As a submodule of PaddlePaddle framework, PaddleSlim is an open-source library for deep model compression and architecture search. PaddleSlim supports current popular deep compression techniques such as pruning, quantization, and knowledge distillation. Further, it also automates the search of hyperparameters and the design of lightweight deep architectures. In the future, we will develop more practically useful compression techniques for industrial-level applications and transfer these techniques to models in NLP.
## 功能
- 模型剪裁
- 支持通道均匀模型剪裁（uniform pruning)
- 基于敏感度的模型剪裁
- 基于进化算法的自动模型剪裁三种方式
## Methods
-量化训练
-在线量化训练（training aware）
-离线量化（post training）
-支持对权重全局量化和Channel-Wise量化
-Pruning
-Uniform pruning
-Sensitivity-based pruning
-Automated model pruning
- 蒸馏
- Quantization
- Training-aware quantization: Quantize models with hyperparameters dynamically estimated from small batches of samples.
- Training-aware quantization: Quantize models with the same hyperparameters estimated from training data.
- Support global quantization of weights and Channel-Wise quantization
