Files
TinyTorch/modules/16_quantization/module.yaml
Vijay Janapa Reddi 45a9cef548 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

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YAML

description: 'Precision optimization through INT8 quantization. Students learn to
reduce model size
and accelerate inference by using lower precision arithmetic while maintaining accuracy.
Especially powerful for CNN convolutions and edge deployment.
'
difficulty: advanced
estimated_hours: 6-8
exports:
- tinytorch.quantization
learning_objectives:
- Understand precision vs performance trade-offs
- Implement INT8 quantization for neural networks
- Build calibration-based quantization systems
- Optimize CNN inference for mobile deployment
name: Quantization
number: 17
prerequisites:
- Module 09: Spatial (CNNs)
- Module 16: Acceleration
skills_developed:
- Quantization techniques and mathematics
- Post-training optimization strategies
- Hardware-aware optimization
- Mobile and edge deployment patterns
type: optimization