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A CNN model that is trained on GPU and containing a BNORM layer produces wring results (all 0 or 1) when is evaluated (e.g. using RReader) on CPU.
The evaluation that is done in the Classification macro (in Factory::EvcaluateAllMethods) is performed on GPU.
This happens only when the model contains the BNORM layer.
The text was updated successfully, but these errors were encountered:
As reported in https://root-forum.cern.ch/t/tmva-read-image-data-for-application-of-a-cnn-model/54181/15
and shown in this notebook example
https://cernbox.cern.ch/s/U7p6sgH7QN4GRlX
A CNN model that is trained on GPU and containing a BNORM layer produces wring results (all 0 or 1) when is evaluated (e.g. using RReader) on CPU.
The evaluation that is done in the Classification macro (in
Factory::EvcaluateAllMethods
) is performed on GPU.This happens only when the model contains the BNORM layer.
The text was updated successfully, but these errors were encountered: