differences between Caffe and Keras when applying MAX pooling

Question

I was working on a project to convert keras json model to caffe prototxt
caffe supports arbitrary padding values
keras (on top of tensorflow) supports \'same\' and

Answer 1

Differences in implementation of Pooling - In keras, the half-windows are discarded. Caffe will put additional output for half-windows.
Differences in Padding schemes - The 'same' padding in keras can sometimes result in different padding values for top-bottom (or left-right). caffe always pad evenly on both sides so the top-bottom (or left-right) padding values are always equal.