| #include "caffe2/operators/sin_op.h" |
| #include "caffe2/utils/eigen_utils.h" |
| |
| #include <algorithm> |
| #include <functional> |
| |
| namespace caffe2 { |
| |
| template <> |
| template <typename T> |
| bool SinGradientFunctor<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 * X_arr.cos(); |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR( |
| Sin, |
| UnaryElementwiseOp<TensorTypes<float>, CPUContext, SinFunctor<CPUContext>>); |
| REGISTER_CPU_OPERATOR( |
| SinGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| SinGradientFunctor<CPUContext>>); |
| |
| OPERATOR_SCHEMA(Sin) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .IdenticalTypeAndShape() |
| .SetDoc(R"DOC( |
| Calculates the sine of the given input tensor, element-wise. |
| |
| Github Links: |
| |
| - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/sin_op.cc |
| |
| |
| <details> |
| |
| <summary> <b>Example</b> </summary> |
| |
| **Code** |
| |
| ``` |
| |
| workspace.ResetWorkspace() |
| |
| op = core.CreateOperator( |
| "Sin", |
| ["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: [0.8466114 0.1803606 0.5601509 0.04959291 0.64770824] |
| Y: [0.74903965 0.17938434 0.5313141 0.04957259 0.60336035] |
| |
| ``` |
| |
| </details> |
| |
| )DOC") |
| .Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.") |
| .Output( |
| 0, |
| "Y", |
| "*(type: Tensor`<float>`)* Output tensor calculated as the sine of the input tensor, element-wise."); |
| |
| OPERATOR_SCHEMA(SinGradient).NumInputs(2).NumOutputs(1).IdenticalTypeAndShape(); |
| |
| namespace { |
| |
| class GetSinGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| std::vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "SinGradient", |
| "", |
| std::vector<std::string>{I(0), GO(0)}, |
| std::vector<std::string>{GI(0)}); |
| } |
| }; |
| |
| } // namespace |
| |
| REGISTER_GRADIENT(Sin, GetSinGradient); |
| |
| } // namespace caffe2 |