ANE/training/layers
Andy Huang e113fae683 feat: implement ANE SDK for general-purpose neural engine development
- Implement modular ANE-MIL layer library (Linear, Conv2D, Softmax, LayerNorm, etc.)
- Add Sequential model container with automated activation surface chaining (ping-ponging)
- Implement optimized 'Weights-as-Tensors' pattern across all SDK layers for zero-recompile weight updates
- Add comprehensive automated regression testing suite (regression_test.py)
- Standardize verification for legacy Transformer training and new modular SDK components
- Update README.md and roadmap to reflect SDK capabilities and usage instructions
- Refactor hardcoded paths and unify checkpoint naming conventions for stability
2026-03-03 15:35:55 +11:00
..
anesdk.h feat: implement ANE SDK for general-purpose neural engine development 2026-03-03 15:35:55 +11:00
cnn.h feat: implement ANE SDK for general-purpose neural engine development 2026-03-03 15:35:55 +11:00
core.h feat: implement ANE SDK for general-purpose neural engine development 2026-03-03 15:35:55 +11:00
types.h feat: implement ANE SDK for general-purpose neural engine development 2026-03-03 15:35:55 +11:00