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path: root/training/train_cnn.py
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22 hoursdocs: Update CNN comments and add bias fix summaryskal
22 hoursfix: CNN bias accumulation and output format improvementsskal
29 hoursrefactor: Use linspace(-1,1) directly for coordsskal
29 hoursfix: Compute gray from [0,1] RGB in CNN shader generatorskal
35 hoursadd --save-intermediates to train.py and cnn_testskal
35 hoursfix: Move sigmoid activation to call site in CNN layer shaderskal
35 hoursfix: Replace clamp with sigmoid in CNN final layerskal
36 hoursfeat: Add early stopping to CNN trainingskal
36 hoursfix: CNN training/inference to match WGSL sliding windowskal
36 hoursformat .wgsl layer code (cosmetics)skal
45 hoursfix: Use patch-based inference to match CNN training distributionskal
45 hoursopt: Move invariant in1 calculation outside CNN convolution loopsskal
46 hoursopt: Vec4-optimize CNN convolution shaders for SIMDskal
46 hoursfeat: Add salient-point patch extraction for CNN trainingskal
48 hoursfix: Correct UV coordinate computation to match PyTorch linspaceskal
48 hoursfix: Add clamp to CNN final layer to match PyTorch trainingskal
2 daysrefactor: Optimize CNN grayscale computationskal
2 daysupdate train_cnn.py and shaderskal
2 daysfeat: Add inference mode to train_cnn.py for ground truth generationskal
2 daysfix: CNN training normalization pipeline consistencyskal
2 daysrefactor: 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