fix: CNN training normalization pipeline consistency

**Training changes:**
- Final layer now outputs [0,1] directly with torch.clamp()
- Removed denormalization step (was converting [-1,1] to [0,1])
- Network learns [0,1] output natively

**Shader generation fixes:**
- Layer 0 uses _src variant (5 params, normalizes [0,1] input internally)
- Removed pre-normalization of input texture (handled by _src)
- Final layer blending: gray_out already [0,1], no denormalization needed
- Added generate_conv_src_function() for all kernel sizes
- Auto-generates _src variants when exporting (skips if exists)

**Cleanup:**
- Removed obsolete 4-channel functions from cnn_conv5x5.wgsl
- Keep only 7-channel variants (_7to4, _7to1, _7to4_src)

**Normalization flow:**
[0,1] texture → _src normalizes to [-1,1] → tanh [-1,1] → ... → final conv [0,1] clipped

handoff(Claude): CNN normalization pipeline fixed and consistent with training

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