Caffe層系列:Scale Layer
阿新 • • 發佈:2019-01-11
Scale Layer是輸入進行縮放和平移,常常出現在BatchNorm歸一化後
首先我們先看一下 ScaleParameter
message ScaleParameter { // The first axis of bottom[0] (the first input Blob) along which to apply // bottom[1] (the second input Blob). May be negative to index from the end // (e.g., -1 for the last axis). // 根據 bottom[0] 指定 bottom[1] 的形狀 // For example, if bottom[0] is 4D with shape 100x3x40x60, the output // top[0] will have the same shape, and bottom[1] may have any of the // following shapes (for the given value of axis): // (axis == 0 == -4) 100; 100x3; 100x3x40; 100x3x40x60 // (axis == 1 == -3) 3; 3x40; 3x40x60 // (axis == 2 == -2) 40; 40x60 // (axis == 3 == -1) 60 // Furthermore, bottom[1] may have the empty shape (regardless of the value of // "axis") -- a scalar multiplier. // 例如,如果 bottom[0] 的 shape 為 100x3x40x60,則 top[0] 輸出相同的 shape; // bottom[1] 可以包含上面 shapes 中的任一種(對於給定 axis 值). // 而且,bottom[1] 可以是 empty shape 的,沒有任何的 axis 值,只是一個標量的乘子. optional int32 axis = 1 [default = 1]; // (num_axes is ignored unless just one bottom is given and the scale is // a learned parameter of the layer. Otherwise, num_axes is determined by the // number of axes by the second bottom.) // (忽略 num_axes 引數,除非只給定一個 bottom 及 scale 是網路層的一個學習到的引數. // 否則,num_axes 是由第二個 bottom 的數量來決定的.) // The number of axes of the input (bottom[0]) covered by the scale // parameter, or -1 to cover all axes of bottom[0] starting from `axis`. // Set num_axes := 0, to multiply with a zero-axis Blob: a scalar. // bottom[0] 的 num_axes 是由 scale 引數覆蓋的; optional int32 num_axes = 2 [default = 1]; // (filler is ignored unless just one bottom is given and the scale is // a learned parameter of the layer.) // (忽略 filler 引數,除非只給定一個 bottom 及 scale 是網路層的一個學習到的引數. // The initialization for the learned scale parameter. // scale 引數學習的初始化 // Default is the unit (1) initialization, resulting in the ScaleLayer // initially performing the identity operation. // 預設是單位初始化,使 Scale 層初始進行單位操作. optional FillerParameter filler = 3; // Whether to also learn a bias (equivalent to a ScaleLayer+BiasLayer, but // may be more efficient). Initialized with bias_filler (defaults to 0). // 是否學習 bias,等價於 ScaleLayer+BiasLayer,只不過效率更高 // 採用 bias_filler 進行初始化. 預設為 0. optional bool bias_term = 4 [default = false]; optional FillerParameter bias_filler = 5; }
Scale layer 在prototxt裡面的書寫:
layer {
name: "scale_conv1"
type: "Scale"
bottom: "conv1"
top: "conv1"
scale_param {
bias_term: true
}
例如在MobileNet中:
layer { name: "conv6_4/scale" type: "Scale" bottom: "conv6_4/bn" top: "conv6_4/bn" param { lr_mult: 1 decay_mult: 0 } param { lr_mult: 1 decay_mult: 0 } scale_param { bias_term: true } }