caffe卷积层参数

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axis

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// The axis to interpret as "channels" when performing convolution.
// Preceding dimensions are treated as independent inputs;
// succeeding dimensions are treated as "spatial".
// With (N, C, H, W) inputs, and axis == 1 (the default), we perform
// N independent 2D convolutions, sliding C-channel (or (C/g)-channels, for
// groups g>1) filters across the spatial axes (H, W) of the input.
// With (N, C, D, H, W) inputs, and axis == 1, we perform
// N independent 3D convolutions, sliding (C/g)-channels
// filters across the spatial axes (D, H, W) of the input.
optional int32 axis = 16 [default = 1];

说白了，就是将哪个轴作为通道，默认为1，默认为1的话就是第二个轴为通道[0,1,2,3]。

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// Preceding dimensions are treated as independent inputs;`
// succeeding dimensions are treated as "spatial".

前边的轴作为独立输入，后边的轴作为空间坐标轴。

另外一个函数：

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inline int CanonicalAxisIndex(int axis_index) const {
    CHECK_GE(axis_index, -num_axes())
        << "axis " << axis_index << " out of range for " << num_axes()
        << "-D Blob with shape " << shape_string();
    CHECK_LT(axis_index, num_axes())
        << "axis " << axis_index << " out of range for " << num_axes()
        << "-D Blob with shape " << shape_string();
    if (axis_index < 0) {
      return axis_index + num_axes();
    }
    return axis_index;
  }

返回Canonical的index，字面意思是权威。实际如下：

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input:  0,1,2,3
        -4,-3,-2,-1
output: 0,1,2,3