Re-exported all modules after restructuring:
- Updated _modidx.py with new module locations
- Removed outdated autogeneration headers
- Updated all core modules (tensor, autograd, layers, etc.)
- Updated optimization modules (quantization, compression, etc.)
- Updated TITO commands for new structure
Changes include:
- 24 tinytorch/ module files
- 24 tito/ command and core files
- Updated references from modules/source/ to modules/
All modules re-exported via nbdev from their new locations.
- tinytorch/benchmarking/: Benchmark class for Module 19
- tinytorch/competition/: Submission utilities for Module 20
- tinytorch/data/: Data loading utilities
- tinytorch/utils/data/: Additional data helpers
Exported from modules 19-20 and module 08
This commit includes:
- Exported tinytorch package files from nbdev (autograd, losses, optimizers, training, etc.)
- Updated activations.py and layers.py with __call__ methods
- New module exports: attention, spatial, tokenization, transformer, etc.
- Removed old _modidx.py file
- Cleanup of duplicate milestone directories
These are the generated package files that correspond to the source modules
we've been developing. Students will import from these when using TinyTorch.
PROBLEM:
- nbdev requires #| export directive on EACH cell to export when using # %% markers
- Cell markers inside class definitions split classes across multiple cells
- Only partial classes were being exported to tinytorch package
- Missing matmul, arithmetic operations, and activation classes in exports
SOLUTION:
1. Removed # %% cell markers INSIDE class definitions (kept classes as single units)
2. Added #| export to imports cell at top of each module
3. Added #| export before each exportable class definition in all 20 modules
4. Added __call__ method to Sigmoid for functional usage
5. Fixed numpy import (moved to module level from __init__)
MODULES FIXED:
- 01_tensor: Tensor class with all operations (matmul, arithmetic, shape ops)
- 02_activations: Sigmoid, ReLU, Tanh, GELU, Softmax classes
- 03_layers: Linear, Dropout classes
- 04_losses: MSELoss, CrossEntropyLoss, BinaryCrossEntropyLoss classes
- 05_autograd: Function, AddBackward, MulBackward, MatmulBackward, SumBackward
- 06_optimizers: Optimizer, SGD, Adam, AdamW classes
- 07_training: CosineSchedule, Trainer classes
- 08_dataloader: Dataset, TensorDataset, DataLoader classes
- 09_spatial: Conv2d, MaxPool2d, AvgPool2d, SimpleCNN classes
- 10-20: All exportable classes in remaining modules
TESTING:
- Test functions use 'if __name__ == "__main__"' guards
- Tests run in notebooks but NOT on import
- Rosenblatt Perceptron milestone working perfectly
RESULT:
✅ All 20 modules export correctly
✅ Perceptron (1957) milestone functional
✅ Clean separation: development (modules/source) vs package (tinytorch)
