Some questions about feeding 2 inputs to any MLP model & train type

[tnguyen87 (Tommy)]

Greetings,

I am constructing a simple MLP model and trying to use 2 different inputs (A and B) to predict y. Before training a model, I need to feed inputs to the model correctly. I define a first layer to be nn.Linear(2,next_dim). I would like to ask whether I need to flatten out all inputs by concatenate(A,B) before feeding to a model? I believe that I have to but not really confident about this! Can anyone confirm this for me by chance, please?

Secondly, if I want to train 2 different models (more like multi model), can I train each model with different type of sending data to a model differently? what I meant is that I use a dataloader to train model A and use a normal batch (dataloader does not involved) to train model B

Thank you in advances,
Tommy

[InnovArul (Arul)]

@tnguyen87

nn.Linear(2,next_dim)

What is 2 here?
Does it mean A, B are of 1-D each?

@tnguyen87

whether I need to flatten out all inputs by concatenate(A,B)

It would help if you could spell out the dimensions of A & B.

@tnguyen87

can I train each model with different type of sending data to a model differently?

Yes, you can. There is no restriction.