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107 lines
4.0 KiB
107 lines
4.0 KiB
/* Copyright (c) 2020 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/imag_op.h"
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namespace paddle {
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namespace operators {
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class ImagOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Imag");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Imag");
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auto x_dims = ctx->GetInputDim("X");
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ctx->SetOutputDim("Out", x_dims);
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ctx->ShareLoD("X", "Out");
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}
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};
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class ImagOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "(Tensor), The input tensor of imag op.");
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AddOutput("Out", "(Tensor), The output tensor of imag op.");
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AddComment(R"DOC(
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Imag Operator.
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This operator is used to get a new tensor containing imaginary values
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from a tensor with complex data type.
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)DOC");
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}
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};
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class ImagGradOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
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"Out@Grad", "ImagGrad");
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OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")), "Output",
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"X@Grad", "ImagGrad");
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auto dout_dims = ctx->GetInputDim(framework::GradVarName("Out"));
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ctx->SetOutputDim(framework::GradVarName("X"), dout_dims);
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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auto dtype = OperatorWithKernel::IndicateVarDataType(
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ctx, framework::GradVarName("Out"));
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auto complex_dtype = framework::ToComplexType(dtype);
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return framework::OpKernelType(complex_dtype, ctx.GetPlace());
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}
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};
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template <typename T>
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class ImagGradOpMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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void Apply(GradOpPtr<T> grad_op) const override {
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grad_op->SetType("imag_grad");
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grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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grad_op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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}
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};
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DECLARE_INPLACE_OP_INFERER(ImagOpInplaceInferer, {"X", "Out"});
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DECLARE_INPLACE_OP_INFERER(ImagGradOpInplaceInferer,
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{framework::GradVarName("Out"),
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framework::GradVarName("X")});
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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(imag, ops::ImagOp, ops::ImagOpMaker,
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ops::ImagGradOpMaker<paddle::framework::OpDesc>,
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ops::ImagGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(imag_grad, ops::ImagGradOp);
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REGISTER_OP_CPU_KERNEL(imag, ops::ImagKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64>,
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ops::ImagKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128>);
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REGISTER_OP_CPU_KERNEL(imag_grad,
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ops::ImagGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex64>,
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ops::ImagGradKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::complex128>);
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