提交 2988a58e 编写于 作者: C caoying03

add unittest.

上级 84627bb9
...@@ -30,6 +30,12 @@ add_unittest_without_exec(test_CRFLayerGrad ...@@ -30,6 +30,12 @@ add_unittest_without_exec(test_CRFLayerGrad
add_test(NAME test_CRFLayerGrad add_test(NAME test_CRFLayerGrad
COMMAND test_CRFLayerGrad) COMMAND test_CRFLayerGrad)
################ test_SeqSliceLayerGrad ####################
add_unittest_without_exec(test_SeqSliceLayerGrad
test_SeqSliceLayerGrad.cpp
LayerGradUtil.cpp)
add_test(NAME test_SeqSliceLayerGrad
COMMAND test_SeqSliceLayerGrad)
add_unittest_without_exec(test_ActivationGrad add_unittest_without_exec(test_ActivationGrad
test_ActivationGrad.cpp test_ActivationGrad.cpp
......
/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gtest/gtest.h>
#include "ModelConfig.pb.h"
#include "paddle/gserver/layers/DataLayer.h"
#include "paddle/trainer/Trainer.h"
#include "LayerGradUtil.h"
#include "paddle/testing/TestUtil.h"
using namespace paddle; // NOLINT
using namespace std; // NOLINT
DECLARE_int32(gpu_id);
DECLARE_bool(thread_local_rand_use_global_seed);
const int MAX_SEQ_NUM = 5;
const int MAX_SEQ_LEN = 5;
const int MAX_BEAM_SIZE = 3;
vector<real> randSampling(real range, int n) {
CHECK_GE(range, n);
vector<real> num(range);
iota(begin(num), end(num), 0.);
if (range == n) return num;
random_shuffle(begin(num), end(num));
num.resize(n);
sort(begin(num), end(num));
return num;
}
void genSeqInfo(vector<int>& seqStartPos, vector<int>& subSeqStartPos) {
seqStartPos.resize(1, 0);
subSeqStartPos.resize(1, 0);
// srand((size_t)(time(NULL)));
srand(1);
int seqNum = 1 + (rand() % MAX_SEQ_NUM);
for (int i = 0; i < seqNum; ++i) {
int subSeqNum = 1 + (rand() % MAX_SEQ_NUM);
for (int j = 0; j < subSeqNum; ++j)
subSeqStartPos.push_back(subSeqStartPos.back() +
(1 + (rand() % MAX_SEQ_LEN)));
seqStartPos.push_back(subSeqStartPos.back());
}
}
/*
generate start indices according to sequence start positions.
*/
void genStarts(vector<int>& seqStartPos,
vector<vector<real>>& starts,
size_t beamSize) {
starts.clear();
starts.resize(seqStartPos.size() - 1, vector<real>(beamSize, -1.));
for (size_t i = 0; i < seqStartPos.size() - 1; ++i) {
int seqLen = seqStartPos[i + 1] - seqStartPos[i];
vector<real> randStarts =
randSampling(seqLen, min(seqLen, static_cast<int>(beamSize)));
copy(begin(randStarts), end(randStarts), begin(starts[i]));
}
}
/*
generate end indices according to sequence start positions and start indices.
