Summary:
This is a first step in improving our RNN story. It provides a wrapper around current RecurrentNetworkOp implementation which infers most of the redundant parameters and makes API much simpler.
Also in order to support general step nets I added an extra argument to the RecurrentNetworkOp.
Future work:
1. Inferring step net output and internal blobs (scratches) sizes and type
2. Avoid accessing blobs by names in c++ part
3. Remove requirement for inputs / output 1:1 correspondence in the step net
4. Make python API support networks with operators like Sum being on the boarder of the Cell net (currently there is an issue with such networks where gradient blobs which are on the side are not explicitly created).
Differential Revision: D4268503
fbshipit-source-id: f8a66491c2b55daa730caeed7e9f2b3921541b49
c2d28fb874