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112 lines
3.8 KiB
112 lines
3.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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class IncrementInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"),
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"Input(X) of IncrementOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
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"Output(Out) of IncrementOp should not be null.");
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PADDLE_ENFORCE_EQ(1, framework::product(ctx->GetInputDim("X")));
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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}
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};
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struct IncrementFunctor {
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IncrementFunctor(const framework::LoDTensor &x, framework::LoDTensor *out,
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float value)
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: x_(x), out_(out), value_(value) {}
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template <typename T>
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void operator()() const {
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*out_->data<T>() = *x_.data<T>() + static_cast<T>(value_);
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}
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const framework::LoDTensor &x_;
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framework::LoDTensor *out_;
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float value_;
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};
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class IncrementOp : public framework::OperatorBase {
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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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: OperatorBase(type, inputs, outputs, attrs) {}
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void Run(const framework::Scope &scope,
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const platform::DeviceContext &dev_ctx) const override {
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auto &x = scope.FindVar(Input("X"))->Get<framework::LoDTensor>();
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auto &out =
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*scope.FindVar(Output("Out"))->GetMutable<framework::LoDTensor>();
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PADDLE_ENFORCE(platform::is_cpu_place(x.place()));
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out.Resize(x.dims());
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out.mutable_data(x.place(), x.type());
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float value = Attr<float>("step");
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VLOG(10) << Output("Out") << " increase " << Input("X") << " with "
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<< value;
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framework::VisitDataType(framework::ToDataType(out.type()),
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IncrementFunctor(x, &out, value));
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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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IncrementOpMaker(OpProto *proto, OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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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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class IncrementGradOpMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto *grad_op = new framework::OpDesc();
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grad_op->SetType("increment");
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grad_op->SetInput("X", Output("Out"));
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grad_op->SetOutput("Out", Input("X"));
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grad_op->SetAttr("step", -boost::get<float>(GetAttr("step")));
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return std::unique_ptr<framework::OpDesc>(grad_op);
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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::IncrementInferShape,
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ops::IncrementOpMaker, ops::IncrementGradOpMaker);
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