Add per TEST_METHOD names to the output directory structure, so parallel unit test runs won't overwrite one another. (#219)
This commit is contained in:
pmbrown1055
Ryan Lai
Родитель
a8727a3e5d
Коммит
25e1ded8c2
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@ -32,13 +32,16 @@ static HRESULT RunProc(LPWSTR commandLine)
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return HRESULT_FROM_WIN32(exitCode);
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}
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// Use this test method definition, if the test needs access to the METHOD_NAME
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#define TEST_METHOD_WITH_NAME(methodName) TEST_METHOD(methodName) { const std::wstring METHOD_NAME(L#methodName);
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namespace WinMLRunnerTest
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{
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static const std::wstring CURRENT_PATH = FileHelper::GetModulePath();
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static const std::wstring EXE_PATH = CURRENT_PATH + L"WinMLRunner.exe";
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static const std::wstring INPUT_FOLDER_PATH = CURRENT_PATH + L"test_folder_input";
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static const std::wstring OUTPUT_PATH = CURRENT_PATH + L"test_output.csv";
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static const std::wstring TENSOR_DATA_PATH = CURRENT_PATH + L"TestResult";
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static const std::wstring TENSOR_DATA_PATH = CURRENT_PATH + L"TestResults";
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static std::wstring BuildCommand(std::initializer_list<std::wstring>&& arguments)
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{
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@ -217,8 +220,7 @@ namespace WinMLRunnerTest
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return true;
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}
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TEST_CLASS(GarbageInputTest) {
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public: TEST_CLASS_INITIALIZE(SetupClass) {
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TEST_CLASS(GarbageInputTest) { public: TEST_CLASS_INITIALIZE(SetupClass) {
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// Make test_folder_input folder before starting the tests
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std::string mkFolderCommand = "mkdir " + std::string(INPUT_FOLDER_PATH.begin(), INPUT_FOLDER_PATH.end());
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system(mkFolderCommand.c_str());
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@ -241,6 +243,13 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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std::string copyCommand = "rd /s /q ";
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copyCommand += std::string(INPUT_FOLDER_PATH.begin(), INPUT_FOLDER_PATH.end());
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system(copyCommand.c_str());
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try
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{
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std::filesystem::remove_all(std::string(TENSOR_DATA_PATH.begin(), TENSOR_DATA_PATH.end()).c_str());
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}
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catch (const std::filesystem::filesystem_error &)
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{
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}
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}
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TEST_METHOD_CLEANUP(CleanupMethod)
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@ -521,6 +530,7 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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}
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catch (const std::filesystem::filesystem_error &) {}
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}
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TEST_METHOD(ProvidedImageInputCpuAndGpu)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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@ -552,78 +562,84 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath, L"-autoScale", L"Cubic" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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}
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TEST_METHOD(ProvidedImageInputOnlyGpuSaveTensor)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyGpuSaveTensor)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyCpuSaveTensor)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.png";
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_CPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1CpuIteration1.csv"));
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tensorDataPath + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyGpuSaveTensorImageDenotation)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyCpuSaveTensor)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_CPU.csv",
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tensorDataPath + L"\\softmaxout_1CpuIteration1.csv"));
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}
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyGpuSaveTensorImageDenotation)
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const std::wstring modelPath = CURRENT_PATH + L"mnist.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"mnist_28.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Mnist_8_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\Plus214_Output_0GpuIteration1.csv"));
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tensorDataPath + L"\\Plus214_Output_0GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyCpuSaveTensorImageDenotation)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyCpuSaveTensorImageDenotation)
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const std::wstring modelPath = CURRENT_PATH + L"mnist.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"mnist_28.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Mnist_8_input_CPU.csv",
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TENSOR_DATA_PATH + L"\\Plus214_Output_0CpuIteration1.csv"));
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tensorDataPath + L"\\Plus214_Output_0CpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyGpuSaveTensorFp16)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyGpuSaveTensorFp16)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1GpuIteration1.csv"));
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tensorDataPath + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyCpuSaveTensorFp16)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyCpuSaveTensorFp16)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.png";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_CPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1CpuIteration1.csv"));
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tensorDataPath + L"\\softmaxout_1CpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedImageInputOnlyCpuPerIterationPerformance)
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{
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TEST_METHOD_WITH_NAME(ProvidedImageInputOnlyCpuPerIterationPerformance)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command =
