Question

如何在Caffe中配置每一个层的结构

Answer 1

如何在Caffe中配置每一个层的结构
最近刚在电脑上装好Caffe，由于神经网络中有不同的层结构，不同类型的层又有不同的参数，所有就根据Caffe官网的说明文档做了一个简单的总结。
1. Vision Layers
1.1 卷积层(Convolution)
类型：CONVOLUTION
例子
layers {
name: "conv1"
type: CONVOLUTION
bottom: "data"
top: "conv1"
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
weight_decay: 0 # weight decay multiplier for the biases
convolution_param {
num_output: 96 # learn 96 filters
kernel_size: 11 # each filter is 11x11
stride: 4 # step 4 pixels between each filter application
weight_filler {
type: "gaussian" # initialize the filters from a Gaussian
std: 0.01 # distribution with stdev 0.01 (default mean: 0)
}
bias_filler {
type: "constant" # initialize the biases to zero (0)
value: 0
}
}
}
blobs_lr: 学习率调整的参数，在上面的例子中设置权重学习率和运行中求解器给出的学习率一样，同时是偏置学习率为权重的两倍。