[Caffe]: 关于Scale layer

最新推荐文章于 2025-09-10 20:42:23 发布

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本文详细介绍了Caffe框架中ScaleLayer的功能与配置参数。ScaleLayer能够实现两个输入矩阵的按元素相乘，并可通过广播机制调整输入大小。此外，还支持学习偏差项，提升网络表达能力。

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Scale layer

caffe源码中给出了scale层的作用，如下：

/**
 * @brief Computes the elementwise product of two input Blobs, with the shape of
 *        the latter Blob "broadcast" to match the shape of the former.
 *        Equivalent to tiling the latter Blob, then computing the elementwise
 *        product. Note: for efficiency and convenience, this layer can
 *        additionally perform a "broadcast" sum too when `bias_term: true`
 *        is set.
 *
 * The latter, scale input may be omitted, in which case it's learned as
 * parameter of the layer (as is the bias, if it is included).
 */

即，按元素计算连个输入的乘积。该过程以广播第二个输入来匹配第一个输入矩阵的大小。
也就是通过平铺第二个输入矩阵来计算按元素乘积（点乘）。

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).
  //
  // 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.
  optional int32 axis = 1 [default = 1]; //指定第二个输入的形状大小，默认为axis = 1，即如例子中所示可能有(3; 3x40; 3x40x60;)三种形状。

  // (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.) 除了只有一个输入bottom[0]外,num_axes都将被忽略.
  // 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. //num_axes=-1，覆盖第一个输入的所有轴(维度)；num_axes=0, 第一个输入与一个标量做点乘.
  optional int32 num_axes = 2 [default = 1]; //第一个输入被覆盖轴的数量，默认为1.

  // (filler is ignored unless just one bottom is given and the scale is
  // a learned parameter of the layer.) 除了只有一个输入bottom[0]外,filler都将被忽略.
  // The initialization for the learned scale parameter. 学习的scale参数的初始化.
  // Default is the unit (1) initialization, resulting in the ScaleLayer
  // initially performing the identity operation. 默认为单位初始化.
  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).
  optional bool bias_term = 4 [default = false]; //是否同时学习偏差bias，默认为否.
  optional FillerParameter bias_filler = 5; //带有偏差填充的初始化，偏差bias_filler默认为0
}