Luo Tao
7 years ago
committed by
zchen0211
parent
8013328ed8
commit
873ee9ab7e
@ -0,0 +1,125 @@
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/* 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 <gtest/gtest.h>
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#include <string>
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#include <vector>
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#include "LayerGradUtil.h"
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#include "paddle/testing/TestUtil.h"
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using namespace paddle; // NOLINT
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using namespace std; // NOLINT
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// Do one forward pass of expand layer and check to see if its output
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// matches the given result.(Test onlyCPU currently.)
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void doOneExpandTest(string trans_type,
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bool hasSubseq,
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bool useGpu,
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Argument& input1,
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Argument& input2,
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Argument& result) {
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FLAGS_use_gpu = false;
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// Setting up the expand layer
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TestConfig config;
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config.layerConfig.set_type("expand");
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auto inputType1 =
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trans_type == "non-seq" ? INPUT_DENSE_DIM_DATA : INPUT_SEQUENCE_DATA;
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config.inputDefs.push_back({inputType1, "layer0", 1, 0});
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auto inputType2 =
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hasSubseq ? INPUT_HASSUB_SEQUENCE_DATA : INPUT_SEQUENCE_DATA;
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config.inputDefs.push_back({inputType2, "layer1", 1, 0});
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config.layerConfig.add_inputs();
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config.layerConfig.add_inputs();
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config.layerConfig.set_trans_type(trans_type);
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// data layer initialize
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std::vector<DataLayerPtr> dataLayers;
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LayerMap layerMap;
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vector<Argument> datas;
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initDataLayer(
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config, &dataLayers, &datas, &layerMap, "expand", 1, false, useGpu);
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dataLayers[0]->getOutput() = input1;
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dataLayers[1]->getOutput() = input2;
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// test layer initialize
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std::vector<ParameterPtr> parameters;
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LayerPtr expandLayer;
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initTestLayer(config, &layerMap, ¶meters, &expandLayer);
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expandLayer->forward(PASS_GC);
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checkMatrixEqual(expandLayer->getOutputValue(), result.value);
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}
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TEST(Layer, ExpandLayerFwd) {
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bool useGpu = false;
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// Assume batch_size =3 in all cases.
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// CPU case 1. non-seq expand to seq
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// input1 = 1,2,3
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// input2 = [4,5],[6],[7,8,9]
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// result = [1,1],[2],[3,3,3]
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Argument input1, input2, result;
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input1.value = Matrix::create(3, 1, false, useGpu);
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real input1Data[] = {1, 2, 3};
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input1.value->setData(input1Data);
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input2.value = Matrix::create(6, 1, false, useGpu);
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real input2Data[] = {4, 5, 6, 7, 8, 9};
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input2.value->setData(input2Data);
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input2.sequenceStartPositions = ICpuGpuVector::create(4, useGpu);
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int input2Seq[] = {0, 2, 3, 6};
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input2.sequenceStartPositions->copyFrom(input2Seq, 4, useGpu);
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result.value = Matrix::create(6, 1, false, useGpu);
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real resultData[] = {1, 1, 2, 3, 3, 3};
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result.value->setData(resultData);
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doOneExpandTest("non-seq", false, useGpu, input1, input2, result);
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// CPU case 2. non-seq expand to sub-seq
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// input1 = 1,2,3
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// input2 = [[4,5]],[[6]],[[7],[8,9]]
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// result = [[1,1]],[[2]],[[3],[3,3]]
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input2.subSequenceStartPositions = ICpuGpuVector::create(5, useGpu);
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int input2SubSeq[] = {0, 2, 3, 4, 6};
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input2.subSequenceStartPositions->copyFrom(input2SubSeq, 5, useGpu);
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doOneExpandTest("non-seq", true, useGpu, input1, input2, result);
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// CPU case 3. seq expand to sub-seq
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// input1 = [1,2],[3],[4]
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// input2 = [[4,5]],[[6]],[[7],[8,9]]
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// result = [[1,1]],[[2]],[[3],[4,4]]
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Matrix::resizeOrCreate(input1.value, 4, 1, false, useGpu);
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real input1Data_case3[] = {1, 2, 3, 4};
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input1.value->setData(input1Data_case3);
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input1.sequenceStartPositions = ICpuGpuVector::create(4, useGpu);
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int input1Seq[] = {0, 2, 3, 4};
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input1.sequenceStartPositions->copyFrom(input1Seq, 4, useGpu);
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real resultData_case3[] = {1, 1, 2, 3, 4, 4};
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result.value->setData(resultData_case3);
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doOneExpandTest("seq", true, useGpu, input1, input2, result);
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}
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int main(int argc, char** argv) {
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testing::InitGoogleTest(&argc, argv);
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initMain(argc, argv);
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return RUN_ALL_TESTS();
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}
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