Looking forward to your WebGPU ML runtime! Also, why not contribute back to WONNX? (https://github.com/webonnx/wonnx)
I sent you an email a few weeks back - would be great to chat!
WONNX is a seriously impressive project. There is a few reason I didn't just contribute back to WONNX:
1. WONNX does not parse the ONNX model into an IR, which I think is essential to have the freedom to transform the model as required.
2. When I started, WONNX didn't seem focused on symbolic dimensions (but I've seen you shipping the shape inference recently!).
3. The code quality has to be much higher when it's open source! I wanted to hack on this without anyone to please but myself.
In my opinion, ONNX is more complex than necessary. Therefore, I opted to convert it to an intermediate representation (IR) first, which is then used to generate source code. A key advantage of this approach is the ease of merging nodes into corresponding operations, since ONNX and Burn don't share the same set of operators.
ONNX is 100% more complex than necessary. Another format of interest is NNEF: https://www.khronos.org/nnef