Now the baseline model is using keras for VAE, and I want to reimplement them in pytorch. I can fix the input part by this transformation. But not sure how to do this for the decoder output.
To be more specific, in the pytorch implementation, the input is [batch, filter/channel, timestep/length]. And if I want to follow the structure of baseline models, which outputs [batch, timestep/length, filter/channel] (in keras), do you think it’s reasonable to use this transpose on the output for loss calculation?