diff options
Diffstat (limited to 'tests/ExecuteNetwork/ExecuteNetwork.cpp')
| -rw-r--r-- | tests/ExecuteNetwork/ExecuteNetwork.cpp | 87 |
1 files changed, 45 insertions, 42 deletions
diff --git a/tests/ExecuteNetwork/ExecuteNetwork.cpp b/tests/ExecuteNetwork/ExecuteNetwork.cpp index e3ca22e0ff..f812e53e04 100644 --- a/tests/ExecuteNetwork/ExecuteNetwork.cpp +++ b/tests/ExecuteNetwork/ExecuteNetwork.cpp @@ -54,18 +54,27 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, builder(&tfLiteInterpreter); tfLiteInterpreter->AllocateTensors(); - // Create the Armnn Delegate - armnnDelegate::DelegateOptions delegateOptions(params.m_ComputeDevices); - std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> - theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), - armnnDelegate::TfLiteArmnnDelegateDelete); - // Register armnn_delegate to TfLiteInterpreter - int status = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(theArmnnDelegate)); - if (status == kTfLiteError) + int status = 0; + if (params.m_TfLiteExecutor == ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate) { - ARMNN_LOG(fatal) << "Could not register ArmNN TfLite Delegate to TfLiteInterpreter!"; - return EXIT_FAILURE; + // Create the Armnn Delegate + armnnDelegate::DelegateOptions delegateOptions(params.m_ComputeDevices); + std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)> + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + // Register armnn_delegate to TfLiteInterpreter + status = tfLiteInterpreter->ModifyGraphWithDelegate(std::move(theArmnnDelegate)); + if (status == kTfLiteError) + { + ARMNN_LOG(fatal) << "Could not register ArmNN TfLite Delegate to TfLiteInterpreter!"; + return EXIT_FAILURE; + } } + else + { + std::cout << "Running on TfLite without ArmNN delegate\n"; + } + std::vector<std::string> inputBindings; for (const std::string& inputName: params.m_InputNames) @@ -110,7 +119,7 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, std::copy(tensorData.begin(), tensorData.end(), inputData); } - else if (params.m_InputTypes[inputIndex].compare("int8") == 0) + else if (params.m_InputTypes[inputIndex].compare("qsymms8") == 0) { auto inputData = tfLiteInterpreter->typed_tensor<int8_t>(input); @@ -180,7 +189,7 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, for (size_t x = 0; x < params.m_Iterations; x++) { // Run the inference - tfLiteInterpreter->Invoke(); + status = tfLiteInterpreter->Invoke(); // Print out the output for (unsigned int outputIndex = 0; outputIndex < params.m_OutputNames.size(); ++outputIndex) @@ -207,11 +216,7 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, for (int i = 0; i < outputSize; ++i) { - std::cout << tfLiteDelageOutputData[i] << ", "; - if (i % 60 == 0) - { - std::cout << std::endl; - } + printf("%f ", tfLiteDelageOutputData[i]); } } else if (params.m_OutputTypes[outputIndex].compare("int") == 0) @@ -226,14 +231,10 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, for (int i = 0; i < outputSize; ++i) { - std::cout << tfLiteDelageOutputData[i] << ", "; - if (i % 60 == 0) - { - std::cout << std::endl; - } + printf("%d ", tfLiteDelageOutputData[i]); } } - else if (params.m_OutputTypes[outputIndex].compare("int8") == 0) + else if (params.m_OutputTypes[outputIndex].compare("qsymms8") == 0) { auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<int8_t>(tfLiteDelegateOutputId); if(tfLiteDelageOutputData == NULL) @@ -245,11 +246,7 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, for (int i = 0; i < outputSize; ++i) { - std::cout << signed(tfLiteDelageOutputData[i]) << ", "; - if (i % 60 == 0) - { - std::cout << std::endl; - } + printf("%d ", tfLiteDelageOutputData[i]); } } else if (params.m_OutputTypes[outputIndex].compare("qasymm8") == 0) @@ -264,11 +261,7 @@ int TfLiteDelegateMainImpl(const ExecuteNetworkParams& params, for (int i = 0; i < outputSize; ++i) { - std::cout << unsigned(tfLiteDelageOutputData[i]) << ", "; - if (i % 60 == 0) - { - std::cout << std::endl; - } + printf("%u ", tfLiteDelageOutputData[i]); } } else @@ -289,7 +282,8 @@ template<typename TParser, typename TDataType> int MainImpl(const ExecuteNetworkParams& params, const std::shared_ptr<armnn::IRuntime>& runtime = nullptr) { - using TContainer = mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>>; + using TContainer = + mapbox::util::variant<std::vector<float>, std::vector<int>, std::vector<unsigned char>, std::vector<int8_t>>; std::vector<TContainer> inputDataContainers; @@ -383,6 +377,10 @@ int MainImpl(const ExecuteNetworkParams& params, { outputDataContainers.push_back(std::vector<uint8_t>(model.GetOutputSize(i))); } + else if (params.m_OutputTypes[i].compare("qsymms8") == 0) + { + outputDataContainers.push_back(std::vector<int8_t>(model.GetOutputSize(i))); + } else { ARMNN_LOG(fatal) << "Unsupported tensor data type \"" << params.m_OutputTypes[i] << "\". "; @@ -503,8 +501,19 @@ int main(int argc, const char* argv[]) } else if(modelFormat.find("tflite") != std::string::npos) { - - if (ProgramOptions.m_ExNetParams.m_EnableDelegate) + if (ProgramOptions.m_ExNetParams.m_TfLiteExecutor == ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteParser) + { + #if defined(ARMNN_TF_LITE_PARSER) + return MainImpl<armnnTfLiteParser::ITfLiteParser, float>(ProgramOptions.m_ExNetParams, runtime); + #else + ARMNN_LOG(fatal) << "Not built with Tensorflow-Lite parser support."; + return EXIT_FAILURE; + #endif + } + else if (ProgramOptions.m_ExNetParams.m_TfLiteExecutor == + ExecuteNetworkParams::TfLiteExecutor::ArmNNTfLiteDelegate || + ProgramOptions.m_ExNetParams.m_TfLiteExecutor == + ExecuteNetworkParams::TfLiteExecutor::TfliteInterpreter) { #if defined(ARMNN_TF_LITE_DELEGATE) return TfLiteDelegateMainImpl(ProgramOptions.m_ExNetParams, runtime); @@ -513,12 +522,6 @@ int main(int argc, const char* argv[]) return EXIT_FAILURE; #endif } - #if defined(ARMNN_TF_LITE_PARSER) - return MainImpl<armnnTfLiteParser::ITfLiteParser, float>(ProgramOptions.m_ExNetParams, runtime); - #else - ARMNN_LOG(fatal) << "Not built with Tensorflow-Lite parser support."; - return EXIT_FAILURE; - #endif } else { |