Initial model generation

[SawsanAbdulRahman]

On the client side, when running the application, I can see that the initial model used is the one located in assets folder. If we create the initial model on the server (PhotoLabellerServer/model/src/main/kotlin/com/mccorby/photolabeller/ml/Main.kt), and then we use the generated model in the app, the model misbehaves; The prediction for the images as well as the scores at each iteration when training the new model show a NaN values.

So how the initial model in the assets folder has been generated ?

[mccorby]

Hi,
Thanks for trying this project. I have just train the model and deployed it in the app and could it see it working as expected (at least the prediction)
Does the model work on the server? I mean, does the predictions work on this project with the model?

If it does, could you try training the model again? The system is not very stable (please note this is a PoC) due to the use of images in Android but those NaN are not expected

If nothing else works, could you send me the model to <my_Github_user_name> at gmail?

[SawsanAbdulRahman]

I figured out that the server sometimes generate good models (cifar_federated of 4825 KB) that works fine on the mobile device and sometimes it doesn't (cifar_federated of 7KB) where it shows NaN values on the clients. Yet in both cases, the eval function on the server side doesn't work, i get the following error:
=====eval model========
Exception in thread "main" java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at com.intellij.rt.execution.CommandLineWrapper.main(CommandLineWrapper.java:67)
Caused by: java.lang.IllegalArgumentException: bound must be positive
at java.util.Random.nextInt(Random.java:388)
at org.nd4j.linalg.util.ArrayUtil.buildInterleavedVector(ArrayUtil.java:1679)
at org.nd4j.linalg.cpu.nativecpu.CpuNDArrayFactory.shuffle(CpuNDArrayFactory.java:814)
at org.nd4j.linalg.factory.Nd4j.shuffle(Nd4j.java:452)
at org.nd4j.linalg.dataset.DataSet.shuffle(DataSet.java:619)
at org.datavec.image.loader.CifarLoader.convertDataSet(CifarLoader.java:380)
at org.datavec.image.loader.CifarLoader.next(CifarLoader.java:424)
at org.datavec.image.loader.CifarLoader.next(CifarLoader.java:392)
at org.deeplearning4j.datasets.iterator.impl.CifarDataSetIterator.next(CifarDataSetIterator.java:110)
at com.mccorby.photolabeller.ml.trainer.CifarTrainer.eval(CifarTrainer.kt:100)
at com.mccorby.photolabeller.ml.MainKt.main(Main.kt:39)
... 5 more

[koustabhdolui]

Hello @mccorby and @SawsanAbdulRahman. Great work @mccorby to implement Federated Learning. I came across your article on proandroiddev. I am trying to work with this repository. However, I am unable to make it run. Can you suggest what configuration I should choose on IntelliJ?
com.mccorby.photolabeller.ml.MainKt as the main class does not work.
I get an error saying com.mccorby.photolabeller.ml.MainKt is not found in module "PhotoLabellerServer".