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#include "caffe2/operators/cube_op.h"
#include "caffe2/utils/eigen_utils.h"
#include <algorithm>
#include <functional>
#include <string>
namespace caffe2 {
template <>
template <typename T>
bool CubeGradientFunctor<CPUContext>::Forward(
const std::vector<int>& dY_dims,
const std::vector<int>& /* X_dims */,
const T* dY,
const T* X,
T* dX,
CPUContext* /* context */) const {
const int size = std::accumulate(
dY_dims.cbegin(), dY_dims.cend(), 1, std::multiplies<int>());
EigenVectorMap<T>(dX, size) = ConstEigenVectorArrayMap<T>(dY, size) *
ConstEigenVectorArrayMap<T>(X, size).square() * T(3);
return true;
}
REGISTER_CPU_OPERATOR(
Cube,
UnaryElementwiseOp<NumericTypes, CPUContext, CubeFunctor<CPUContext>>);
REGISTER_CPU_OPERATOR(
CubeGradient,
BinaryElementwiseOp<
NumericTypes,
CPUContext,
CubeGradientFunctor<CPUContext>>);
OPERATOR_SCHEMA(Cube)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShape()
.Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.")
.Output(
0,
"Y",
"*(type: Tensor`<float>`)* Output tensor calculated as the cube of the input tensor, element-wise.");
OPERATOR_SCHEMA(CubeGradient)
.NumInputs(2)
.NumOutputs(1)
.IdenticalTypeAndShape();
namespace {
class GetCubeGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"CubeGradient",
"",
std::vector<std::string>{GO(0), I(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Cube, GetCubeGradient);
} // namespace caffe2
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