Commit Graph

7 Commits

Author SHA1 Message Date
Vijay Janapa Reddi
40ad9e01a2 Add structural organization headers to 12_compression module
- 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.
2025-07-20 10:08:42 -04:00
Vijay Janapa Reddi
80fb5cb111 Fix 12_compression: Move integration tests BEFORE testing, clean structure
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
2025-07-20 09:42:47 -04:00
Vijay Janapa Reddi
23b4c4353b Fix 12_compression: Add missing Module Summary section
Module 12_compression now follows the complete standardized pattern:
1. ## 🧪 Module Testing (explanation)
2. Standardized testing cell with run_module_tests_auto
3. Integration test functions
4. ## 🎯 Module Summary (educational wrap-up) ← ADDED

 Added comprehensive Module Summary covering:
- Model compression techniques (pruning, quantization)
- Production deployment skills
- Mathematical foundations
- Real-world applications and industry connections
- Professional development outcomes

All 16 modules now follow the complete standardized testing pattern
2025-07-20 09:09:47 -04:00
Vijay Janapa Reddi
771ed98a80 🧹 Remove Jupyter notebooks from modules/source - Python-first workflow
- 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
2025-07-20 08:41:26 -04:00
Vijay Janapa Reddi
f77db43975 Production: Standardize test naming in optimization and deployment modules
- Compression: test_compression_metrics → test_unit_compression_metrics
- Compression: test_magnitude_pruning → test_unit_magnitude_pruning
- Compression: test_quantization → test_unit_quantization
- Compression: test_distillation → test_unit_distillation
- Compression: test_structured_pruning → test_unit_structured_pruning
- Compression: test_comprehensive_comparison → test_unit_comprehensive_comparison
- Kernels: All test_* → test_unit_* except test_kernel_integration_* → test_module_*
- Benchmarking: All test_* → test_unit_* except test_comprehensive_* → test_module_*
- MLOps: All test_* → test_unit_* except test_comprehensive_integration → test_module_*
- Finalizes test naming standardization across production-ready modules
2025-07-20 08:39:27 -04:00
Vijay Janapa Reddi
442e860d5f Fix module file naming and tensor assignment issues
- 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
2025-07-18 01:56:07 -04:00
Vijay Janapa Reddi
59d58718f9 refactor: Implement learner-focused module progression with better naming
 Renamed modules for clearer pedagogical flow:
- 05_networks → 05_dense (multi-layer dense/fully connected networks)
- 06_cnn → 06_spatial (convolutional networks for spatial patterns)
- 06_attention → 07_attention (attention mechanisms for sequences)

 Shifted remaining modules down by 1:
- 07_dataloader → 08_dataloader
- 08_autograd → 09_autograd
- 09_optimizers → 10_optimizers
- 10_training → 11_training
- 11_compression → 12_compression
- 12_kernels → 13_kernels
- 13_benchmarking → 14_benchmarking
- 14_mlops → 15_mlops
- 15_capstone → 16_capstone

 Updated module metadata (module.yaml files):
- Updated names, descriptions, dependencies
- Fixed prerequisite chains and enables relationships
- Updated export paths to match new names

New learner progression:
Foundation → Individual Layers → Dense Networks → Spatial Networks → Attention Networks → Training Pipeline

Perfect pedagogical flow: Build one layer → Stack dense layers → Add spatial patterns → Add attention mechanisms → Learn to train them all.
2025-07-18 00:12:50 -04:00