Commit Graph

7 Commits

Author SHA1 Message Date
Vijay Janapa Reddi
ec3481682b Clean up tensor module: Essential operations only, improved testing pattern 2025-09-28 14:53:37 -04:00
Vijay Janapa Reddi
a4b806156e Improve module-developer guidelines and fix all module issues
- Added progressive complexity guidelines (Foundation/Intermediate/Advanced)
- Added measurement function consolidation to prevent information overload
- Fixed all diagnostic issues in losses_dev.py
- Fixed markdown formatting across all modules
- Consolidated redundant analysis functions in foundation modules
- Fixed syntax errors and unused variables
- Ensured all educational content is in proper markdown cells for Jupyter
2025-09-28 09:42:25 -04:00
Vijay Janapa Reddi
aecef5ac68 Enhance tensor module: Add deep systems analysis and production insights
TENSOR MODULE IMPROVEMENTS: Enhanced pedagogical quality and systems thinking

Key Enhancements:
 Fixed module reference numbers (Module 05 Autograd, Module 02 Activations)
 Updated export instructions (tito module complete 01)
 Added comprehensive systems analysis sections:
   - Memory efficiency at production scale (7B parameter models)
   - Broadcasting in transformer architectures
   - Gradient compatibility and computational graphs

Deep Systems Insights Added:
🧠 Memory optimization strategies for large language models
🧠 Transformer broadcasting patterns and attention mechanisms
🧠 Gradient flow architecture and autograd preparation
🧠 Production connections to PyTorch/TensorFlow patterns

Educational Improvements:
📚 Enhanced Build → Use → Reflect pedagogical framework
📚 Concrete production examples (GPT-3 memory requirements)
📚 Clear connections between tensor design and ML system constraints
📚 Actionable analysis replacing generic placeholder questions

Result: Tensor module now provides deep systems understanding while maintaining
strong implementation foundation. All tests pass, ready for student use.
2025-09-28 08:14:46 -04:00
Vijay Janapa Reddi
9f7248d3d7 Fix import paths: Update all modules to use new numbering
IMPORT PATH FIXES: All modules now reference correct directories

Fixed Paths:
 02_tensor → 01_tensor (in all modules)
 03_activations → 02_activations (in all modules)
 04_layers → 03_layers (in all modules)
 05_losses → 04_losses (in all modules)
 Added comprehensive fallback imports for 07_training

Module Test Status:
 01_tensor, 02_activations, 03_layers: All tests pass
 06_optimizers, 08_spatial: All tests pass
🔧 04_losses: Syntax error (markdown in Python)
🔧 05_autograd: Test assertion failure
🔧 07_training: Import paths fixed, ready for retest

All import dependencies now correctly reference reorganized module structure.
2025-09-28 08:07:44 -04:00
Vijay Janapa Reddi
4aec4ba297 Major reorganization: Remove setup module, renumber all modules, add tito setup command and numeric shortcuts
- Removed 01_setup module (archived to archive/setup_module)
- Renumbered all modules: tensor is now 01, activations is 02, etc.
- Added tito setup command for environment setup and package installation
- Added numeric shortcuts: tito 01, tito 02, etc. for quick module access
- Fixed view command to find dev files correctly
- Updated module dependencies and references
- Improved user experience: immediate ML learning instead of boring setup
2025-09-28 07:02:08 -04:00
Vijay Janapa Reddi
83fb269d9f Complete migration from modules/ to assignments/source/ structure
- Migrated all Python source files to assignments/source/ structure
- Updated nbdev configuration to use assignments/source as nbs_path
- Updated all tito commands (nbgrader, export, test) to use new structure
- Fixed hardcoded paths in Python files and documentation
- Updated config.py to use assignments/source instead of modules
- Fixed test command to use correct file naming (short names vs full module names)
- Regenerated all notebook files with clean metadata
- Verified complete workflow: Python source → NBGrader → nbdev export → testing

All systems now working: NBGrader (14 source assignments, 1 released), nbdev export (7 generated files), and pytest integration.

The modules/ directory has been retired and replaced with standard NBGrader structure.
2025-07-12 12:06:56 -04:00
Vijay Janapa Reddi
23c2f53c2b Add numbered prefixes to complete modules
- Rename complete modules to numbered progression:
  - setup → 00_setup
  - tensor → 01_tensor
  - activations → 02_activations
  - layers → 03_layers
  - networks → 04_networks
  - dataloader → 05_dataloader

- Update test imports to use new numbered module names
- Keep incomplete modules (autograd, training, etc.) unnumbered
- Clear progression: 6 complete modules ready for students
- Maintains rock solid foundation approach with proper imports
2025-07-12 02:12:12 -04:00