Hi, I am comparing few zoo models implementation in DL4J with Pytorch zoo models and found
that the padding in Convolution layers does not match most of time ?
For  Resnet50 and SqueezeNet  :
In DL4J, they  do not  apply padding : [0, 0] ; while in PyTorch they have padding [1, 1].
This results in different output in layers
In DL4J, they apply  Bias  in Conv layers while in PyTorch, they do not.
Why such irregularities in Network structure across frameworks ?