提交 9f990d90 编写于 作者: G gaoyuan

Add unittest of the priorbox layer

上级 1048aee0
...@@ -76,6 +76,7 @@ void PriorBoxLayer::forward(PassType passType) { ...@@ -76,6 +76,7 @@ void PriorBoxLayer::forward(PassType passType) {
auto image = getInput(1); auto image = getInput(1);
int imageWidth = image.getFrameWidth(); int imageWidth = image.getFrameWidth();
int imageHeight = image.getFrameHeight(); int imageHeight = image.getFrameHeight();
float stepW = static_cast<float>(imageWidth) / layerWidth; float stepW = static_cast<float>(imageWidth) / layerWidth;
float stepH = static_cast<float>(imageHeight) / layerHeight; float stepH = static_cast<float>(imageHeight) / layerHeight;
int dim = layerHeight * layerWidth * numPriors_ * 4; int dim = layerHeight * layerWidth * numPriors_ * 4;
......
...@@ -34,6 +34,14 @@ add_unittest_without_exec(test_ConvTrans ...@@ -34,6 +34,14 @@ add_unittest_without_exec(test_ConvTrans
add_test(NAME test_ConvTrans add_test(NAME test_ConvTrans
COMMAND test_ConvTrans) COMMAND test_ConvTrans)
################# test_PriorBox #######################
add_unittest_without_exec(test_PriorBox
test_PriorBox.cpp
LayerGradUtil.cpp
TestUtil.cpp)
add_test(NAME test_PriorBox
COMMAND test_PriorBox)
################# test_ConvUnify ####################### ################# test_ConvUnify #######################
add_unittest_without_exec(test_ConvUnify add_unittest_without_exec(test_ConvUnify
test_ConvUnify.cpp test_ConvUnify.cpp
......
/* Copyright (c) 2016 PaddlePaddle Authors. 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 <string>
#include <vector>
#include "LayerGradUtil.h"
#include "TestUtil.h"
using namespace paddle; // NOLINT
using namespace std; // NOLINT
P_DECLARE_bool(use_gpu);
P_DECLARE_int32(gpu_id);
P_DECLARE_bool(thread_local_rand_use_global_seed);
// Do one forward pass of priorBox layer and check to see if its output
// matches the given result
void doOnePriorBoxTest(size_t featureMapWidth,
size_t featureMapHeight,
size_t imageWidth,
size_t imageHeight,
vector<int> minSize,
vector<int> maxSize,
vector<float> aspectRatio,
vector<float> variance,
MatrixPtr& result) {
// Setting up the priorbox layer
TestConfig configt;
configt.layerConfig.set_type("priorbox");
configt.inputDefs.push_back({INPUT_DATA, "featureMap", 1, 0});
LayerInputConfig* input = configt.layerConfig.add_inputs();
configt.inputDefs.push_back({INPUT_DATA, "image", 1, 0});
configt.layerConfig.add_inputs();
PriorBoxConfig* pb = input->mutable_priorbox_conf();
for (size_t i = 0; i < minSize.size(); i++) pb->add_min_size(minSize[i]);
for (size_t i = 0; i < maxSize.size(); i++) pb->add_max_size(maxSize[i]);
for (size_t i = 0; i < aspectRatio.size(); i++)
pb->add_aspect_ratio(aspectRatio[i]);
for (size_t i = 0; i < variance.size(); i++) pb->add_variance(variance[i]);
// data layer initialize
std::vector<DataLayerPtr> dataLayers;
LayerMap layerMap;
vector<Argument> datas;
initDataLayer(
configt, &dataLayers, &datas, &layerMap, "priorbox", 1, false, true);
dataLayers[0]->getOutput().setFrameHeight(featureMapHeight);
dataLayers[0]->getOutput().setFrameWidth(featureMapWidth);
dataLayers[1]->getOutput().setFrameHeight(imageHeight);
dataLayers[1]->getOutput().setFrameWidth(imageWidth);
// test layer initialize
std::vector<ParameterPtr> parameters;
LayerPtr priorboxLayer;
initTestLayer(configt, &layerMap, &parameters, &priorboxLayer);
priorboxLayer->forward(PASS_GC);
checkMatrixEqual(priorboxLayer->getOutputValue(), result);
