提交 af5d954b 编写于 作者: Y Yu Yang

Clean BatchNorm Code.

上级 fefb3c13
......@@ -59,24 +59,14 @@ void BatchNormalizationLayer::calMeanAndStd(const MatrixPtr& mat) {
void BatchNormalizationLayer::calMovingMeanAndVar() {
// calculating and saving moving mean and variance
MatrixPtr movingMean = movingMean_->getW();
MatrixPtr movingVar = movingVar_->getW();
if (!useGpu_ && FLAGS_trainer_count > 1) {
auto mvMean = std::dynamic_pointer_cast<SharedCpuMatrix>(movingMean);
auto mvVar = std::dynamic_pointer_cast<SharedCpuMatrix>(movingVar);
CHECK(mvMean && mvVar);
mvMean->add(*savedMean_, movingAvgFraction_, 1.0 - movingAvgFraction_);
mvVar->add(*savedInvVar_, movingAvgFraction_, 1.0 - movingAvgFraction_);
} else {
// movingMean = movingMean * movingAvgFraction_
// + savedMean_ * (1 - movingAvgFraction_)
movingMean->add(*savedMean_, movingAvgFraction_, 1.0 - movingAvgFraction_);
// movingVar = movingVar * movingAvgFraction_
// + savedInvVar_ * (1 - movingAvgFraction_)
movingVar->add(*savedInvVar_, movingAvgFraction_, 1.0 - movingAvgFraction_);
}
auto& movingMean = movingMean_->getW();
auto& movingVar = movingVar_->getW();
// movingMean = movingMean * movingAvgFraction_
// + savedMean_ * (1 - movingAvgFraction_)
movingMean->add(*savedMean_, movingAvgFraction_, 1.0 - movingAvgFraction_);
// movingVar = movingVar * movingAvgFraction_
// + savedInvVar_ * (1 - movingAvgFraction_)
movingVar->add(*savedInvVar_, movingAvgFraction_, 1.0 - movingAvgFraction_);
}
void BatchNormalizationLayer::setMeanAndStd() {
......
......@@ -1973,8 +1973,8 @@ public:
public:
virtual void mul(CpuSparseMatrix* a, CpuMatrix* b, real scaleAB, real scaleT);
void add(Matrix& b, real p1, real p2);
void add(real p1, real p2);
virtual void add(Matrix& b, real p1, real p2);
virtual void add(real p1, real p2);
private:
using Matrix::mul;
......
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