| #include "caffe2/operators/elu_op.h" |
| |
| #include "caffe2/utils/math.h" |
| |
| namespace caffe2 { |
| |
| template <> |
| bool EluOp<float, CPUContext>::RunOnDevice() { |
| auto& X = Input(0); |
| auto* Y = Output(0); |
| // Otherwise inplace gradient and Elu dosen't make sense. |
| CAFFE_ENFORCE_GE(alpha_, 0); |
| Y->ResizeLike(X); |
| const auto* Xdata = X.template data<float>(); |
| auto* Ydata = Y->template mutable_data<float>(); |
| ConstEigenVectorArrayMap<float> Xvec(Xdata, X.size()); |
| EigenVectorArrayMap<float> Yvec(Ydata, Y->size()); |
| Yvec = Xvec.cwiseMax(0.f) + (alpha_ * (Xvec.exp() - 1.0f)).cwiseMin(0.f); |
| return true; |
| } |
| |
| template <> |
| bool EluGradientOp<float, CPUContext>::RunOnDevice() { |
| auto& Y = Input(0); |
| auto& dY = Input(1); |
| auto* dX = Output(0); |
| DCHECK_GT(Y.size(), 0); |
| DCHECK_EQ(dY.size(), Y.size()); |
| dX->ResizeLike(Y); |
| |
| const float* Ydata = Y.data<float>(); |
| const float* dYdata = dY.data<float>(); |
| float* dXdata = dX->mutable_data<float>(); |
| ConstEigenVectorArrayMap<float> Yvec(Ydata, Y.size()); |
| ConstEigenVectorArrayMap<float> dYvec(dYdata, dY.size()); |
| EigenVectorArrayMap<float> dXvec(dXdata, dX->size()); |
| dXvec = (Yvec > 0).select(dYvec, dYvec * (Yvec + alpha_)); |
| return true; |
| } |
| |
| REGISTER_CPU_OPERATOR(Elu, EluOp<float, CPUContext>); |
| REGISTER_CPU_OPERATOR(EluGradient, EluGradientOp<float, CPUContext>); |
| |
| // Input: X, output: Y |
| OPERATOR_SCHEMA(Elu) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .AllowInplace({{0, 0}}) |
| .IdenticalTypeAndShape() |
| .SetDoc(R"DOC( |
| |
| Elu takes one input data (Tensor<T>) and produces one output data |
| (Tensor<T>) where the function `f(x) = alpha * (exp(x) - 1.) for x < |
| 0`, `f(x) = x for x >= 0`., is applied to the tensor elementwise. |
| |
| )DOC") |
| .Input(0, "X", "1D input tensor") |
| .Output(0, "Y", "1D input tensor"); |
| |
| // Input: Y, dY, output: dX |
| OPERATOR_SCHEMA(EluGradient) |
| .NumInputs(2) |
| .NumOutputs(1) |
| .AllowInplace({{1, 0}}) |
| .SetDoc(R"DOC( |
| EluGradient takes both Y and dY and uses this to update dX according to the |
| chain rule and derivatives of the rectified linear function. |
| )DOC"); |
| |
| class GetEluGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| def_.type() + "Gradient", |
| "", |
| vector<string>{O(0), GO(0)}, |
| vector<string>{GI(0)}); |
| } |
| }; |
| REGISTER_GRADIENT(Elu, GetEluGradient); |
| |
| } // namespace caffe2 |