From a4247d5a50502811a6956dffd990c0254622b7e1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C3=89anna=20=C3=93=20Cath=C3=A1in?= Date: Wed, 8 May 2019 14:00:45 +0100 Subject: IVGCVSW-2900 Adding the Accuracy Checker Tool and tests MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Change-Id: I4ac325e45f2236b8e0757d21046f117024ce3979 Signed-off-by: Éanna Ó Catháin --- CMakeLists.txt | 3 + src/armnn/test/ModelAccuracyCheckerTest.cpp | 98 +++++++ src/armnnUtils/ModelAccuracyChecker.cpp | 31 +++ src/armnnUtils/ModelAccuracyChecker.hpp | 103 ++++++++ tests/CMakeLists.txt | 26 ++ tests/InferenceTest.cpp | 12 + .../ModelAccuracyTool-Armnn.cpp | 289 +++++++++++++++++++++ 7 files changed, 562 insertions(+) create mode 100644 src/armnn/test/ModelAccuracyCheckerTest.cpp create mode 100644 src/armnnUtils/ModelAccuracyChecker.cpp create mode 100644 src/armnnUtils/ModelAccuracyChecker.hpp create mode 100644 tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp diff --git a/CMakeLists.txt b/CMakeLists.txt index b3056c9cae..c54c3955f1 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -42,6 +42,8 @@ list(APPEND armnnUtils_sources src/armnnUtils/HeapProfiling.hpp src/armnnUtils/LeakChecking.cpp src/armnnUtils/LeakChecking.hpp + src/armnnUtils/ModelAccuracyChecker.cpp + src/armnnUtils/ModelAccuracyChecker.hpp src/armnnUtils/CsvReader.cpp src/armnnUtils/CsvReader.hpp src/armnnUtils/FloatingPointConverter.cpp @@ -455,6 +457,7 @@ if(BUILD_UNIT_TESTS) src/armnn/test/GraphUtils.hpp src/armnn/test/InstrumentTests.cpp src/armnn/test/LayerValidateOutputTest.cpp + src/armnn/test/ModelAccuracyCheckerTest.cpp src/armnn/test/NetworkTests.cpp src/armnn/test/ObservableTest.cpp src/armnn/test/OptimizerTests.cpp diff --git a/src/armnn/test/ModelAccuracyCheckerTest.cpp b/src/armnn/test/ModelAccuracyCheckerTest.cpp new file mode 100644 index 0000000000..f3a6c9d81d --- /dev/null +++ b/src/armnn/test/ModelAccuracyCheckerTest.cpp @@ -0,0 +1,98 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// +#include "ModelAccuracyChecker.hpp" + +#include +#include + +#include +#include +#include +#include +#include +#include + +using namespace armnnUtils; + +struct TestHelper { + const std::map GetValidationLabelSet() + { + std::map validationLabelSet; + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000001", 2)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000002", 9)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000003", 1)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000004", 6)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000005", 5)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000006", 0)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000007", 8)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000008", 4)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000009", 3)); + validationLabelSet.insert( std::make_pair("ILSVRC2012_val_00000009", 7)); + + return validationLabelSet; + } +}; + +BOOST_AUTO_TEST_SUITE(ModelAccuracyCheckerTest) + +using TContainer = boost::variant, std::vector, std::vector>; + +BOOST_FIXTURE_TEST_CASE(TestFloat32OutputTensorAccuracy, TestHelper) +{ + ModelAccuracyChecker checker(GetValidationLabelSet()); + + // Add image 1 and check accuracy + std::vector 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 outputTensor1; + outputTensor1.push_back(inference1Container); + + std::string imageName = "ILSVRC2012_val_00000001.JPEG"; + checker.AddImageResult(imageName, outputTensor1); + + // Top 1 Accuracy + float totalAccuracy = checker.GetAccuracy(1); + BOOST_CHECK(totalAccuracy == 100.0f); + + // Add image 2 and check accuracy + std::vector 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 outputTensor2; + outputTensor2.push_back(inference2Container); + + imageName = "ILSVRC2012_val_00000002.JPEG"; + checker.AddImageResult(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 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 outputTensor3; + outputTensor3.push_back(inference3Container); + + imageName = "ILSVRC2012_val_00000003.JPEG"; + checker.AddImageResult(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() diff --git a/src/armnnUtils/ModelAccuracyChecker.cpp b/src/armnnUtils/ModelAccuracyChecker.cpp new file mode 100644 index 0000000000..bee5ca2365 --- /dev/null +++ b/src/armnnUtils/ModelAccuracyChecker.cpp @@ -0,0 +1,31 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include +#include +#include +#include "ModelAccuracyChecker.hpp" + +namespace armnnUtils +{ + +armnnUtils::ModelAccuracyChecker::ModelAccuracyChecker(const std::map& validationLabels) + : m_GroundTruthLabelSet(validationLabels){} + +float ModelAccuracyChecker::GetAccuracy(unsigned int k) +{ + if(k > 10) { + BOOST_LOG_TRIVIAL(info) << "Accuracy Tool only supports a maximum of Top 10 Accuracy. " + "Printing Top 10 Accuracy result!"; + k = 10; + } + unsigned int total = 0; + for (unsigned int i = k; i > 0; --i) + { + total += m_TopK[i]; + } + return static_cast(total * 100) / static_cast(m_ImagesProcessed); +} +} \ No newline at end of file diff --git a/src/armnnUtils/ModelAccuracyChecker.hpp b/src/armnnUtils/ModelAccuracyChecker.hpp new file mode 100644 index 0000000000..abf994b5e1 --- /dev/null +++ b/src/armnnUtils/ModelAccuracyChecker.hpp @@ -0,0 +1,103 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace armnnUtils +{ + +using namespace armnn; + +class ModelAccuracyChecker +{ +public: + ModelAccuracyChecker(const std::map& validationLabelSet); + + float GetAccuracy(unsigned int k); + + template + void AddImageResult(const std::string& imageName, std::vector outputTensor) + { + // Increment the total number of images processed + ++m_ImagesProcessed; + + std::map confidenceMap; + auto & output = outputTensor[0]; + + // Create a map of all predictions + boost::apply_visitor([&](auto && value) + { + int index = 0; + for (const auto & o : value) + { + if (o > 0) + { + confidenceMap.insert(std::pair(index, static_cast(o))); + } + ++index; + } + }, + output); + + // Create a comparator for sorting the map in order of highest probability + typedef std::function, std::pair)> Comparator; + + Comparator compFunctor = + [](std::pair element1, std::pair element2) + { + return element1.second > element2.second; + }; + + // Do the sorting and store in an ordered set + std::set, Comparator> setOfPredictions( + confidenceMap.begin(), confidenceMap.end(), compFunctor); + + std::string trimmedName = GetTrimmedImageName(imageName); + int value = m_GroundTruthLabelSet.find(trimmedName)->second; + + unsigned int index = 1; + for (std::pair element : setOfPredictions) + { + if(element.first == value) + { + ++m_TopK[index]; + } else + { + ++index; + } + } + } + + std::string GetTrimmedImageName(const std::string& imageName) const + { + std::string trimmedName; + size_t lastindex = imageName.find_last_of("."); + if(lastindex != std::string::npos) + { + trimmedName = imageName.substr(0, lastindex); + } else + { + trimmedName = imageName; + } + return trimmedName; + } + +private: + const std::map m_GroundTruthLabelSet; + std::vector m_TopK = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; + unsigned int m_ImagesProcessed = 0; +}; +} //namespace armnnUtils + diff --git a/tests/CMakeLists.txt b/tests/CMakeLists.txt index 028fc8283f..dfcf4b48e0 100644 --- a/tests/CMakeLists.txt +++ b/tests/CMakeLists.txt @@ -291,6 +291,32 @@ if (BUILD_ARMNN_SERIALIZER OR BUILD_CAFFE_PARSER OR BUILD_TF_PARSER OR BUILD_TF_ addDllCopyCommands(ExecuteNetwork) endif() +if(BUILD_ACCURACY_TOOL) + macro(AccuracyTool executorName) + target_link_libraries(${executorName} ${CMAKE_THREAD_LIBS_INIT}) + if(OPENCL_LIBRARIES) + target_link_libraries(${executorName} ${OPENCL_LIBRARIES}) + endif() + target_link_libraries(${executorName} + ${Boost_SYSTEM_LIBRARY} + ${Boost_FILESYSTEM_LIBRARY} + ${Boost_PROGRAM_OPTIONS_LIBRARY}) + addDllCopyCommands(${executorName}) + endmacro() + + set(ModelAccuracyTool-Armnn_sources + ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp) + + add_executable_ex(ModelAccuracyTool ${ModelAccuracyTool-Armnn_sources}) + target_include_directories(ModelAccuracyTool PRIVATE ../src/armnn) + target_include_directories(ModelAccuracyTool PRIVATE ../src/armnnUtils) + target_include_directories(ModelAccuracyTool PRIVATE ../src/backends) + target_link_libraries(ModelAccuracyTool inferenceTest) + target_link_libraries(ModelAccuracyTool armnn) + target_link_libraries(ModelAccuracyTool armnnSerializer) + AccuracyTool(ModelAccuracyTool) +endif() + if(BUILD_ARMNN_QUANTIZER) macro(ImageTensorExecutor executorName) target_link_libraries(${executorName} ${CMAKE_THREAD_LIBS_INIT}) diff --git a/tests/InferenceTest.cpp b/tests/InferenceTest.cpp index 89e78def2f..cf97459ddc 100644 --- a/tests/InferenceTest.cpp +++ b/tests/InferenceTest.cpp @@ -92,6 +92,12 @@ bool ParseCommandLine(int argc, char** argv, IInferenceTestCaseProvider& testCas bool ValidateDirectory(std::string& dir) { + if (dir.empty()) + { + std::cerr << "No directory specified" << std::endl; + return false; + } + if (dir[dir.length() - 