- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Hardware-Optimized Operations
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Model Compression
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Training
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Optimization Algorithms
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Automatic Differentiation
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Data Loading Systems
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Attention Mechanisms
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Convolutional Networks
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Architectures
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Layers
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Activation Functions
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Tensor Foundation
Improves notebook organization without changing any code logic or content.
- Moved ## 🔧 DEVELOPMENT to proper location at start of Step 2 where actual development begins
- Removed misplaced header from test function area
- Headers now correctly organize: Development → Auto Testing → Module Summary
- Added ## 🔧 DEVELOPMENT section before test functions
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Setup Configuration
Improves notebook organization without changing any code logic or content.
CORRECTED PATTERN NOW:
1. ✅ Integration test (test_module_kernel_sequential_model) - BEFORE ## 🧪 Module Testing
2. ✅ ## 🧪 Module Testing (markdown section)
3. ✅ STANDARDIZED MODULE TESTING (nbgrader cell)
4. ✅ if __name__ == '__main__' block with run_module_tests_auto
5. ✅ ## 🎯 Module Summary (immediately after, no code between)
FIXES APPLIED:
✅ Moved integration test function from AFTER testing section to BEFORE it
✅ Removed duplicate integration test function and markdown section
✅ Added integration test to the if __name__ == '__main__' block
✅ Clean STANDARDIZED MODULE TESTING structure
Module 13_kernels now follows the exact pattern
CORRECTED PATTERN NOW:
1. ✅ Integration tests (test_compression_integration, test_comprehensive_compression_integration) - BEFORE ## 🧪 Module Testing
2. ✅ ## 🧪 Module Testing (markdown section)
3. ✅ STANDARDIZED MODULE TESTING (nbgrader cell)
4. ✅ if __name__ == '__main__' block with run_module_tests_auto
5. ✅ ## 🎯 Module Summary (immediately after, no code between)
FIXES APPLIED:
✅ Moved both integration test functions from AFTER testing section to BEFORE it
✅ Removed duplicate integration test functions and markdown sections
✅ Cleaned up multiple run_module_tests_auto calls - now only one clean call
✅ Proper STANDARDIZED MODULE TESTING structure
Module 12_compression now follows the exact pattern
CORRECTED PATTERN NOW:
1. ✅ Integration test (test_module_optimizer_autograd_compatibility) - BEFORE ## 🧪 Module Testing
2. ✅ ## 🧪 Module Testing (markdown section)
3. ✅ STANDARDIZED MODULE TESTING (nbgrader cell with proper structure)
4. ✅ if __name__ == '__main__' block with run_module_tests_auto
5. ✅ ## �� Module Summary (immediately after, no code between)
FIXES APPLIED:
✅ Moved integration test function from AFTER testing section to BEFORE it
✅ Removed duplicate integration test function
✅ Clean STANDARDIZED MODULE TESTING structure with proper nbgrader cell
✅ No extra code between run_module_tests_auto and Module Summary
Module 10_optimizers now follows the EXACT pattern the user specified
Module 02_tensor now follows the correct pattern learned from layers_dev:
1. ## 🧪 Module Testing (explanation)
2. Standardized testing cell with run_module_tests_auto
3. Actual test functions (test_unit_tensor_creation, test_unit_tensor_properties, test_unit_tensor_arithmetic)
4. ## 🎯 Module Summary
✅ Moved test functions from end of file to proper location after standardized testing
✅ Removed duplicate test functions
✅ Students now see actual test implementations before the summary
✅ run_module_tests_auto will auto-discover and run all tests
Cleaned up duplicate/redundant nbgrader cells that were just comments referencing test functions. The actual test functions remain in their proper location after the standardized testing section.
Removed:
- Duplicate test-personal-info nbgrader cell (just a comment)
- Duplicate test-system-info nbgrader cell (just a comment)
- Redundant 'Inline Test Functions' section
This eliminates confusion and follows the clean pattern established by other modules.
Module 01_setup now follows correct pattern:
1. ## 🧪 Module Testing (explanation)
2. Standardized testing cell with run_module_tests_auto
3. Actual test functions (test_unit_personal_info_basic, test_unit_system_info_basic)
4. ## 🎯 Module Summary
This ensures students see actual test implementations before the summary.
