Machine translation shared embeddings
**Describe the bug**

If my understanding is correct, an [MTEncDecModel](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/nlp/models/machine_translation/mt_enc_dec_model.py#L54) exposes no options for sharing embeddings between the encoder and decoder, but this seems to be the de facto standard. E.g. from the AAYN white paper:

> ...we share the same weight matrix between the two embedding layers and the pre-softmax linear transformation

So MT models with shared vocab will learn separate embeddings for each token on both sides.

**Expected behavior**

An option like `cfg.share_embeddings = True` to tie the encoder/decoder embedding weights.