blob: 2aa52646296e7cc2d88e7e1ebcca402869e75989 [file] [log] [blame]
#include "caffe2/operators/sigmoid_op.h"
#include "caffe2/utils/eigen_utils.h"
#include <algorithm>
#include <functional>
#include <string>
#include <vector>
namespace caffe2 {
template <>
template <typename T>
bool SigmoidGradientFunctor<CPUContext>::Forward(
const std::vector<int>& Y_dims,
const std::vector<int>& /* dY_dims */,
const T* Y,
const T* dY,
T* dX,
CPUContext* /* context */) const {
const int size = std::accumulate(
// NOLINTNEXTLINE(modernize-use-transparent-functors)
Y_dims.cbegin(), Y_dims.cend(), 1, std::multiplies<int>());
ConstEigenVectorArrayMap<T> dY_arr(dY, size);
ConstEigenVectorArrayMap<T> Y_arr(Y, size);
EigenVectorArrayMap<T>(dX, size) = dY_arr * Y_arr * (T(1) - Y_arr);
return true;
}
REGISTER_CPU_OPERATOR(
SigmoidGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
SigmoidGradientFunctor<CPUContext>>);
namespace {
class GetSigmoidGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"SigmoidGradient",
"",
std::vector<std::string>{O(0), GO(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Sigmoid, GetSigmoidGradient);
} // namespace caffe2