Keras-Version: in Model-Definition DnCNN() the parameter use_bnorm is faulty?
mullanptr opened this issue · 2 comments
Hello,
In the Keras Version, in main_train.py the function DnCNN (where the model is defined) has a parameter use_bnorm.
What the name of the parameter implies to me, is that you can specify whether to use batch-normalization, or not.
However, that's not what it does. There will be a Layer for Batch-Normalization included, always.
I assume this is just an indention error, with the if-clause above, isn't it?
What it now does, is only affecting the layer counter...
Ahh sorry - maybe this can be closed again. Seems like I applied an auto-indention -- which messed up the original indention...
So yes the the use_bnorm can be used to include or exclude Batch-Normalization.
Only comment I have remaining is, that a small whitespace within the if-clause is present, which can mess up auto-indention...
No I think you are right, the batch normalization used in the if clause governed by use_bnorm is commented out. The batch normalization is therefore always used, no matter the value of use_bnorm.