}
TEST(Layer, priorBoxLayerFwd) {
vector<int> minSize;
vector<int> maxSize;
vector<float> aspectRatio;
vector<float> variance;
minSize.push_back(276);
maxSize.push_back(330);
variance.push_back(0.1);
variance.push_back(0.1);
variance.push_back(0.2);
variance.push_back(0.2);
MatrixPtr result;
result = Matrix::create(1, 2 * 8, false, false);
float resultData[] = {0.04,
0.04,
0.96,
0.96,
0.1,
0.1,
0.2,
0.2,
0,
0,
1,
1,
0.1,
0.1,
0.2,
0.2};
result->setData(resultData);
doOnePriorBoxTest(/* featureMapWidth */ 1,
/* featureMapHeight */ 1,
/* imageWidth */ 300,
/* imageHeight */ 300,
minSize,
maxSize,
aspectRatio,
variance,
result);
variance[1] = 0.2;
variance[3] = 0.1;
maxSize.pop_back();
Matrix::resizeOrCreate(result, 1, 4 * 8, false, false);
float resultData2[] = {0, 0, 0.595, 0.595, 0.1, 0.2, 0.2, 0.1,
0.405, 0, 1, 0.595, 0.1, 0.2, 0.2, 0.1,
0, 0.405, 0.595, 1, 0.1, 0.2, 0.2, 0.1,
0.405, 0.405, 1, 1, 0.1, 0.2, 0.2, 0.1};
result->setData(resultData2);
doOnePriorBoxTest(/* featureMapWidth */ 2,
/* featureMapHeight */ 2,
/* imageWidth */ 400,
/* imageHeight */ 400,
minSize,
maxSize,
aspectRatio,
variance,
result);
aspectRatio.push_back(2);
Matrix::resizeOrCreate(result, 1, 3 * 8, false, false);
float resultData3[] = {0.04, 0.04, 0.96, 0.96, 0.1, 0.2,
0.2, 0.1, 0, 0.17473088, 1, 0.825269,
0.1, 0.2, 0.2, 0.1, 0.17473088, 0,
0.825269, 1, 0.1, 0.2, 0.2, 0.1};
result->setData(resultData3);
doOnePriorBoxTest(/* featureMapWidth */ 1,
/* featureMapHeight */ 1,
/* imageWidth */ 300,
/* imageHeight */ 300,
minSize,
maxSize,
aspectRatio,
variance,
result);
}
int main(int argc, char** argv) {
testing::InitGoogleTest(&argc, argv);
initMain(argc, argv);
FLAGS_thread_local_rand_use_global_seed = true;
srand(1);
return RUN_ALL_TESTS();
}
...@@ -1583,7 +1583,7 @@ class PriorBoxLayer(LayerBase): ...@@ -1583,7 +1583,7 @@ class PriorBoxLayer(LayerBase):
def __init__(self, name, inputs, size, min_size, max_size, aspect_ratio, def __init__(self, name, inputs, size, min_size, max_size, aspect_ratio,
variance): variance):
super(PriorBoxLayer, self).__init__(name, 'priorbox', 0, inputs) super(PriorBoxLayer, self).__init__(name, 'priorbox', 0, inputs)
config_assert(len(inputs) == 2, 'PriorBoxLayer must have 2 input') config_assert(len(inputs) == 2, 'PriorBoxLayer must have 2 inputs')
input_layer = self.get_input_layer(1) input_layer = self.get_input_layer(1)
config_assert( config_assert(
input_layer.type == 'data', input_layer.type == 'data',
...@@ -1591,6 +1591,7 @@ class PriorBoxLayer(LayerBase): ...@@ -1591,6 +1591,7 @@ class PriorBoxLayer(LayerBase):
'a data layer') 'a data layer')
config_assert(input_layer.width > 0, 'The data layer must set width') config_assert(input_layer.width > 0, 'The data layer must set width')
config_assert(input_layer.height > 0, 'The data layer must set height') config_assert(input_layer.height > 0, 'The data layer must set height')
config_assert(len(variance) == 4, 'The variance must have 4 inputs')
self.config.inputs[0].priorbox_conf.min_size.extend(min_size) self.config.inputs[0].priorbox_conf.min_size.extend(min_size)
self.config.inputs[0].priorbox_conf.max_size.extend(max_size) self.config.inputs[0].priorbox_conf.max_size.extend(max_size)
self.config.inputs[0].priorbox_conf.aspect_ratio.extend(aspect_ratio) self.config.inputs[0].priorbox_conf.aspect_ratio.extend(aspect_ratio)
......
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