nt neural networks (RNN) <span class="citation" data-cites="mehri2017samplernn kalchbrenner2018efficient">(Kalchbrenner et al. 2018, Mehri et al. 2017)</span>. Their heavy computational requirements were a disadvantage for both training and performance. Further optimizations with parallel computations emerged <span class="citation" data-cites="oord2017parallel lamtharn_hantrakul_2019_3527860 yamamoto2020parallel song2021improved">(Hantrakul et al. 2019, Oord et al. 2017, Song et al. 2021, Yamamoto et al. 20