Aligning with ONNX (from minutes of 5 Sep 2019 call)

Hi,

Firstly, apologies that neither Ben nor I can make the teleconferences, so were unable to say this in person.

We noticed that there was discussion about not aligning with ONNX on the most recent call. This was slightly surprising since we (Apple) assumed that the decision in https://github.com/webmachinelearning/webnn/issues/17 <https://github.com/webmachinelearning/webnn/issues/17> was a resolution.

While we didn't comment there, we would prefer to align with ONNX at the moment. Can we stick with this resolution for a while before investigating alternatives? What is the driving need for change right now? Unless I'm mistaken, the decision was to start with a small subset of ONNX and then see how compatible it is with JS frameworks. Is there new information?

As Rafael pointed out in the meeting, ONNX has the advantage of being neutral (although there was a question about its neutrality, which I don't understand). 

Dean