• Layer type: Pooling

• Doxygen Documentation

• Header: ./include/caffe/layers/pooling_layer.hpp

• CPU implementation: ./src/caffe/layers/pooling_layer.cpp

• CUDA GPU implementation: ./src/caffe/layers/pooling_layer.cu

• Input

  • n * c * h_i * w_i

• Output

  • n * c * h_o * w_o, where h_o and w_o are computed in the same way as convolution.

• Parameters (PoolingParameter pooling_param)

  • Required
    • kernel_size (or kernel_h and kernel_w): specifies height and width of each filter
  • Optional
    • pool [default MAX]: the pooling method. Currently MAX, AVE, or STOCHASTIC
    • pad (or pad_h and pad_w) [default 0]: specifies the number of pixels to (implicitly) add to each side of the input
    • stride (or stride_h and stride_w) [default 1]: specifies the intervals at which to apply the filters to the input

• From ./src/caffe/proto/caffe.proto:

{% highlight Protobuf %} {% include proto/PoolingParameter.txt %} {% endhighlight %}

• Sample (as seen in ./models/bvlc_reference_caffenet/train_val.prototxt)

  layer {
    name: "pool1"
    type: "Pooling"
    bottom: "conv1"
    top: "pool1"
    pooling_param {
      pool: MAX
      kernel_size: 3 # pool over a 3x3 region
      stride: 2      # step two pixels (in the bottom blob) between pooling regions
    }
  }