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94 lines
3.0 KiB
94 lines
3.0 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/l1_norm_op.h"
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#include <memory>
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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class L1NormOp : 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", "L1NormOp");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "L1NormOp");
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ctx->SetOutputDim("Out", {1});
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}
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};
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class L1NormGradOp : 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", "L1NormGradOp");
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OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
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"Out@GRAD", "L1NormGradOp");
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OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("X")), "Output",
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"X@GRAD", "L1NormGradOp");
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ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
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}
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};
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class L1NormOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "(Tensor) The input of l1_norm op.");
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AddOutput("Out", "(Scalar) The output of l1_norm op.");
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AddComment(R"DOC(
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L1 Norm Operator.
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Computes the L1 norm of a tensor.
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$$Out = \sum{|X|}$$
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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 L1NormGradMaker : 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("l1_norm_grad");
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op->SetInput("X", this->Input("X"));
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op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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op->SetAttrMap(this->Attrs());
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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(l1_norm, ops::L1NormOp, ops::L1NormOpMaker,
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ops::L1NormGradMaker<paddle::framework::OpDesc>,
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ops::L1NormGradMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(l1_norm_grad, ops::L1NormGradOp);
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REGISTER_OP_CPU_KERNEL(
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l1_norm, ops::L1NormKernel<paddle::platform::CPUDeviceContext, float>);
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REGISTER_OP_CPU_KERNEL(
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l1_norm_grad,
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ops::L1NormGradKernel<paddle::platform::CPUDeviceContext, float>);
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