Vijay Janapa Reddi 7644821479 feat: implement professional selective export pattern across all modules ...

BREAKING CHANGE: Refactor from whole-module exports to selective function/class exports

**What Changed:**
- Separate development utilities from production exports
- Each function/class gets individual #| export directive
- Clean Prerequisites & Setup sections in all modules
- Development helpers (import_previous_module) not exported

**Module Export Summary:**
- 01_tensor: Tensor class only
- 02_activations: Sigmoid, ReLU, Tanh, GELU, Softmax only
- 03_layers: Linear, Dropout only
- 04_losses: MSELoss, CrossEntropyLoss, BinaryCrossEntropyLoss, log_softmax only
- 05_autograd: Function class only
- 06_optimizers: SGD, Adam, AdamW only

**Benefits:**
✅ Clean public API (matches PyTorch/TensorFlow patterns)
✅ No development utilities in final package
✅ Professional software education standards
✅ Clear separation of concerns
✅ Educational clarity for students

This matches industry standards for educational ML frameworks.

2025-09-30 09:48:47 -04:00

..

tensor_dev.ipynb

Clean up module imports: convert tinytorch.core to sys.path style

2025-09-30 08:58:58 -04:00

tensor_dev.py

feat: implement professional selective export pattern across all modules

2025-09-30 09:48:47 -04:00