/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include #include "paddle/fluid/operators/elementwise/elementwise_op.h" #include "paddle/fluid/prim/api/composite_backward/composite_backward_api.h" #include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h" #include "paddle/fluid/prim/utils/static/desc_tensor.h" namespace paddle { namespace framework { class OpDesc; } // namespace framework namespace imperative { class OpBase; } // namespace imperative } // namespace paddle namespace paddle { namespace operators { template class ElementwisePowOpGradMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr op) const override { op->SetType("elementwise_pow_grad"); op->SetInput("X", this->Input("X")); op->SetInput("Y", this->Input("Y")); op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); op->SetAttrMap(this->Attrs()); op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); op->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y")); } }; class ElementwisePowCompositeGradOpMaker : public prim::CompositeGradOpMakerBase { using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase; public: void Apply() override { paddle::Tensor x = this->GetSingleForwardInput("X"); paddle::Tensor y = this->GetSingleForwardInput("Y"); paddle::Tensor out_grad = this->GetSingleOutputGrad("Out"); paddle::Tensor dx = this->GetSingleInputGrad("X"); auto dx_ptr = this->GetOutputPtr(&dx); std::string dx_name = this->GetOutputName(dx); paddle::Tensor dy = this->GetSingleInputGrad("Y"); auto dy_ptr = this->GetOutputPtr(&dy); std::string dy_name = this->GetOutputName(dy); int axis = static_cast(this->Attr("axis")); PADDLE_ENFORCE_EQ( axis, -1, phi::errors::InvalidArgument( "We only support axis = -1 in composite pow but we got: ", axis)); VLOG(6) << "Runing pow_grad composite func"; prim::elementwise_pow_grad( x, y, out_grad, axis, dx_ptr, dy_ptr); this->RecoverOutputName(dx, dx_name); this->RecoverOutputName(dy, dy_name); } }; class ElementwisePowOpMaker : public ElementwiseOpMaker { protected: std::string GetName() const override { return "Pow"; } std::string GetEquation() const override { return "Out = X ^ Y"; } void AddInputX() override { AddInput("X", "(Variable), The Base."); } void AddInputY() override { AddInput("Y", "(Variable), The exponents."); } std::string GetOpFuntionality() const override { return "First tensor elements raised to powers from the second tensor, " "element-wise."; } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(elementwise_pow, ops::ElementwiseOp, ops::ElementwisePowOpMaker, ops::ElementwiseOpInferVarType, ops::ElementwisePowOpGradMaker, ops::ElementwisePowOpGradMaker); REGISTER_OPERATOR(elementwise_pow_grad, ops::ElementwiseOpGrad, ops::ElementwisePowCompositeGradOpMaker); REGISTER_OP_VERSION(elementwise_pow) .AddCheckpoint( R"ROC(Register elementwise_pow for adding the attribute of Scale_y)ROC", paddle::framework::compatible::OpVersionDesc().NewAttr( "Scale_y", "In order to support the function of scaling the input Y when " "using the operator of elementwise_pow.", 1.0f));