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7f33ec55b2
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/9350 Re-apply #9270 Breaking this out of #8338 This takes care of the Eigen failure we saw on Mac CUDA builds when BUILD_CAFFE2 and BUILD_ATEN were removed. Fix is to isolate Eigen from headers included by cu files and processed by nvcc. This was worked on with smessmer. Reviewed By: mingzhe09088 Differential Revision: D8794431 fbshipit-source-id: de656334af46c697802073f8e8d9a6aeb9ca65a7
69 lines
1.7 KiB
C++
69 lines
1.7 KiB
C++
#include "caffe2/operators/cube_op.h"
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#include "caffe2/utils/eigen_utils.h"
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#include <algorithm>
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#include <functional>
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#include <string>
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namespace caffe2 {
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template <>
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template <typename T>
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bool CubeGradientFunctor<CPUContext>::Forward(
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const std::vector<int>& dY_dims,
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const std::vector<int>& /* X_dims */,
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const T* dY,
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const T* X,
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T* dX,
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CPUContext* /* context */) const {
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const int size = std::accumulate(
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dY_dims.cbegin(), dY_dims.cend(), 1, std::multiplies<int>());
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EigenVectorMap<T>(dX, size) = ConstEigenVectorArrayMap<T>(dY, size) *
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ConstEigenVectorArrayMap<T>(X, size).square() * T(3);
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return true;
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}
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REGISTER_CPU_OPERATOR(
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Cube,
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UnaryElementwiseOp<NumericTypes, CPUContext, CubeFunctor<CPUContext>>);
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REGISTER_CPU_OPERATOR(
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CubeGradient,
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BinaryElementwiseOp<
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NumericTypes,
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CPUContext,
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CubeGradientFunctor<CPUContext>>);
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OPERATOR_SCHEMA(Cube)
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.NumInputs(1)
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.NumOutputs(1)
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.IdenticalTypeAndShape()
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.Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.")
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.Output(
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0,
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"Y",
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"*(type: Tensor`<float>`)* Output tensor calculated as the cube of the input tensor, element-wise.");
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OPERATOR_SCHEMA(CubeGradient)
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.NumInputs(2)
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.NumOutputs(1)
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.IdenticalTypeAndShape();
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namespace {
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class GetCubeGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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std::vector<OperatorDef> GetGradientDefs() override {
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return SingleGradientDef(
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"CubeGradient",
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"",
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std::vector<std::string>{GO(0), I(0)},
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std::vector<std::string>{GI(0)});
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}
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};
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} // namespace
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REGISTER_GRADIENT(Cube, GetCubeGradient);
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} // namespace caffe2
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