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110 lines
3.8 KiB
110 lines
3.8 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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/increment_op.h"
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#include <string>
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namespace paddle {
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namespace framework {
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class InferShapeContext;
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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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class IncrementOp : public framework::OperatorWithKernel {
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public:
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IncrementOp(const std::string &type, const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: OperatorWithKernel(type, inputs, outputs, attrs) {}
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE_EQ(framework::product(ctx->GetInputDim("X")), 1UL,
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platform::errors::InvalidArgument(
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"The number of elements in Input(X) should be 1."
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"Now the number is %d.",
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framework::product(ctx->GetInputDim("X"))));
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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "increment");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "increment");
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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ctx->ShareLoD("X", "Out");
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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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framework::OpKernelType kt = OperatorWithKernel::GetExpectedKernelType(ctx);
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// IncrementOp kernel's device type is decided by input tensor place
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kt.place_ = ctx.Input<framework::LoDTensor>("X")->place();
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return kt;
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}
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};
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class IncrementOpMaker : 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 increment operator");
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AddOutput("Out", "(Tensor) The output tensor of increment operator.");
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AddAttr<float>("step",
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"(float, default 1.0) "
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"The step size by which the "
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"input tensor will be incremented.")
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.SetDefault(1.0);
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AddComment(R"DOC(
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Increment Operator.
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The equation is:
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$$Out = X + step$$
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)DOC");
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}
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};
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template <typename T>
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class IncrementGradOpMaker : 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("increment");
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grad_op->SetInput("X", this->Output("Out"));
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grad_op->SetOutput("Out", this->Input("X"));
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grad_op->SetAttr("step", -BOOST_GET_CONST(float, this->GetAttr("step")));
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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(increment, ops::IncrementOp, ops::IncrementOpMaker,
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ops::IncrementGradOpMaker<paddle::framework::OpDesc>,
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ops::IncrementGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OP_CPU_KERNEL(
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increment, ops::IncrementKernel<paddle::platform::CPUDeviceContext, float>,
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ops::IncrementKernel<paddle::platform::CPUDeviceContext, double>,
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ops::IncrementKernel<paddle::platform::CPUDeviceContext, int>,
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ops::IncrementKernel<paddle::platform::CPUDeviceContext, int64_t>);
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