the stride of the final representation is 8

[BigPuns]

Thanks for your work, I has implemented the inference demo on my machine, but I have some questions confusing me。

1. In paper，what's the meaning of "the stride of the final representation is eight"， how to control the stride, is that the sum of stride of conv and pool? however it`s not equal。
2. In paper, the network structure is [2, 2, 1, 2, 1, 1, 1]， but the pretrained model "baseline-conv5_e55.mat" structure is [2, 2, 1, 1, 1, 1, 1]，the second pooling layer stride is 1 which different from the paper， and different size of the final feature map, is it a skillful design？
3. I want to convert "baseline-conv5_e55.mat" to caffemodel, i can implement the alexnet part by https://github.com/ecoto/dagnn_caffe_deploy , but the correlation layer has not in caffe layer, so my question is the correlation layer have weights or other parameters? must I convert to this layer?