Major directory restructure to support both developer and learner workflows:
Structure Changes:
- NEW: src/ directory for Python source files (version controlled)
- Files renamed: tensor.py → 01_tensor.py (matches directory naming)
- All 20 modules moved from modules/ to src/
- CHANGED: modules/ now holds generated notebooks (gitignored)
- Generated from src/*.py using jupytext
- Learners work in notebooks, developers work in Python source
- UNCHANGED: tinytorch/ package (still auto-generated from notebooks)
Workflow: src/*.py → modules/*.ipynb → tinytorch/*.py
Command Updates:
- Updated export command to read from src/ and generate to modules/
- Export flow: discovers modules in src/, converts to notebooks in modules/, exports to tinytorch/
- All 20 modules tested and working
Configuration:
- Updated .gitignore to ignore modules/ directory
- Updated README.md with new three-layer architecture explanation
- Updated export.py source mappings and paths
Benefits:
- Clean separation: developers edit Python, learners use notebooks
- Better version control: only Python source committed, notebooks generated
- Flexible learning: can work in notebooks OR Python source
- Maintains backward compatibility: tinytorch package unchanged
Tested:
- Single module export: tito export 01_tensor ✅
- All modules export: tito export --all ✅
- Package imports: from tinytorch.core.tensor import Tensor ✅
- 20/20 modules successfully converted and exported
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- Removed outdated autogeneration headers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.
- Update module path from 15_profiling to 14_profiling
- Add quick_profile helper for quick bottleneck discovery
- Add analyze_weight_distribution for pruning analysis
- Export new helper functions in __all__
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)
- Remove 14 empty/unused directories from tinytorch/ package
- Keep only essential directories: core/, datasets/, configs/
- All directories removed contained only empty __init__.py files or were completely empty
- CLI functionality preserved and tested working
- Cleaner package structure for development
