursrefactor: Optimize CNN grayscale computationskal
46 hoursupdate train_cnn.py and shaderskal
47 hoursfeat: Add inference mode to train_cnn.py for ground truth generationskal
47 hoursfix: CNN training normalization pipeline consistencyskal
48 hoursrefactor: Optimize CNN normalization to eliminate redundant conversionsskal
2 daysfix: Support variable kernel sizes in CNN layer generationskal
2 daysfeat: CNN RGBD→grayscale with 7-channel augmented inputskal
2 daysfeat: Add multi-layer CNN support with framebuffer capture and blend controlskal
2 daysfeat: Add checkpointing support to CNN training scriptskal
2 daysfix: Auto-expand single kernel size to all layers in training scriptskal
2 daysfeat: Add coordinate-aware CNN layer 0 for position-dependent stylizationskal