Solved by ptrblck in post #2 
              
              
                The model output wouldn’t necessarily need to change for the mentioned use cases, but the loss functions and targets. 
E.g. if you would like to predict N floating point values, your model could output a tensor in the shape [batch_size, N] and you could use e.g. nn.MSELoss for this regression task. 
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