如果您查看/caffe-master/src/caffe/proto/caffe.proto
文件(可以在此处在线找到 ),则会看到以下描述:
// The learning rate decay policy. The currently implemented learning rate
// policies are as follows:
// - fixed: always return base_lr.
// - step: return base_lr * gamma ^ (floor(iter / step))
// - exp: return base_lr * gamma ^ iter
// - inv: return base_lr * (1 + gamma * iter) ^ (- power)
// - multistep: similar to step but it allows non uniform steps defined by
// stepvalue
// - poly: the effective learning rate follows a polynomial decay, to be
// zero by the max_iter. return base_lr (1 - iter/max_iter) ^ (power)
// - sigmoid: the effective learning rate follows a sigmod decay
// return base_lr ( 1/(1 + exp(-gamma * (iter - stepsize))))
//
// where base_lr, max_iter, gamma, step, stepvalue and power are defined
// in the solver parameter protocol buffer, and iter is the current iteration.
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我只是试图找出如何使用Caffe的方法 。为此,我只看了示例文件夹中的不同
.prototxt
文件。有一种我不明白的选择:可能的值似乎是:
"fixed"
"inv"
"step"
"multistep"
"stepearly"
"poly"
有人可以解释一下这些选择吗?