We evaluate decoding architectures using different levels of granularity in the vocabulary units and the attention mechanism, including the standard decoding architecture implemented either with subword (Sennrich et al., 2016) or fully character-level <cite>(Cherry et al., 2018)</cite> units, which constitute the baseline approaches, and the hierarchical decoding architecture, by implementing all in Pytorch (Paszke et al., 2017) within the OpenNMT-py framework (Klein et al., 2017) .