wnnx is a new model format which exports models directly from pytorch without onnx. It can be infered via wnn framework, the infer lib is also incrediablly simple and insamely small to serveral kbs.
Even though, wnn can achieve a extremly fast speed and low memory consumption in both X86 and arm platform.
wnnx_models contains some popular models which exports from pytorch. It can be viewed using:
pip install wnetron
wnetron .
When wnnx merged by netron official repo, you can also view wnnx model with netron as well.
SimpleFC:
MobilenetV3:
DynamicLayernorm:
As you can see, wnnx can be fully replace onnx as an option to inference model. It has many strength compare with onnx:
- Powered with flatbuffer, instead using protobuf which is heavy;
- Easy to convert from trained model via pytorch;
- Without any glu ops, the whole graph is extremly clean;
- Can be efficiently inferenced via wnn.