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79 lines
2.6 KiB
79 lines
2.6 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/squared_l2_norm_op.h"
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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class SquaredL2NormOp : 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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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should be not null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should be not null.");
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ctx->SetOutputDim("Out", {1});
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}
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};
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class SquaredL2NormGradOp : 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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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should be not null.");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should be not null.");
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PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X")),
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"Output(X@GRAD) should be not null.");
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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 SquaredL2NormOpMaker : 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 squared_l2_norm op.");
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AddOutput("Out", "(Scalar) The output of squared_l2_norm op.");
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AddComment(R"DOC(
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SquaredL2Norm Operator.
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Computes the squared L2 norm of a tensor.
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$$Out = \sum_{i} X_{i}^2$$
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)DOC");
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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(squared_l2_norm, ops::SquaredL2NormOp,
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ops::SquaredL2NormOpMaker,
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paddle::framework::DefaultGradOpDescMaker<true>);
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REGISTER_OPERATOR(squared_l2_norm_grad, ops::SquaredL2NormGradOp);
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REGISTER_OP_CPU_KERNEL(
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squared_l2_norm,
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ops::SquaredL2NormKernel<paddle::platform::CPUDeviceContext, float>);
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REGISTER_OP_CPU_KERNEL(
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squared_l2_norm_grad,
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ops::SquaredL2NormGradKernel<paddle::platform::CPUDeviceContext, float>);
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