Hi everyone,
I have a project ongoing about making neural networks faster and lighter in terms of parameters for fastai:
Currently, there are 3 techniques implemented:
- Neural Network sparsifying: make the network sparse
- Neural Network pruning: remove the useless convolution filters
- Batch Normalization folding, that I already explained here
I’m planning to continue to develop it and add new techniques such as quantization, knowledge distillation,… and also to make it compatible with fastai2
If anyone is interested to contribute, tell me 