wehub-resource-sync
233 lines
8.7 KiB
C++
233 lines
8.7 KiB
C++
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/fluid/operators/elementwise/elementwise_mul_op.h"
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#include <memory>
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#include <string>
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#include "paddle/fluid/operators/elementwise/elementwise_op.h"
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#include "paddle/fluid/prim/api/composite_backward/composite_backward_api.h"
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#include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
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#include "paddle/fluid/prim/utils/static/desc_tensor.h"
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#include "paddle/phi/common/complex.h"
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namespace paddle {
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namespace operators {
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class ElementwiseMulOpMaker : public ElementwiseOpMaker {
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protected:
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std::string GetName() const override { return "Mul"; }
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std::string GetEquation() const override { return "Out = X \\\\odot Y"; }
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void AddInputX() override {
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AddInput("X",
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"(Variable), Tensor or DenseTensor of any dimensions. Its dtype "
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"should be int32, int64, float32, float64.");
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}
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void AddInputY() override {
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AddInput("Y",
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"(Variable), Tensor or DenseTensor of any dimensions. Its dtype "
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"should be int32, int64, float32, float64.");
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}
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std::string GetOpFunctionality() const override {
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return "Multiply two tensors element-wise";
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}
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};
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template <typename T>
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class ElementwiseMulOpGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetType("elementwise_mul_grad");
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op->SetInput("X", this->Input("X"));
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op->SetInput("Y", this->Input("Y"));
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op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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op->SetAttrMap(this->Attrs());
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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op->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y"));
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}
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};
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class ElementwiseMulCompositeGradOpMaker
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: public prim::CompositeGradOpMakerBase {
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using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
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public:
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void Apply() override {
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auto x = this->GetSingleForwardInput("X");
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auto y = this->GetSingleForwardInput("Y");
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auto out_grad = this->GetSingleOutputGrad("Out");
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auto x_grad = this->GetSingleInputGrad("X");
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auto x_grad_p = this->GetOutputPtr(&x_grad);
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auto x_grad_name = this->GetOutputName(x_grad);
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auto y_grad = this->GetSingleInputGrad("Y");
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auto y_grad_p = this->GetOutputPtr(&y_grad);
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auto y_grad_name = this->GetOutputName(y_grad);
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int axis = static_cast<int>(this->Attr<int>("axis"));
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PADDLE_ENFORCE_EQ(
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axis,
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-1,
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common::errors::InvalidArgument(
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"We only support axis = -1 in composite mul_grad but we got: %d.",
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axis));
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prim::multiply_grad<prim::DescTensor>(
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x, y, out_grad, axis, x_grad_p, y_grad_p);
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VLOG(6) << "Running mul_grad composite func";
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this->RecoverOutputName(x_grad, x_grad_name);
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this->RecoverOutputName(y_grad, y_grad_name);
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}
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};
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template <typename T>
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class ElementwiseMulDoubleGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetType("elementwise_mul_grad_grad");
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op->SetInput("X", this->Input("X"));
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op->SetInput("Y", this->Input("Y"));
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op->SetInput("DOut", this->Input(framework::GradVarName("Out")));
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op->SetInput("DDX", this->OutputGrad(framework::GradVarName("X")));
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op->SetInput("DDY", this->OutputGrad(framework::GradVarName("Y")));
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op->SetAttrMap(this->Attrs());
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op->SetOutput("DDOut", this->InputGrad(framework::GradVarName("Out")));
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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op->SetOutput(framework::GradVarName("Y"), this->InputGrad("Y"));
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}
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};
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class ElementwiseMulCompositeDoubleGradOpMaker
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: public prim::CompositeGradOpMakerBase {
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using prim::CompositeGradOpMakerBase::CompositeGradOpMakerBase;
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public:
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void Apply() override {
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// get input
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paddle::Tensor x = this->GetSingleForwardInput("X");
