| #include "caffe2/operators/cbrt_op.h" |
| #include "caffe2/utils/eigen_utils.h" |
| |
| #include <algorithm> |
| #include <functional> |
| #include <string> |
| |
| namespace caffe2 { |
| |
| template <> |
| template <typename T> |
| bool CbrtGradientFunctor<CPUContext>::Forward( |
| const std::vector<int>& dY_dims, |
| const std::vector<int>& /* Y_dims */, |
| const T* dY, |
| const T* Y, |
| 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>(Y, size).square() / T(3); |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR( |
| Cbrt, |
| UnaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| CbrtFunctor<CPUContext>>); |
| REGISTER_CPU_OPERATOR( |
| CbrtGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| CbrtGradientFunctor<CPUContext>>); |
| |
| OPERATOR_SCHEMA(Cbrt) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .AllowInplace({{0, 0}}) |
| .IdenticalTypeAndShape() |
| .Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.") |
| .Output( |
| 0, |
| "Y", |
| "*(type: Tensor`<float>`)* Output tensor calculated as the cbrt of the input tensor, element-wise."); |
| |
| OPERATOR_SCHEMA(CbrtGradient) |
| .NumInputs(2) |
| .NumOutputs(1) |
| .AllowInplace({{0, 0}}) |
| .IdenticalTypeAndShapeOfInput(0); |
| |
| namespace { |
| |
| class GetCbrtGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| std::vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "CbrtGradient", |
| "", |
| std::vector<std::string>{GO(0), O(0)}, |
| std::vector<std::string>{GI(0)}); |
| } |
| }; |
| |
| } // namespace |
| |
| REGISTER_GRADIENT(Cbrt, GetCbrtGradient); |
| |
| } // namespace caffe2 |