Summary:
This is a bit large diff, sorry about it. It includes basic shape and type inference functionality, based on YQ's Schema scaffolding. I added some helper functions to make it easier to write simple translations.
Bigger refactoring was needed for ConvPoolBase so that we could use the shape inference already there in the schema.
I annotated enough operators to be able to infer forward-pass of shapes for basic convnet, and added test for that. I intend to bootcamp some annotations and annotate enough to handle Resnets fully. Need to think about gradients, if they could be annotated in an easier way.
Only shapes are now exposed to Python, types will follow later. Also the inference is not called yet anywhere but unit test.
Also I am not sure if everything is in the best location in the code, but shouldn't be hard to move stuff around.
Reviewed By: dzhulgakov
Differential Revision: D4436818
fbshipit-source-id: eebee5937ccc9ac09c245465302388a1fae6933c