This repo holds the files for the PyTorch Quantization Workshop conducted by Suraj Subramanian at the MLOpsWorld Conference on June 8 2022.
Learn the fundamentals of quantization in pure Python code.
Learn about quantization schemes, when some are better than others, and using QConfigs in PyTorch
The number of available options can be overwhelming. Choosing the correct quantization technique and scheme is an empirical process; this notebook contains a workflow that aids choosing the most suitable option to quantize your FP32 model.
- An x86 or ARM CPU
- PyTorch 1.10.0+
- Quantization — PyTorch 1.11.0 documentation
- Practical Quantization in PyTorch
- FX Graph Mode Quantization User Guide
- PyTorch Forum - Quantization
- PyTorch Github Issues
If you encounter a bug, please open an issue or a PR. See CONTRIBUTING.MD