caffe filler

cnn 网络权值的初始化方式有很多种， caffe 里面实现了7种， 在include/caffe/filler.hpp。caffe::Filler< Dtype > Class Template ReferenceabstractFills a Blob withconstant or randomly-generated data. More...

#include <filler.hpp>

Inheritance diagram for caffe::Filler< Dtype >:

Public Member Functions
	Filler (const FillerParameter ¶m)
virtual void	Fill (Blob< Dtype > *blob)=0

Protected Attributes
FillerParameter	filler_param_

Detailed Description

template<typename Dtype>class caffe::Filler< Dtype >

Fills a Blob withconstant or randomly-generated data.The documentation for this class was generated from the following file:include/caffe/filler.hpp

Filler<Dtype>* GetFiller(const FillerParameter& param) {
const std::string& type = param.type();
if (type == "constant") {
return new ConstantFiller<Dtype>(param);
} else if (type == "gaussian") {
return new GaussianFiller<Dtype>(param);
} else if (type == "positive_unitball") {
return new PositiveUnitballFiller<Dtype>(param);
} else if (type == "uniform") {
return new UniformFiller<Dtype>(param);
} else if (type == "xavier") {
return new XavierFiller<Dtype>(param);
} else if (type == "msra") {
return new MSRAFiller<Dtype>(param);
} else if (type == "bilinear") {
return new BilinearFiller<Dtype>(param);
} else {
CHECK(false) << "Unknown filler name: " << param.type();
}
return (Filler<Dtype>*)(NULL);
}

共有七种方法， 下面分别介绍一下：（1） constant

template <typename Dtype>
class ConstantFiller : public Filler<Dtype> {
public:
explicit ConstantFiller(const FillerParameter& param)
: Filler<Dtype>(param) {}
virtual void Fill(Blob<Dtype>* blob) {
Dtype* data = blob->mutable_cpu_data();
const int count = blob->count();
// get prototxt filler parameters value
const Dtype value = this->filler_param_.value(); //　得到配置文件中 设置的值
CHECK(count);
for (int i = 0; i < count; ++i) {
data[i] = value; //　　将配置文件中的值，直接赋值到 data中。  所以 是常量型，就是配置文件常量
}<pre name="code" class="cpp">

（2） UniformFiller

<pre name="code" class="cpp"><pre name="code" class="cpp">/// @brief Fills a Blob with uniformly distributed values @f$ x\sim U(a, b) @f$.template <typename Dtype>class UniformFiller : public Filler<Dtype> {public:explicit UniformFiller(const FillerParameter& param): Filler<Dtype>(param) {}virtual void Fill(Blob<Dtype>* blob) {CHECK(blob->count());caffe_rng_uniform<Dtype>(blob->count(), Dtype(this->filler_param_.min()), //调用 caffe_rng_uniform ，这个在math_funtion 中实现Dtype(this->filler_param_.max()), blob->mutable_cpu_data());CHECK_EQ(this->filler_param_.sparse(), -1)<< "Sparsity not supported by this Filler.";}};

CHECK_EQ(this->filler_param_.sparse(), -1) << "Sparsity not supported by this Filler."; }};