| #include "caffe2/operators/tan_op.h" |
| |
| #include "caffe2/utils/eigen_utils.h" |
| |
| #include <algorithm> |
| #include <functional> |
| |
| namespace caffe2 { |
| |
| template <> |
| template <typename T> |
| bool TanGradientFunctor<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().square(); |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR( |
| Tan, |
| UnaryElementwiseOp<TensorTypes<float>, CPUContext, TanFunctor<CPUContext>>); |
| REGISTER_CPU_OPERATOR( |
| TanGradient, |
| BinaryElementwiseOp< |
| TensorTypes<float>, |
| CPUContext, |
| TanGradientFunctor<CPUContext>>); |
| |
| OPERATOR_SCHEMA(Tan) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .IdenticalTypeAndShape() |
| .SetDoc(R"DOC( |
| Calculates the tangent of the given input tensor, element-wise. |
| )DOC") |
| .Input(0, "input", "Input tensor") |
| .Output( |
| 0, |
| "output", |
| "The tangent of the input tensor computed element-wise"); |
| |
| OPERATOR_SCHEMA(TanGradient).NumInputs(2).NumOutputs(1).IdenticalTypeAndShape(); |
| |
| namespace { |
| |
| class GetTanGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| std::vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "TanGradient", |
| "", |
| std::vector<std::string>{I(0), GO(0)}, |
| std::vector<std::string>{GI(0)}); |
| } |
| }; |
| |
| } // namespace |
| |
| REGISTER_GRADIENT(Tan, GetTanGradient); |
| |
| } // namespace caffe2 |