- Added environment validation with dependency checking
- Implemented performance benchmarking for CPU and memory
- Created development environment setup with Git/Jupyter checks
- Built comprehensive system reporting with health scoring
- Maintained educational patterns and inline testing
- Added professional ML systems configuration practices
All functions work correctly with proper error handling and testing.
- Remove all tests/ directories under modules/source/
- Keep main tests/ directory for testing exported functionality
- Update status command to check tests in main tests/ directory
- Update documentation to reflect new test structure
- Reduce maintenance burden by eliminating duplicate test systems
- Focus on inline NBGrader tests for development, main tests for package validation
- Remove all .ipynb files from modules/source/ directories
- Follow Python-first development workflow where .py files are source of truth
- .ipynb files should be temporary outputs generated only for NBGrader work
- Keeps repository clean and follows project conventions
Removed notebooks:
- modules/source/00_setup/setup_dev.ipynb
- modules/source/01_tensor/tensor_dev.ipynb
- modules/source/03_layers/layers_dev.ipynb
- modules/source/04_networks/networks_dev.ipynb
- modules/source/05_cnn/cnn_dev.ipynb
- modules/source/06_dataloader/dataloader_dev.ipynb
- modules/source/07_autograd/autograd_dev.ipynb
- Replace all 'python bin/tito.py' references with correct 'tito' commands
- Update command structure to use proper subcommands (tito system info, tito module test, etc.)
- Add virtual environment activation to all workflows
- Update Makefile to use correct tito commands with .venv activation
- Update activation script to use correct tito path and command examples
- Add Tiny🔥Torch branding to activation script header
- Update documentation to reflect correct CLI usage patterns
- Added detailed ML systems context and architecture overview
- Enhanced conceptual foundations for system configuration
- Improved personal info section with professional development context
- Expanded system info section with hardware-aware ML concepts
- Added comprehensive testing explanations
- Connected to real-world ML frameworks and practices
- Improved learning scaffolding and step-by-step guidance
- Remove unnecessary module_paths.txt file for cleaner architecture
- Update export command to discover modules dynamically from modules/source/
- Simplify nbdev command to support --all and module-specific exports
- Use single source of truth: nbdev settings.ini for module paths
- Clean up import structure in setup module for proper nbdev export
- Maintain clean separation between module discovery and export logic
This implements a proper software engineering approach with:
- Single source of truth (settings.ini)
- Dynamic discovery (no hardcoded paths)
- Clean CLI interface (tito package nbdev --export [--all|module])
- Robust error handling with helpful feedback
