mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
a9b0a921d5
Summary: As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH` All changes but the ones to `.clang-tidy` are generated using following script: ``` for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008 Reviewed By: driazati, r-barnes Differential Revision: D29838584 Pulled By: malfet fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
70 lines
1.7 KiB
C++
70 lines
1.7 KiB
C++
#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(
|
|
// NOLINTNEXTLINE(modernize-use-transparent-functors)
|
|
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
|