| #include "caffe2/operators/asin_op.h" |
| #include "caffe2/utils/eigen_utils.h" |
| |
| #include <algorithm> |
| #include <functional> |
| |
| namespace caffe2 { |
| |
| template <> |
| template <typename T> |
| bool AsinGradientFunctor<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( |
| // NOLINTNEXTLINE(modernize-use-transparent-functors) |
| 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) = dY_arr * (T(1) - X_arr.square()).rsqrt(); |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR( |
| Asin, |
| UnaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| AsinFunctor<CPUContext>>); |
| REGISTER_CPU_OPERATOR( |
| AsinGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| AsinGradientFunctor<CPUContext>>); |
| |
| OPERATOR_SCHEMA(Asin) |
| .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(AsinGradient) |
| .NumInputs(2) |
| .NumOutputs(1) |
| .IdenticalTypeAndShape(); |
| |
| namespace { |
| |
| class GetAsinGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| std::vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "AsinGradient", |
| "", |
| std::vector<std::string>{I(0), GO(0)}, |
| std::vector<std::string>{GI(0)}); |
| } |
| }; |
| |
| } // namespace |
| |
| REGISTER_GRADIENT(Asin, GetAsinGradient); |
| |
| } // namespace caffe2 |