I wanted to use the Experiment manager to train a network which takes in input an image of size 1xM and outputs 1 numerical value. My dataset is composed by N of such pairs and usually I feed the network using trainNetwork(TrainIn, TrainOut, layers, options), where TrainIn is a matrix [1 M 1 N] shaped and TrainOut is a numerical array with N elements, and it works. Also the validation set is shaped like this and I input it in trainingOptions using 'ValidationData',{VaIn,VaOut}.
I watched the "How to Set Up Your Own Deep Learning Experiments", and I thought it was enough to let the output of the function be
[ TrainIn, TrainOut, layers, output] = experimentFunction(params)
instead of just [ dataset, layers, output] = experimentFunction(params)
but when I run the Experiment Manager I get the error:
Error(s) occurred while validating the setup function: Caused by: Error using textscan Invalid file identifier. Use fopen to generate a valid file identifier.
and this happens both if I explicit the validation set or not. I imagine that this happens because I am not using a datastore. If I manage to use a datastore for the TrainIn images, then, does it have to be a single datastore containing TrainIn and TrainOut or can I have a datastore input and an array of numbers output? If it must contain both the input and output set, how do I signal to the code which is which?
Thank you in advance.
