Hey Guys,
I am using multiple nn.BatchNorm1d()
layers. I noticed that the activation of the same inputs change slightly when I include the input in different batches. Even when I am using model.eval()
.
So I have input A
and I feed it to the model in the same batch as the the inputs B
and C
. The activation of A
will differ to the Activation of A
when I fed it through the network together with B
C
, D
, E
.
Is this due to the BatchNorm
I feel like model.eval()
, should prevent this behavior. But maybe I am messed up somewhere.
Would there be a option to prevent this behavior