Sorry.
I didn’t know about which specific layer effects such behaviour and only knew that it may be Dropout or BatchNormalization or like this cause with the same sample my losses fluctuated a bit every run.
But the main problem that I cannot get predictions and losses simultaneously.
To get predictions I need to set model.eval(), to get losses I need to set model.train() and at the time I run the methods one by one with the same sample to get losses and predictions.
So could I get desired ouput without dual run?