*/
void genEnds(vector<int>& seqStartPos,
vector<vector<real>>& starts,
vector<vector<real>>& ends,
size_t beamSize) {
CHECK_EQ(seqStartPos.size() - 1, starts.size());
ends.clear();
ends.resize(seqStartPos.size() - 1, vector<real>(beamSize, -1.));
for (size_t i = 0; i < starts.size(); ++i) {
for (size_t j = 0; j < starts[i].size(); ++j) {
int seqLen = seqStartPos[i + 1] - seqStartPos[i];
CHECK_GE(seqLen - 1, starts[i][j]);
if (starts[i][j] == -1.) break;
if (starts[i][j] == (seqLen - 1)) {
ends[i][j] = starts[i][j];
} else {
ends[i][j] = starts[i][j] + randSampling(seqLen - starts[i][j], 1)[0];
}
}
}
}
void genTestData(vector<int>& seqStartPos,
vector<int>& subSeqStartPos,
vector<vector<real>>& starts,
vector<vector<real>>& ends,
bool hasSubseq) {
size_t beamSize = MAX_BEAM_SIZE;
genSeqInfo(seqStartPos, subSeqStartPos);
genStarts(hasSubseq ? subSeqStartPos : seqStartPos, starts, beamSize);
genEnds(hasSubseq ? subSeqStartPos : seqStartPos, starts, ends, beamSize);
}
template <typename T>
void flatten2dVector(vector<vector<T>>& inVec, vector<T>& outVec) {
size_t totalSize{0};
for (auto const& items : inVec) totalSize += items.size();
outVec.reserve(totalSize);
for (auto& items : inVec)
move(items.begin(), items.end(), back_inserter(outVec));
}
void testSeqSliceLayer(bool hasSubseq,
bool useGpu,
vector<int>& seqStartPos,
vector<int>& subSeqStartPos,
vector<vector<real>>& starts,
vector<vector<real>>& ends) {
// layer size is not crutial for this layer,
// so here use a small layer size in the unittest.
const size_t layerSize{4};
TestConfig config;
config.layerConfig.set_type("seq_slice");
config.layerConfig.set_size(layerSize);
// add the first input
MatrixPtr seqInputPtr =
Matrix::create(hasSubseq ? subSeqStartPos.back() : seqStartPos.back(),
layerSize,
false,
false);
seqInputPtr->randomizeUniform();
if (hasSubseq) {
config.inputDefs.push_back({INPUT_SELF_DEFINE_DATA,
"seq_input",
seqInputPtr,
seqStartPos,
subSeqStartPos});
} else {
config.inputDefs.push_back(
{INPUT_SELF_DEFINE_DATA, "seq_input", seqInputPtr, seqStartPos});
}
config.layerConfig.add_inputs();
// add start indices
if (starts.size()) {
vector<real> startsToVec;
flatten2dVector(starts, startsToVec);
MatrixPtr startMatrixPtr =
Matrix::create(starts.size(), starts[0].size(), false, false);
startMatrixPtr->copyFrom(startsToVec.data(), startsToVec.size());
config.inputDefs.push_back(
{INPUT_SELF_DEFINE_DATA, "starts", startMatrixPtr});
config.layerConfig.add_inputs();
}
// add end indices
if (ends.size()) {
vector<real> endsToVec;
flatten2dVector(ends, endsToVec);
MatrixPtr endMatrixPtr =
Matrix::create(ends.size(), ends[0].size(), false, false);
config.inputDefs.push_back({INPUT_SELF_DEFINE_DATA, "ends", endMatrixPtr});
config.layerConfig.add_inputs();
}
testLayerGrad(config, "seq_slice", /*batchSize*/ 100, false, useGpu, false);
}
TEST(Layer, SeqSliceLayer) {
vector<int> seqStartPos;
vector<int> subSeqStartPos;
vector<vector<real>> starts;
vector<vector<real>> ends;
genSeqInfo(seqStartPos, subSeqStartPos);
for (bool hasSubseq : {false, true}) {
genTestData(seqStartPos, subSeqStartPos, starts, ends, hasSubseq);
for (bool useGpu : {false, true}) {
vector<vector<real>> tmp;
testSeqSliceLayer(
hasSubseq, useGpu, seqStartPos, subSeqStartPos, tmp, ends);
testSeqSliceLayer(
hasSubseq, useGpu, seqStartPos, subSeqStartPos, starts, tmp);
testSeqSliceLayer(
hasSubseq, useGpu, seqStartPos, subSeqStartPos, starts, ends);
}
}
}
int main(int argc, char** argv) {
initMain(argc, argv);
hl_start();
hl_init(FLAGS_gpu_id);
FLAGS_thread_local_rand_use_global_seed = true;
srand(1);
testing::InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}
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