Vijay Janapa Reddi
4f06392de5
Apply formatting fixes to achieve 10/10 consistency
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- Add 🧪 emoji to all test_module() docstrings (20 modules)
- Fix Module 16 (compression): Add if __name__ guards to 6 test functions
- Fix Module 08 (dataloader): Add if __name__ guard to test_training_integration
All modules now follow consistent formatting standards for release.
2025-11-24 15:07:32 -05:00
Vijay Janapa Reddi
f35f30a1f7
Improve module implementations: code quality and functionality updates
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- Enhance tensor operations and autograd functionality
- Improve activation functions and layer implementations
- Refine optimizer and training code
- Update spatial operations and transformer components
- Clean up profiling, quantization, and compression modules
- Streamline benchmarking and acceleration code
2025-11-13 10:42:49 -05:00
Vijay Janapa Reddi
884f024743
Fix NBGrader metadata for Modules 15 and 16
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Module 15 (Quantization):
- Added locked=true to test_module cell (line 1523)
- Added NBGrader metadata to systems-thinking markdown cell (line 1751)
- Added schema_version: 3 to both cells
Module 16 (Compression):
- Added NBGrader metadata to 6 solution cells:
* measure-sparsity (line 380)
* magnitude-prune (line 511)
* structured-prune (line 675)
* low-rank-approx (line 843)
* distillation (line 1013)
* compress-model-comprehensive (line 1234)
- Added NBGrader metadata to 6 test cells:
* test-measure-sparsity (line 427) - 5 points
* test-magnitude-prune (line 567) - 10 points
* test-structured-prune (line 733) - 10 points
* test-low-rank (line 888) - 10 points
* test-distillation (line 1133) - 15 points
* test-compression-integration (line 1300) - 20 points
- Total: 70 points for Module 16
Result:
- Module 15: 0 P0-BLOCKER, 0 P1-IMPORTANT (was 1 P0 + 1 P1)
- Module 16: 0 P0-BLOCKER, 0 P1-IMPORTANT (was 12 P0)
- Both modules now production-ready for NBGrader deployment(https://claude.com/claude-code )
2025-11-11 14:50:37 -05:00
Vijay Janapa Reddi
5f3591a57b
Reorder modules for better pedagogical flow
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Moved memoization (KV-cache) after compression to align with optimization tier milestones.
Changes:
- Module 15: Quantization (was 16)
- Module 16: Compression (was 17)
- Module 17: Memoization (was 15)
Pedagogical Rationale:
This creates clear alignment with the optimization milestone structure:
- M06 (Profiling): Module 14
- M07 (Compression): Modules 15-16 (Quantization + Compression)
- M08 (Acceleration): Modules 17-18 (Memoization/KV-cache + Acceleration)
Before: Students learned KV-cache before understanding why models are slow
After: Students profile → compress → then optimize with KV-cache
Updated milestone reference in profile_kv_cache.py: Module 15 → Module 17
2025-11-10 19:29:10 -05:00
