Pooling

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

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:

message PoolingParameter {
  enum PoolMethod {
    MAX = 0;
    AVE = 1;
    STOCHASTIC = 2;
  }
  optional PoolMethod pool = 1 [default = MAX]; // The pooling method
  // Pad, kernel size, and stride are all given as a single value for equal
  // dimensions in height and width or as Y, X pairs.
  optional uint32 pad = 4 [default = 0]; // The padding size (equal in Y, X)
  optional uint32 pad_h = 9 [default = 0]; // The padding height
  optional uint32 pad_w = 10 [default = 0]; // The padding width
  optional uint32 kernel_size = 2; // The kernel size (square)
  optional uint32 kernel_h = 5; // The kernel height
  optional uint32 kernel_w = 6; // The kernel width
  optional uint32 stride = 3 [default = 1]; // The stride (equal in Y, X)
  optional uint32 stride_h = 7; // The stride height
  optional uint32 stride_w = 8; // The stride width
  enum Engine {
    DEFAULT = 0;
    CAFFE = 1;
    CUDNN = 2;
  }
  optional Engine engine = 11 [default = DEFAULT];
  // If global_pooling then it will pool over the size of the bottom by doing
  // kernel_h = bottom->height and kernel_w = bottom->width
  optional bool global_pooling = 12 [default = false];
}

Sample

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
  }
}