Which ROOT version are you using ? I could not reproduce this with the latest one. Also, which architecture are you using for the DNN ? The CPU or the GPU ones ?
Thank you for posting the files. I will investigate it and let you know
did you saw what was wrong?
I could reproduce your problem with your code, but I could not find the cause.
Using different data set works fine.
It cannot be the reading of the model, because his is tested in the first macro when calling Factory::EvaluateAllMethods.
I will continue investigating and I will let you know
I have found that in your Reader application you are not using the same inputs variables as when you run the train. You are applying a log() to several of the input features, but in TMVApplication you don’t use the log.
For example you should do:
r_lep_Pt_0 = log(lep_Pt_0);
As shown in the tutorials tmva/TMVAClassificationApplication.C you need to apply the expression to the variables.
You need to be sure to have the same input type of data. I would suggest you to check that.
Also it is not clear to me what you are doing exactly with the variables jet_PT. It seems in some files some array elements are not defined. You need to have the same inputs for all files, otherwise this can cause problems
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Sorry for the late reply! Are you still having this issue ?
Getting a n output of a DNN which is always the same means that the activation functions are saturated. This can happen when the input variable distributions are very different from what has been used for training.
You need to be sure that these distributions are similar