A common practice, as seen in Vaswani et al. (2017)’s setup, is to jointly learn BPE for both source and target languages, which facilitates three-way weight sharing between the encoder’s input, the decoder’s input, and the output (i.e. classifier’s class) embeddings (Press and Wolf, 2017).
to facilitate fine-grained analysis of vocabulary sizes and their effect on class imbalance, our models separately learn source and target vocabularies; weight sharing between the encoder's  combined in Figure 4.