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