gradient noise vs variational weight noise
Hi, I notice that the variational noise for RNNT model is implemented as gradient noise addition (line 878 of `nemo/collections/asr/models/rnnt_models.py`). The variational noise cited by the Conformer-Transducer paper is actually adding noise to weights. So, is this a mistake or because injecting gradient noise works better than adding weight noise?