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paddle::Tensor y = this->GetSingleForwardInput("Y");
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paddle::Tensor out_grad = this->GetSingleOutputGrad("Out");
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paddle::optional<paddle::Tensor> ddx =
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this->GetOptionalSingleOutputGrad(framework::GradVarName("X"));
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paddle::optional<paddle::Tensor> ddy =
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this->GetOptionalSingleOutputGrad(framework::GradVarName("Y"));
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// get attr
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int axis = static_cast<int>(this->Attr<int>("axis"));
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PADDLE_ENFORCE_EQ(axis,
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-1,
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common::errors::InvalidArgument(
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"We only support axis = -1 in composite "
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"add_double_grad but we got: %d",
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axis));
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// get output
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paddle::Tensor x_grad_t = this->GetSingleInputGrad("X");
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paddle::Tensor y_grad_t = this->GetSingleInputGrad("Y");
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paddle::Tensor grad_out_grad_t =
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this->GetSingleInputGrad(framework::GradVarName("Out"));
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// get output ptr
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paddle::Tensor* x_grad = this->GetOutputPtr(&x_grad_t);
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paddle::Tensor* y_grad = this->GetOutputPtr(&y_grad_t);
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paddle::Tensor* grad_out_grad = this->GetOutputPtr(&grad_out_grad_t);
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// get output original name
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std::string x_grad_name = this->GetOutputName(x_grad_t);
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std::string y_grad_name = this->GetOutputName(y_grad_t);
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std::string grad_out_grad_name = this->GetOutputName(grad_out_grad_t);
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VLOG(6) << "Running multiply_double_grad composite func";
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prim::multiply_double_grad<prim::DescTensor>(
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x, y, out_grad, ddx, ddy, axis, x_grad, y_grad, grad_out_grad);
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// recover output name
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this->RecoverOutputName(x_grad_t, x_grad_name);
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this->RecoverOutputName(y_grad_t, y_grad_name);
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this->RecoverOutputName(grad_out_grad_t, grad_out_grad_name);
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}
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};
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template <typename T>
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class ElementwiseMulTripleGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> op) const override {
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op->SetType("elementwise_mul_triple_grad");
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// get input from double grad
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op->SetInput("X", this->Input("X"));
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op->SetInput("Y", this->Input("Y"));
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op->SetInput("DOut", this->Input("DOut"));
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op->SetInput("DDX", this->Input("DDX"));
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op->SetInput("DDY", this->Input("DDY"));
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op->SetInput("D_DX", this->OutputGrad(framework::GradVarName("X")));
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op->SetInput("D_DY", this->OutputGrad(framework::GradVarName("Y")));
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op->SetInput("D_DDOut", this->OutputGrad("DDOut"));
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op->SetAttrMap(this->Attrs());
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// set outputs
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op->SetOutput("D_X", this->InputGrad("X"));
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op->SetOutput("D_Y", this->InputGrad("Y"));
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op->SetOutput("D_DOut", this->InputGrad("DOut"));
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op->SetOutput("D_DDX", this->InputGrad("DDX"));
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op->SetOutput("D_DDY", this->InputGrad("DDY"));
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(elementwise_mul,
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ops::ElementwiseMulOp,
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ops::ElementwiseMulOpMaker,
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ops::ElementwiseOpInferVarType,
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ops::ElementwiseMulOpGradMaker<paddle::framework::OpDesc>,
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ops::ElementwiseMulOpGradMaker<paddle::imperative::OpBase>,
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ops::ElementwiseMulCompositeGradOpMaker);
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REGISTER_OPERATOR(
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elementwise_mul_grad,
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ops::ElementwiseOpGrad,
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ops::ElementwiseMulDoubleGradMaker<paddle::framework::OpDesc>,
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ops::ElementwiseMulDoubleGradMaker<paddle::imperative::OpBase>,
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ops::ElementwiseMulCompositeDoubleGradOpMaker);
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REGISTER_OPERATOR(
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elementwise_mul_grad_grad,
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ops::ElementwiseOpDoubleGrad,
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ops::ElementwiseDoubleGradOpInplaceInferer,
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ops::ElementwiseMulTripleGradMaker<paddle::framework::OpDesc>,
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ops::ElementwiseMulTripleGradMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(elementwise_mul_triple_grad, ops::ElementwiseOpTripleGrad);
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REGISTER_OP_VERSION(elementwise_mul)
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.AddCheckpoint(
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R"ROC(Register elementwise_mul for adding the attribute of Scale_y)ROC",
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paddle::framework::compatible::OpVersionDesc().NewAttr(
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"Scale_y",
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"In order to support the function of scaling the input Y when "
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"using the operator of elementwise_mul.",
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1.0f));
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