This comprehensive update ensures all TinyTorch modules follow consistent NBGrader
formatting guidelines and proper Python module structure:
- Fix test execution patterns: All test calls now wrapped in if __name__ == "__main__" blocks
- Add ML Systems Thinking Questions to modules missing them
- Standardize NBGrader formatting (BEGIN/END SOLUTION blocks, STEP-BY-STEP, etc.)
- Remove unused imports across all modules
- Fix syntax errors (apostrophes, special characters)
- Ensure modules can be imported without running tests
Affected modules: All 17 development modules (00-16)
Agent workflow: Module Developer → QA Agent → Package Manager coordination
Testing: Comprehensive QA validation completed
- Added ProductionBenchmarkingProfiler class with end-to-end profiling
- Implemented resource utilization monitoring and bottleneck detection
- Added A/B testing framework with statistical significance
- Included performance regression detection and capacity planning
- Added comprehensive ML systems thinking questions
Updates markdown headers in development files to improve consistency and readability.
Removes the redundant "🔧 DEVELOPMENT" headers and standardizes the subsequent headers to indicate the purpose of the following code, such as "🧪 Test Your Matrix Multiplication". This change enhances the clarity and organization of the development files.
- Insert ## 🔧 DEVELOPMENT header before first test function
- Organizes module according to educational structure guidelines
- Maintains all existing functionality and test execution
- Improves readability and navigation for educational use
Removes redundant "DEVELOPMENT" headers from several notebook files.
These headers are no longer necessary and declutter the notebook content, improving readability and focus on the core content and testing sections.
- Added test_unit_benchmark_scenarios() call after function definition
- Fixed test_statistical_validation() → test_unit_statistical_validation()
- Added test_unit_tinytorch_perf() call after function definition
- Fixed test_performance_reporter() → test_unit_performance_reporter()
- Fixed test_comprehensive_benchmarking() → test_module_comprehensive_benchmarking()
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Performance Benchmarking
Improves notebook organization without changing any code logic or content.
Vijay Janapa Reddi