Deep Learning Toolbox: Inputs and Outputs

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Blake Van Winkle
Blake Van Winkle el 17 de Oct. de 2019
Comentada: Blake Van Winkle el 25 de Oct. de 2019
Hi everyone, I have started to transition from my own Matlab ML tool suite into the Deep Learning toolbox, and I have been unable to do the most simple of problems (a vector of elements for an input and a vector of elements for an output). Do you all know how to do this with mulitple hidden layers?
I have tried two different paths, and so far, I have failed royally.
For the 'trainNetwork', I am looking for an input layer for something that isn't a matrix in time sequence or not, but I am able to output a vector of outputs.
For 'train', I have been able to figure out how to define multiple inputs, but I am unable to output more than one value from the final layer.
This is rather dumbfounding, and I hope one of you have figured out how to fix this problem.
The image below may help you all grasp what I am trying to do, and I should note that this will be integrated into an AutoML process to define the network structure, so a GUI based answer won't work.
Matlab 19a with Deep Learning Toolbox, but I could transfer to 19b (I believe) if required.

Respuesta aceptada

Blake Van Winkle
Blake Van Winkle el 25 de Oct. de 2019
If you are having this issue, I found that it was much easier to just use imageInputLayer but not have it defined as an image format.
For a vector: imageInputLayer([n,1,1])
For a 2d matrix: imageInputLayer([n,m,1])
For a 3d matrix: imageInputLayer([n,m,o])
Thanks for other suggestions...

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Sai Bhargav Avula
Sai Bhargav Avula el 23 de Oct. de 2019
Hi,
If the network also has multiple inputs and outputs, then you must define the network as a function and train the network using a custom training loop. for more information.
For a detailed understanding on how to it needs to be done refer the following link.
Hope this helps
  1 comentario
Blake Van Winkle
Blake Van Winkle el 25 de Oct. de 2019
To Sai:
While I am assuming the documentation makes sense to some, it is clear as mud to me. You wouldn't happen to have an example handy?
Thanks

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