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BuildCommand({ EXE_PATH, L"-model", modelPath, L"-PerfOutput", OUTPUT_PATH, L"-perf",
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L"-SavePerIterationPerf", L"-BaseOutputPath", TENSOR_DATA_PATH,
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L"-SavePerIterationPerf", L"-BaseOutputPath", tensorDataPath,
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L"-PerIterationPath PerIterationData", L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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// We need to expect one more line because of the header
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Assert::AreEqual(static_cast<size_t>(2), GetOutputCSVLineCount(TENSOR_DATA_PATH + L"\\PerIterationData\\Summary.csv"));
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Assert::AreEqual(static_cast<size_t>(2), GetOutputCSVLineCount(tensorDataPath + L"\\PerIterationData\\Summary.csv"));
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}
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};
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@ -641,6 +657,7 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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}
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catch (const std::filesystem::filesystem_error &) {}
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}
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TEST_METHOD(ProvidedCSVInput)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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@ -648,6 +665,7 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath });
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Assert::AreEqual(S_OK, RunProc((wchar_t *)command.c_str()));
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}
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TEST_METHOD(ProvidedCSVBadBinding)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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@ -655,76 +673,82 @@ public: TEST_CLASS_INITIALIZE(SetupClass) {
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath });
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Assert::AreEqual(HRESULT_FROM_WIN32(ERROR_INVALID_PARAMETER), RunProc((wchar_t *)command.c_str()));
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}
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TEST_METHOD(ProvidedCSVInputGPUSaveCpuBoundTensor)
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{
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TEST_METHOD_WITH_NAME(ProvidedCSVInputGPUSaveCpuBoundTensor)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedCSVInputGPUSaveGpuBoundTensor)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU", L"-GPUBoundInput" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedCSVInputCPUSaveCpuBoundTensor)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_CPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1CpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedCSVInputGPUSaveCpuBoundTensorFp16)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedCSVInputCPUSaveCpuBoundTensorFp16)
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{
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_CPU.csv",
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TENSOR_DATA_PATH + L"\\softmaxout_1CpuIteration1.csv"));
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tensorDataPath + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD(ProvidedCSVInputOnlyGpuSaveCpuBoundTensorImageDenotation)
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{
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TEST_METHOD_WITH_NAME(ProvidedCSVInputGPUSaveGpuBoundTensor)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU", L"-GPUBoundInput" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_GPU.csv",
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tensorDataPath + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD_WITH_NAME(ProvidedCSVInputCPUSaveCpuBoundTensor)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Squeezenet_fish_input_CPU.csv",
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tensorDataPath + L"\\softmaxout_1CpuIteration1.csv"));
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}
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TEST_METHOD_WITH_NAME(ProvidedCSVInputGPUSaveCpuBoundTensorFp16)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_GPU.csv",
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tensorDataPath + L"\\softmaxout_1GpuIteration1.csv"));
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}
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TEST_METHOD_WITH_NAME(ProvidedCSVInputCPUSaveCpuBoundTensorFp16)
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const std::wstring modelPath = CURRENT_PATH + L"SqueezeNet_fp16.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"fish.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensorsFP16(L"OutputTensorData\\Squeezenet_fp16_fish_input_CPU.csv",
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tensorDataPath + L"\\softmaxout_1CpuIteration1.csv"));
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}
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TEST_METHOD_WITH_NAME(ProvidedCSVInputOnlyGpuSaveCpuBoundTensorImageDenotation)
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const std::wstring modelPath = CURRENT_PATH + L"mnist.onnx";
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const std::wstring inputPath = CURRENT_PATH + L"mnist_28.csv";
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
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const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-GPU" });
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-GPU" });
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
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Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Mnist_8_input_GPU.csv",
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TENSOR_DATA_PATH + L"\\Plus214_Output_0GpuIteration1.csv"));
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tensorDataPath + L"\\Plus214_Output_0GpuIteration1.csv"));
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}
|
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TEST_METHOD(ProvidedCSVInputOnlyCpuSaveCpuBoundTensorImageDenotation)
|
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{
|
||||
|
||||
TEST_METHOD_WITH_NAME(ProvidedCSVInputOnlyCpuSaveCpuBoundTensorImageDenotation)
|
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const std::wstring modelPath = CURRENT_PATH + L"mnist.onnx";
|
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const std::wstring inputPath = CURRENT_PATH + L"mnist_28.csv";
|
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const std::wstring tensorDataPath = TENSOR_DATA_PATH + L"\\" + METHOD_NAME;
|
||||
const std::wstring command = BuildCommand({ EXE_PATH, L"-model ", modelPath, L"-input", inputPath,
|
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L"-SaveTensorData", L"First", L"-PerIterationPath", TENSOR_DATA_PATH, L"-CPU" });
|
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L"-SaveTensorData", L"First", L"-PerIterationPath", tensorDataPath, L"-CPU" });
|
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Assert::AreEqual(S_OK, RunProc((wchar_t*)command.c_str()));
|
||||
Assert::AreEqual(true, CompareTensors(L"OutputTensorData\\Mnist_8_input_CPU.csv",
|
||||
TENSOR_DATA_PATH + L"\\Plus214_Output_0CpuIteration1.csv"));
|
||||
tensorDataPath + L"\\Plus214_Output_0CpuIteration1.csv"));
|
||||
}
|
||||
};
|
||||
|
||||
|
|
|
|||
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