Progress Update from Neural Network Trainer running on Parallel Server Cloud

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SMEAC
SMEAC 2023-10-19
评论： Sam Marshalik 2023-10-20
I am performing some training of a neural network using some pretty standard code:
[net1,tr] = train(net1,X,Y1,'useParallel','yes')
When I do the training locally, the Neural Network Training window, gets constantly updated, and I can follow the progress of the Epochs and the Performance. Aborting the training if something is not working.
However, I also have Amazon AWS Setup as cloud support for the parallel toolbox.
When I activate the Parallel Pool and the training uses the cloud, I get no update at all. The Neural Network Training Window, stays at Epoch 0 of 10000, until all training is completed. Even if this is several hours. :(
Is there a way to force how often updates are reported back from the parallel pool? Or do I need to script it myself, forcing a limit of 100 Epochs per training call, and continually pass the trained network back and forwards?
Thanks in advance
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SMEAC
SMEAC 2023-10-19
When I run the parallel Toolbox on my own computer, I get an update too.
But when the Parallel Pool is remote on AWS, I get no update at all.
Sam Marshalik
Sam Marshalik 2023-10-20
I spun up a MATLAB Parallel Server cluster using Cloud Center and ran the job there without any issues. I could see the epoch progress, just like I could with a local parallel pool:
I will note that it took a bit for the epochs to start moving, so make sure you wait a minute to ensure nothing is actually populating there.
If you are running MATLAB Parallel Server in Cloud Center like I am, I would expect you to see the progress as I can. I would suggest reaching out to Technical Support.

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