| #include "caffe2/operators/sinh_op.h" |
| |
| #include <algorithm> |
| #include <functional> |
| |
| namespace caffe2 { |
| |
| template <> |
| template <typename T> |
| bool SinhGradientFunctor<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) |
| 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 * (X_arr.exp() + (-X_arr).exp()) / 2; |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR( |
| Sinh, |
| UnaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| SinhFunctor<CPUContext>>); |
| REGISTER_CPU_OPERATOR( |
| SinhGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| SinhGradientFunctor<CPUContext>>); |
| |
| OPERATOR_SCHEMA(Sinh) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .IdenticalTypeAndShape() |
| .SetDoc(R"DOC( |
| Calculates the hyperbolic sine of the given input tensor, element-wise. |
| |
| Github Links: |
| |
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/sinh_op.cc |
| |
| |
| <details> |
| |
| <summary> <b>Example</b> </summary> |
| |
| **Code** |
| |
| ``` |
| |
| workspace.ResetWorkspace() |
| |
| op = core.CreateOperator( |
| "Sinh", |
| ["X"], |
| ["Y"] |
| ) |
| |
| workspace.FeedBlob("X", np.random.rand(5).astype(np.float32)) |
| print("X:", workspace.FetchBlob("X")) |
| workspace.RunOperatorOnce(op) |
| print("Y:", workspace.FetchBlob("Y")) |
| |
| ``` |
| |
| **Result** |
| |
| ``` |
| |
| X: [0.98907769 0.52907848 0.03216429 0.94983935 0.47881418] |
| Y: [1.15841695 0.5541099 0.03216984 1.09924557 0.49732079] |
| |
| ``` |
| |
| </details> |
| |
| )DOC") |
| .Input(0, "input", "Input tensor") |
| .Output( |
| 0, |
| "output", |
| "The hyperbolic sine values of the input tensor, computed " |
| "element-wise") |
| .InheritOnnxSchema(); |
| |
| OPERATOR_SCHEMA(SinhGradient) |
| .NumInputs(2) |
| .NumOutputs(1) |
| .IdenticalTypeAndShapeOfInput(0); |
| |
| namespace { |
| |
| class GetSinhGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| std::vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "SinhGradient", |
| "", |
| std::vector<std::string>{GO(0), I(0)}, |
| std::vector<std::string>{GI(0)}); |
| } |
| }; |
| |
| } // namespace |
| |
| REGISTER_GRADIENT(Sinh, GetSinhGradient); |
| |
| } // namespace caffe2 |