I have a layer using 3x3 max pooling layer in caffe
layer {
  name: "pool"
  type: "Pooling"
  bottom: "conv1"
  top: "pool"
  pooling_param {
    pool: MAX 
    kernel_size: 3
    stride: 2
    engine: CUDNN
  }
}

I tried to convert it to pytorch by
self.pool= nn.MaxPool3d(kernel_size=3, stride=2)

For input feature size of torch.Size([1, 64, 32, 32, 32]), the caffe output size is 1, 64, 16, 16, 16, while the pytorch is 1,64,15,15,15. What is happen?