Ensures consistent testing framework across all TinyTorch modules with:
✅ Added standardized testing sections to modules that were missing them:
- 01_setup: Added complete testing section + module summary
- 02_tensor: Added testing section + comprehensive module summary
- 15_mlops: Standardized existing testing section to match convention
✅ All modules now follow the consistent pattern:
1. ## 🧪 Module Testing (markdown explanation)
2. Locked nbgrader cell with standardized-testing ID
3. run_module_tests_auto call to discover and run all tests
4. ## 🎯 Module Summary (educational wrap-up)
✅ Benefits:
- Consistent testing experience across all 16 modules
- Automatic test discovery and execution before module completion
- Standardized educational flow: learn → implement → test → reflect
- Professional testing practices with locked testing framework
✅ Verification: All 16 modules now have both:
- '## 🧪 Module Testing' section ✓
- 'run_module_tests_auto' call ✓
This ensures students always verify their implementations work correctly
before moving to the next module, following TinyTorch's educational philosophy.
- Remove loose test code from nbgrader cells that ran automatically on import
- Keep only proper test_unit_personal_info_basic() and test_unit_system_info_basic() functions
- Prevents tests from running when module is imported as package
- Follows established test naming conventions (test_unit_*)
- Improves module reliability and reduces side effects
Fixed issues:
- NBGrader cells now reference test functions instead of running test code directly
- All assertions and test logic properly contained in named test functions
- Module can be imported without automatically executing tests
- 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
- Updated module.yaml files for 05_dense and 06_spatial to reference correct dev file names
- Fixed #| default_exp directives in dense_dev.py and spatial_dev.py to export to correct module names
- Fixed tensor assignment issues in 12_compression module by creating new Tensor objects instead of trying to assign to .data property
- Removed missing function imports from autograd integration test
- All individual module tests now pass (01_setup through 14_benchmarking)
- Generated correct module files: dense.py, spatial.py, attention.py
✅ NBGrader solution/test structure: ### BEGIN/END SOLUTION blocks
✅ Educational TODO sections: STEP-BY-STEP, HINTS, EXAMPLES, LEARNING CONNECTIONS
✅ Immediate unit tests: proper assertions after each solution
✅ TinyTorch consistency: same patterns as tensor, layers, activations modules
✅ All tests passing: 100% success rate with comprehensive coverage
Module now follows established TinyTorch educational format:
- Detailed TODO instructions for student implementation
- Solution blocks wrapped in NBGrader tags
- Immediate feedback with unit tests after each piece
- Progress tracking with emojis and clear status messages
Ready for NBGrader processing and student use.
- Implement scaled dot-product attention with masking support
- Build multi-head attention with learnable projections
- Create sinusoidal positional encoding for sequence understanding
- Add layer normalization for training stability
- Complete transformer block with residual connections
- Include self-attention wrapper and utility functions
- Full inline testing with 100% pass rate
- Educational content explaining attention mechanisms
- Foundation for modern AI architectures (GPT, BERT, etc.)
This module bridges classical ML (tensors, layers, networks) with
modern transformer architectures that power ChatGPT and contemporary AI.
- Added educational metadata (difficulty, time_estimate) to all module.yaml files
- Updated convert_readmes.py to read from YAML instead of hardcoded mappings
- Standardized difficulty progression: ⭐ → ⭐⭐ → ⭐⭐⭐ → ⭐⭐⭐⭐ → ⭐⭐⭐⭐⭐🥷
- Fixed path resolution for YAML reading in book build process
- Eliminated duplication: single source of truth for educational metadata
- Capstone gets special ninja treatment (⭐⭐⭐⭐⭐🥷) as beyond-expert level
- Updated book generation to include 15_capstone with 5-star difficulty rating
- Changed time estimate from '20-40 hours' to 'Capstone Project' for better visitor experience
- Removed specific week references from project phases for more encouraging presentation
- Maintained detailed project structure while making timeline more flexible
- Ensures consistent 5-star rating for expert-level modules across the framework
- Added bold formatting to match other modules' style
- Enhanced clarity with more specific descriptors
- Added 'efficiently' and 'with proper broadcasting' for precision
- Now consistent with activations and other modules formatting
- Improves visual hierarchy and readability in built book
