caffe_layer参数

1 . blob
看blob.hpp

Blob(const int num, const int channels, const int height, const int width); 

2 . conv layer参数

  blobs_lr: 1          # learning rate multiplier for the filters  blobs_lr: 2          # learning rate multiplier for the biases  weight_decay: 1      # weight decay multiplier for the filters [Regularization]  weight_decay: 0      # weight decay multiplier for the biases

weight_filler [default type: 'constant' value: 0]：参数的初始化方法bias_filler：偏置的初始化方法

通过卷积后的大小变化
输入：n∗ci∗hi∗wi
输出：n∗co∗ho∗wo，

其中ho=(hi+2∗P−K)S+1，
wo通过同样的方法计算
P: pad, K: kernel size, S: stride

1. inner_product_param
   num_output: 1000