- Regenerate all .ipynb files from fixed .py modules
- Update tinytorch package exports with corrected implementations
- Sync package module index with current 16-module structure
These generated files reflect all the module fixes and ensure consistent
.py ↔ .ipynb conversion with the updated module implementations.
- Fixed test functions to only run when modules executed directly
- Added proper __name__ == '__main__' guards to all test calls
- Fixed syntax errors from incorrect replacements in Module 13 and 15
- Modules now import properly without executing tests
- ProductionBenchmarkingProfiler (Module 14) and ProductionMLSystemProfiler (Module 16) fully working
- Other profiler classes present but require full numpy environment to test completely
- Add tensor_dev.ipynb converted from tensor_dev.py
- Add activations_dev.ipynb converted from activations_dev.py
These notebooks provide interactive learning environments for students
to explore tensor operations and activation functions.
- Delete all 15 .ipynb files from modules/source directories
- Align with TinyTorch's Python-first development philosophy
- .py files are the source of truth, .ipynb files are temporary outputs
- Prevents version control conflicts with notebook metadata
- Students work directly with .py files using Jupytext format
- Notebooks can be regenerated when needed via 'tito nbdev generate'
Removed files:
- All *_dev.ipynb files across modules 01-15
- Keeps repository clean and focused on source code
