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#include "caffe2/operators/erf_op.h"
#include "caffe2/utils/eigen_utils.h"
#include <algorithm>
#include <functional>
namespace caffe2 {
template <>
template <typename T>
bool ErfGradientFunctor<CPUContext>::Forward(
const std::vector<int>& X_dims,
const std::vector<int>& /* dY_dims */,
const T* X,
const T* dY,
T* dX,
CPUContext* /* context */) const {
const int size = std::accumulate(
X_dims.cbegin(), X_dims.cend(), 1, std::multiplies<int>());
ConstEigenVectorArrayMap<T> dY_arr(dY, size);
ConstEigenVectorArrayMap<T> X_arr(X, size);
EigenVectorMap<T>(dX, size) = T(2) / sqrtf(PI) * (-X_arr.square()).exp() * dY_arr;
return true;
}
REGISTER_CPU_OPERATOR(
Erf,
UnaryElementwiseOp<
TensorTypes<float>,
CPUContext,
ErfFunctor<CPUContext>>);
REGISTER_CPU_OPERATOR(
ErfGradient,
BinaryElementwiseOp<
TensorTypes<float>,
CPUContext,
ErfGradientFunctor<CPUContext>>);
OPERATOR_SCHEMA(Erf)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShape()
.SetDoc(R"DOC(
Calculates the arcsine of the given input tensor, element-wise.
)DOC")
.Input(0, "input", "Input tensor")
.Output(
0,
"output",
"The arcsine of the input tensor computed element-wise");
OPERATOR_SCHEMA(ErfGradient)
.NumInputs(2)
.NumOutputs(1)
.IdenticalTypeAndShape();
namespace {
class GetErfGradient : public GradientMakerBase {
using GradientMakerBase::GradientMakerBase;
std::vector<OperatorDef> GetGradientDefs() override {
return SingleGradientDef(
"ErfGradient",
"",
std::vector<std::string>{I(0), GO(0)},
std::vector<std::string>{GI(0)});
}
};
} // namespace
REGISTER_GRADIENT(Erf, GetErfGradient);
} // namespace caffe2
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