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168 lines
6.6 KiB
168 lines
6.6 KiB
/* 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_sub_op.h"
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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/platform/complex128.h"
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#include "paddle/fluid/platform/complex64.h"
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namespace paddle {
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namespace framework {
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class OpDesc;
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} // namespace framework
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namespace imperative {
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class OpBase;
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} // namespace imperative
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namespace platform {
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class CPUDeviceContext;
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struct CPUPlace;
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} // namespace platform
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} // namespace paddle
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namespace paddle {
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namespace operators {
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template <typename T>
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struct SameDimsElemwiseSub<
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platform::CPUDeviceContext, T,
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typename std::enable_if<std::is_floating_point<T>::value>::type> {
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void operator()(const framework::ExecutionContext &ctx,
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const framework::Tensor *x, const framework::Tensor *y,
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framework::Tensor *z) {
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auto blas = math::GetBlas<platform::CPUDeviceContext, T>(ctx);
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blas.VSUB(x->numel(), x->data<T>(), y->data<T>(), z->data<T>());
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}
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};
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template <typename T>
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struct SameDimsElemwiseSub<
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platform::CPUDeviceContext, T,
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typename std::enable_if<!std::is_floating_point<T>::value>::type> {
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void operator()(const framework::ExecutionContext &ctx,
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const framework::Tensor *x, const framework::Tensor *y,
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framework::Tensor *z) {
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auto eigen_x = framework::EigenVector<T>::Flatten(*x);
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auto eigen_y = framework::EigenVector<T>::Flatten(*y);
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auto eigen_z = framework::EigenVector<T>::Flatten(*z);
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auto &place = *ctx.template device_context<platform::CPUDeviceContext>()
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.eigen_device();
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eigen_z.device(place) = eigen_x - eigen_y;
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}
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};
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class ElementwiseSubOpMaker : public ElementwiseOpMaker {
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protected:
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std::string GetName() const override { return "Sub"; }
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std::string GetEquation() const override { return "Out = X - Y"; }
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void AddInputX() override {
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AddInput("X",
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"(Variable), Tensor or LoDTensor 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 LoDTensor 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 GetOpFuntionality() const override {
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return "Substract two tensors element-wise";
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}
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};
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template <typename T>
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class ElementwiseSubDoubleGradMaker : 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_sub_grad_grad");
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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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}
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};
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} // namespace operators
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} // namespace paddle
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REGISTER_ELEMWISE_GRAD_MAKER(elementwise_sub, Sub);
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REGISTER_ELEMWISE_EXPLICIT_OP_WITHOUT_GRAD(elementwise_sub, Sub);
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(
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elementwise_sub_grad, ops::ElementwiseOpGrad,
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ops::ElementwiseGradOpInplaceInferer, ops::ElementwiseGradNoBufVarsInferer,
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ops::ElementwiseSubDoubleGradMaker<paddle::framework::OpDesc>,
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ops::ElementwiseSubDoubleGradMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(elementwise_sub_grad_grad,
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ops::ElementwiseOpDoubleGradWithoutDXDY,
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ops::ElementwiseDoubleGradOpInplaceInferer,
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ops::ElementwiseDoubleGradNoBufVarsInferer);
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REGISTER_OP_CPU_KERNEL(
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elementwise_sub,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, float>,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, double>,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, int>,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64>,
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ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128>);
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REGISTER_OP_CPU_KERNEL(
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elementwise_sub_grad,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, float>,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, double>,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, int>,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64>,
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ops::ElementwiseSubGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128>);
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REGISTER_OP_CPU_KERNEL(
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elementwise_sub_grad_grad,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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float>,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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double>,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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int>,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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int64_t>,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64>,
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ops::ElementwiseSubDoubleGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128>);
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REGISTER_OP_VERSION(elementwise_sub)
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.AddCheckpoint(
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R"ROC(Register elementwise_sub 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_sub.",
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1.0f));
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