1] != '/') { dir += "/"; @@ -103,6 +109,12 @@ bool ValidateDirectory(std::string& dir) return false; } + if (!boost::filesystem::is_directory(dir)) + { + std::cerr << "Given directory [" << dir << "] is not a directory" << std::endl; + return false; + } + return true; } diff --git a/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp new file mode 100644 index 0000000000..7b968302d9 --- /dev/null +++ b/tests/ModelAccuracyTool-Armnn/ModelAccuracyTool-Armnn.cpp @@ -0,0 +1,289 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ModelAccuracyChecker.hpp" +#include "../InferenceTest.hpp" +#include "../ImagePreprocessor.hpp" +#include "armnnDeserializer/IDeserializer.hpp" + +#include +#include +#include + +using namespace armnn::test; + +namespace po = boost::program_options; + +bool CheckOption(const po::variables_map& vm, + const char* option) +{ + // Check that the given option is valid. + if (option == nullptr) + { + return false; + } + + // Check whether 'option' is provided. + return vm.find(option) != vm.end(); +} + +template +std::vector ParseArrayImpl(std::istream& stream, TParseElementFunc parseElementFunc, const char * chars = "\t ,:") +{ + std::vector result; + // Processes line-by-line. + std::string line; + while (std::getline(stream, line)) + { + std::vector tokens; + try + { + // Coverity fix: boost::split() may throw an exception of type boost::bad_function_call. + boost::split(tokens, line, boost::algorithm::is_any_of(chars), boost::token_compress_on); + } + catch (const std::exception& e) + { + BOOST_LOG_TRIVIAL(error) << "An error occurred when splitting tokens: " << e.what(); + continue; + } + for (const std::string& token : tokens) + { + if (!token.empty()) // See https://stackoverflow.com/questions/10437406/ + { + try + { + result.push_back(parseElementFunc(token)); + } + catch (const std::exception&) + { + BOOST_LOG_TRIVIAL(error) << "'" << token << "' is not a valid number. It has been ignored."; + } + } + } + } + + return result; +} + +map LoadValidationLabels(const string & validationLabelPath); + +template +auto ParseDataArray(std::istream & stream); + +template<> +auto ParseDataArray(std::istream & stream) +{ + return ParseArrayImpl(stream, [](const std::string& s) { return std::stof(s); }); +} + +int main(int argc, char* argv[]) +{ + try + { + using namespace boost::filesystem; + armnn::LogSeverity level = armnn::LogSeverity::Debug; + armnn::ConfigureLogging(true, true, level); + armnnUtils::ConfigureLogging(boost::log::core::get().get(), true, true, level); + + // Set-up program Options + namespace po = boost::program_options; + + std::vector computeDevice; + std::vector defaultBackends = {armnn::Compute::CpuAcc, armnn::Compute::CpuRef}; + std::string modelPath; + std::string dataDir; + std::string inputName; + std::string outputName; + std::string validationLabelPath; + + const std::string backendsMessage = "Which device to run layers on by default. Possible choices: " + + armnn::BackendRegistryInstance().GetBackendIdsAsString(); + + po::options_description desc("Options"); + try + { + // Adds generic options needed to run Accuracy Tool. + desc.add_options() + ("help", "Display help messages") + ("model-path,m", po::value(&modelPath)->required(), "Path to armnn format model file") + ("compute,c", po::value>(&computeDevice)->default_value(defaultBackends), + backendsMessage.c_str()) + ("data-dir,d", po::value(&dataDir)->required(), + "Path to directory containing the ImageNet test data") + ("input-name,i", po::value(&inputName)->required(), + "Identifier of the input tensors in the network separated by comma.") + ("output-name,o", po::value(&outputName)->required(), + "Identifier of the output tensors in the network separated by comma.") + ("validation-labels-path,v", po::value(&validationLabelPath)->required(), + "Path to ImageNet Validation Label file"); + } + catch (const std::exception& e) + { + // Coverity points out that default_value(...) can throw a bad_lexical_cast, + // and that desc.add_options() can throw boost::io::too_few_args. + // They really won't in any of these cases. + BOOST_ASSERT_MSG(false, "Caught unexpected exception"); + std::cerr << "Fatal internal error: " << e.what() << std::endl; + return 1; + } + + po::variables_map vm; + try + { + po::store(po::parse_command_line(argc, argv, desc), vm); + + if (vm.count("help")) + { + std::cout << desc << std::endl; + return 1; + } + po::notify(vm); + } + catch (po::error& e) + { + std::cerr << e.what() << std::endl << std::endl; + std::cerr << desc << std::endl; + return 1; + } + + // Check if the requested backend are all valid + std::string invalidBackends; + if (!CheckRequestedBackendsAreValid(computeDevice, armnn::Optional(invalidBackends))) + { + BOOST_LOG_TRIVIAL(fatal) << "The list of preferred devices contains invalid backend IDs: " + << invalidBackends; + return EXIT_FAILURE; + } + armnn::Status status; + + // Create runtime + armnn::IRuntime::CreationOptions options; + armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options)); + std::ifstream file(modelPath); + + // Create Parser + using IParser = armnnDeserializer::IDeserializer; + auto armnnparser(IParser::Create()); + + // Create a network + armnn::INetworkPtr network = armnnparser->CreateNetworkFromBinary(file); + + // Optimizes the network. + armnn::IOptimizedNetworkPtr optimizedNet(nullptr, nullptr); + try + { + optimizedNet = armnn::Optimize(*network, computeDevice, runtime->GetDeviceSpec()); + } + catch (armnn::Exception& e) + { + std::stringstream message; + message << "armnn::Exception (" << e.what() << ") caught from optimize."; + BOOST_LOG_TRIVIAL(fatal) << message.str(); + return 1; + } + + // Loads the network into the runtime. + armnn::NetworkId networkId; + status = runtime->LoadNetwork(networkId, std::move(optimizedNet)); + if (status == armnn::Status::Failure) + { + BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to load network"; + return 1; + } + + // Set up Network + using BindingPointInfo = InferenceModelInternal::BindingPointInfo; + + const armnnDeserializer::BindingPointInfo& + inputBindingInfo = armnnparser->GetNetworkInputBindingInfo(0, inputName); + + std::pair + m_InputBindingInfo(inputBindingInfo.m_BindingId, inputBindingInfo.m_TensorInfo); + std::vector inputBindings = { m_InputBindingInfo }; + + const armnnDeserializer::BindingPointInfo& + outputBindingInfo = armnnparser->GetNetworkOutputBindingInfo(0, outputName); + + std::pair + m_OutputBindingInfo(outputBindingInfo.m_BindingId, outputBindingInfo.m_TensorInfo); + std::vector outputBindings = { m_OutputBindingInfo }; + + path pathToDataDir(dataDir); + map validationLabels = LoadValidationLabels(validationLabelPath); + armnnUtils::ModelAccuracyChecker checker(validationLabels); + using TContainer = boost::variant, std::vector, std::vector>; + + if(ValidateDirectory(dataDir)) + { + for (auto & imageEntry : boost::make_iterator_range(directory_iterator(pathToDataDir), {})) + { + cout << "Processing image: " << imageEntry << "\n"; + + std::ifstream inputTensorFile(imageEntry.path().string()); + vector inputDataContainers; + inputDataContainers.push_back(ParseDataArray(inputTensorFile)); + vector outputDataContainers = {vector(1001)}; + + status = runtime->EnqueueWorkload(networkId, + armnnUtils::MakeInputTensors(inputBindings, inputDataContainers), + armnnUtils::MakeOutputTensors(outputBindings, outputDataContainers)); + + if (status == armnn::Status::Failure) + { + BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to enqueue workload for image: " << imageEntry; + } + + const std::string imageName = imageEntry.path().filename().string(); + checker.AddImageResult(imageName, outputDataContainers); + } + } + else + { + return 1; + } + + for(unsigned int i = 1; i <= 5; ++i) + { + std::cout << "Top " << i << " Accuracy: " << checker.GetAccuracy(i) << "%" << "\n"; + } + + BOOST_LOG_TRIVIAL(info) << "Accuracy Tool ran successfully!"; + return 0; + } + catch (armnn::Exception const & e) + { + // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an + // exception of type std::length_error. + // Using stderr instead in this context as there is no point in nesting try-catch blocks here. + std::cerr << "Armnn Error: " << e.what() << std::endl; + return 1; + } + catch (const std::exception & e) + { + // Coverity fix: various boost exceptions can be thrown by methods called by this test. + std::cerr << "WARNING: ModelAccuracyTool-Armnn: An error has occurred when running the " + "Accuracy Tool: " << e.what() << std::endl; + return 1; + } +} + +map LoadValidationLabels(const string & validationLabelPath) +{ + std::string imageName; + int classification; + map validationLabel; + ifstream infile(validationLabelPath); + while (infile >> imageName >> classification) + { + std::string trimmedName; + size_t lastindex = imageName.find_last_of("."); + if(lastindex != std::string::npos) + { + trimmedName = imageName.substr(0, lastindex); + } + validationLabel.insert(pair(trimmedName, classification)); + } + return validationLabel; +} -- cgit v1.2.1