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I don’t have much experience in pytorch or neural networks, but from what I understand, if I concatenate the constant vector, I have to do it to each of the inputs of the training set, so I multiply by 4 the memory, and since I am using a very large set of training, I think that is not an option.
I have drawn a diagram of the inputs and outputs of the model, I use it to generate the training set, as you can see the model uses only the three vectors of size 80.
I wonder if there is any way to introduce this information in the NN to invert the model and without quadrupling the information of the training set.