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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "ModelAccuracyChecker.hpp"
#include <boost/test/unit_test.hpp>
#include <iostream>
#include <string>
using namespace armnnUtils;
namespace {
struct TestHelper
{
const std::map<std::string, std::string> GetValidationLabelSet()
{
std::map<std::string, std::string> validationLabelSet;
validationLabelSet.insert(std::make_pair("val_01.JPEG", "goldfinch"));
validationLabelSet.insert(std::make_pair("val_02.JPEG", "magpie"));
validationLabelSet.insert(std::make_pair("val_03.JPEG", "brambling"));
validationLabelSet.insert(std::make_pair("val_04.JPEG", "robin"));
validationLabelSet.insert(std::make_pair("val_05.JPEG", "indigo bird"));
validationLabelSet.insert(std::make_pair("val_06.JPEG", "ostrich"));
validationLabelSet.insert(std::make_pair("val_07.JPEG", "jay"));
validationLabelSet.insert(std::make_pair("val_08.JPEG", "snowbird"));
validationLabelSet.insert(std::make_pair("val_09.JPEG", "house finch"));
validationLabelSet.insert(std::make_pair("val_09.JPEG", "bulbul"));
return validationLabelSet;
}
const std::vector<armnnUtils::LabelCategoryNames> GetModelOutputLabels()
{
const std::vector<armnnUtils::LabelCategoryNames> modelOutputLabels =
{
{"ostrich", "Struthio camelus"},
{"brambling", "Fringilla montifringilla"},
{"goldfinch", "Carduelis carduelis"},
{"house finch", "linnet", "Carpodacus mexicanus"},
{"junco", "snowbird"},
{"indigo bunting", "indigo finch", "indigo bird", "Passerina cyanea"},
{"robin", "American robin", "Turdus migratorius"},
{"bulbul"},
{"jay"},
{"magpie"}
};
return modelOutputLabels;
}
};
}
BOOST_AUTO_TEST_SUITE(ModelAccuracyCheckerTest)
using TContainer =
mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>, std::vector<int8_t>>;
BOOST_FIXTURE_TEST_CASE(TestFloat32OutputTensorAccuracy, TestHelper)
{
ModelAccuracyChecker checker(GetValidationLabelSet(), GetModelOutputLabels());
// Add image 1 and check accuracy
std::vector<float> inferenceOutputVector1 = {0.05f, 0.10f, 0.70f, 0.15f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f};
TContainer inference1Container(inferenceOutputVector1);
std::vector<TContainer> outputTensor1;
outputTensor1.push_back(inference1Container);
std::string imageName = "val_01.JPEG";
checker.AddImageResult<TContainer>(imageName, outputTensor1);
// Top 1 Accuracy
float totalAccuracy = checker.GetAccuracy(1);
BOOST_CHECK(totalAccuracy == 100.0f);
// Add image 2 and check accuracy
std::vector<float> inferenceOutputVector2 = {0.10f, 0.0f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
TContainer inference2Container(inferenceOutputVector2);
std::vector<TContainer> outputTensor2;
outputTensor2.push_back(inference2Container);
imageName = "val_02.JPEG";
checker.AddImageResult<TContainer>(imageName, outputTensor2);
// Top 1 Accuracy
totalAccuracy = checker.GetAccuracy(1);
BOOST_CHECK(totalAccuracy == 50.0f);
// Top 2 Accuracy
totalAccuracy = checker.GetAccuracy(2);
BOOST_CHECK(totalAccuracy == 100.0f);
// Add image 3 and check accuracy
std::vector<float> inferenceOutputVector3 = {0.0f, 0.10f, 0.0f, 0.0f, 0.05f, 0.70f, 0.0f, 0.0f, 0.0f, 0.15f};
TContainer inference3Container(inferenceOutputVector3);
std::vector<TContainer> outputTensor3;
outputTensor3.push_back(inference3Container);
imageName = "val_03.JPEG";
checker.AddImageResult<TContainer>(imageName, outputTensor3);
// Top 1 Accuracy
totalAccuracy = checker.GetAccuracy(1);
BOOST_CHECK(totalAccuracy == 33.3333321f);
// Top 2 Accuracy
totalAccuracy = checker.GetAccuracy(2);
BOOST_CHECK(totalAccuracy == 66.6666641f);
// Top 3 Accuracy
totalAccuracy = checker.GetAccuracy(3);
BOOST_CHECK(totalAccuracy == 100.0f);
}
BOOST_AUTO_TEST_SUITE_END()
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