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110 lines
3.9 KiB
110 lines
3.9 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/operators/scale_op.h"
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#include "paddle/operators/net_op.h"
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namespace paddle {
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namespace operators {
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class ScaleOp : public framework::OperatorWithKernel {
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public:
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ScaleOp(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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protected:
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void InferShape(const framework::InferShapeContext &ctx) const override {
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auto *in = ctx.Input<framework::Tensor>("X");
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auto *out = ctx.Output<framework::Tensor>("Out");
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out->Resize(in->dims());
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}
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};
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template <typename AttrType>
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class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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ScaleOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The input tensor of scale operator.").NotInGradient();
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AddOutput("Out", "The output tensor of scale operator.").NotInGradient();
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AddComment(R"DOC(Scale operator
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The equation is: Out = scale*X
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)DOC");
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AddAttr<AttrType>("scale", "The scaling factor of the scale operator.")
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.SetDefault(1.0);
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}
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};
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// IdentityOp's gradient is IdentityOp, too.
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// Grad(Out=scale(X)) => Grad(X) = scale(Grad(Out))
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template <typename AttrType>
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class ScaleGradOp : public NetOp {
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public:
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ScaleGradOp(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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: NetOp(type, inputs, outputs, attrs) {
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AppendOp(framework::OpRegistry::CreateOp(
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"scale", {{"X", {Input(framework::GradVarName("Out"))}}},
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{{"Out", {Output(framework::GradVarName("X"))}}},
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{{"scale", GetAttr<AttrType>("scale")}}));
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CompleteAddOp(false);
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}
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};
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// IdentityOp is an alias of the ScaleOp. This is also an example for creating
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// an alias of an existing operator.
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template <typename AttrType>
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class IdentityOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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IdentityOpMaker(framework::OpProto *proto,
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framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "The input tensor of identity op.");
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AddOutput("Out", "The output tensor of identity op.");
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AddComment(R"DOC(
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The identity operator is just an alias of the scale operator with the
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attribute scale is fixed to 1.0.
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)DOC");
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}
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};
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template <typename AttrType>
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class IdentityOp : public NetOp {
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public:
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IdentityOp(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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: NetOp(type, inputs, outputs, attrs) {
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AppendOp(framework::OpRegistry::CreateOp(
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"scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}},
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{{"scale", static_cast<AttrType>(1)}}));
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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_OP(scale, ops::ScaleOp, ops::ScaleOpMaker<float>, scale_grad,
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ops::ScaleGradOp<float>);
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REGISTER_OP_CPU_KERNEL(scale,
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ops::ScaleKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_WITHOUT_GRADIENT(identity, ops::IdentityOp<float>,
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ops::IdentityOpMaker<float>);
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