MAJOR IMPROVEMENT: Simplified test discovery logic
- Removed restrictive valid_patterns requirement from testing framework
- Any function starting with 'test_' is now automatically discovered
- Follows standard pytest conventions - no maintenance overhead
- Eliminates need to manually add patterns for new test functions
CLEANED UP: Test function names across all 10 modules
- Removed redundant '_comprehensive' suffix from all test functions
- Updated 40+ test function names to be more concise and readable:
* 00_setup: 6 functions (test_personal_info, test_system_info, etc.)
* 01_tensor: 4 functions (test_tensor_creation, test_tensor_properties, etc.)
* 02_activations: 1 function (test_activations)
* 03_layers: 3 functions (test_matrix_multiplication, test_dense_layer, etc.)
* 04_networks: 4 functions (test_sequential_networks, test_mlp_creation, etc.)
* 05_cnn: 3 functions (test_convolution_operation, test_conv2d_layer, etc.)
* 06_dataloader: 4 functions (test_dataset_interface, test_dataloader, etc.)
* 07_autograd: 6 functions (test_variable_class, test_add_operation, etc.)
* 08_optimizers: 5 functions (test_gradient_descent_step, test_sgd_optimizer, etc.)
* 09_training: 6 functions (test_mse_loss, test_crossentropy_loss, etc.)
* 10_compression: 6 functions (already cleaned up)
VERIFICATION: All tests still pass
- All 10 modules tested successfully with new discovery logic
- Total test count maintained: 47 inline tests across all modules
- No functionality lost, only improved maintainability
RESULT: Much cleaner, more maintainable testing framework following standard conventions
- Updated all _dev.py files to use 'comprehensive test' instead of 'integration test'
- Changed function names: test_*_integration() → test_*_comprehensive()
- Updated markdown headers, print statements, success/error messages
- Clarifies that these are comprehensive tests of single modules, not cross-module integration
- Real cross-module integration tests remain in tests/ directory
- Updated modules: 00_setup, 01_tensor, 02_activations, 03_layers, 04_networks, 05_cnn, 06_dataloader, 07_autograd
- Remove student-facing bloat (learning objectives, time estimates, pedagogical details)
- Remove assessment sections (not needed for operational metadata)
- Streamline to essential system information only:
- Module identification and dependencies
- Package export configuration
- File structure and component listings
- Updated existing files (6): setup, tensor, activations, layers, autograd, optimizers
- Created missing files (3): networks, cnn, dataloader
- Consistent 25-26 line format across all 9 modules
Result: Pure operational metadata for CLI tools and build systems
Perfect for instructor/staff development workflow
- 00_setup: Fix naming inconsistency (setup_health → setup_score)
- Tests expected 'setup_score' key but implementation returned 'setup_health'
- Updated all references to use consistent 'setup_score' naming
- Result: 37/37 tests now passing
- 05_cnn: Fix flatten function shape expectations
- Comprehensive tests expected (4,) shape but integration tests expected (1,4) shape
- Made comprehensive tests consistent with integration test expectations
- Flatten function now correctly preserves batch dimension for realistic usage
- Result: 39/39 tests now passing
- 08_optimizers: Fix recursion error in test execution
- Direct test call was causing infinite recursion loop
- Removed problematic direct test call, rely on auto-discovery system
- Result: 5/5 tests now passing
All inline tests now pass: 214/214 tests (100% success rate)
- Move testing utilities from tinytorch/utils/testing.py to tito/tools/testing.py
- Update all module imports to use tito.tools.testing
- Remove testing utilities from core TinyTorch package
- Testing utilities are development tools, not part of the ML library
- Maintains clean separation between library code and development toolchain
- All tests continue to work correctly with improved architecture
- Replaced 3 overlapping documentation files with 1 authoritative source
- Set modules/source/08_optimizers/optimizers_dev.py as reference implementation
- Created comprehensive module-rules.md with complete patterns and examples
- Added living-example approach: use actual working code as template
- Removed redundant files: module-structure-design.md, module-quick-reference.md, testing-design.md
- Updated cursor rules to point to consolidated documentation
- All module development now follows single source of truth
- 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
