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75 lines
2.7 KiB
75 lines
2.7 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/accuracy_op.h"
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namespace paddle {
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namespace operators {
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class AccuracyOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContextBase *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("Inference"),
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"Input(Inference) of AccuracyOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Label"),
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"Input(Label) of AccuracyOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Accuracy"),
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"Output(Accuracy) of AccuracyOp should not be null.");
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auto inference_dim = ctx->GetInputDim("Inference");
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auto label_dim = ctx->GetInputDim("Label");
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PADDLE_ENFORCE_EQ(label_dim.size(), 1, "label must be a vector");
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PADDLE_ENFORCE_EQ(inference_dim[0], label_dim[0],
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"inference size must be the same as label size");
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ctx->SetOutputDim("Accuracy", {1});
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ctx->ShareLoD("Inference", /*->*/ "Accuracy");
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}
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};
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class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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AccuracyOpMaker(framework::OpProto *proto,
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framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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// TODO(typhoonzero): support both inference value and indices.
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AddInput("Inference", "topk(indices) the network output");
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AddInput("Label", "Label of the training data");
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// TODO(typhoonzero): AddInput("Weight", ...
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AddOutput("Accuracy", "The accuracy of current batch");
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AddComment(R"DOC(
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Accuracy. It will print accuracy rate for classification.
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The accuracy is:
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.. math::
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accuracy = \\frac{NumOfCorrectPredicts}{NumOfAllSamples})
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Both the input `Inference` and `Label` can carry the LoD (Level of Details)
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information, or not. But the output only shares the LoD with input `Inference`.
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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_OP_WITHOUT_GRADIENT(accuracy, ops::AccuracyOp, ops::AccuracyOpMaker);
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REGISTER_OP_CPU_KERNEL(accuracy,
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ops::AccuracyKernel<paddle::platform::CPUPlace, float>);
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