diff options
Diffstat (limited to 'samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp')
-rw-r--r-- | samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp | 38 |
1 files changed, 22 insertions, 16 deletions
diff --git a/samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp b/samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp index 9f1ef5475c..80558d84da 100644 --- a/samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp +++ b/samples/common/include/ArmnnUtils/ArmnnNetworkExecutor.hpp @@ -11,6 +11,7 @@ #include "armnnTfLiteParser/ITfLiteParser.hpp" #include "armnnUtils/DataLayoutIndexed.hpp" #include <armnn/Logging.hpp> +#include "Profiling.hpp" #include <string> #include <vector> @@ -21,7 +22,7 @@ namespace common * @brief Used to load in a network through ArmNN and run inference on it against a given backend. * */ -template <class Tout> +template <typename Tout> class ArmnnNetworkExecutor { private: @@ -31,7 +32,7 @@ private: armnn::InputTensors m_InputTensors; armnn::OutputTensors m_OutputTensors; std::vector<armnnTfLiteParser::BindingPointInfo> m_outputBindingInfo; - + Profiling m_profiling; std::vector<std::string> m_outputLayerNamesList; armnnTfLiteParser::BindingPointInfo m_inputBindingInfo; @@ -59,7 +60,8 @@ public: * * @param[in] backends - The list of preferred backends to run inference on */ ArmnnNetworkExecutor(std::string& modelPath, - std::vector<armnn::BackendId>& backends); + std::vector<armnn::BackendId>& backends, + bool isProfilingEnabled = false); /** * @brief Returns the aspect ratio of the associated model in the order of width, height. @@ -87,12 +89,15 @@ public: }; -template <class Tout> +template <typename Tout> ArmnnNetworkExecutor<Tout>::ArmnnNetworkExecutor(std::string& modelPath, - std::vector<armnn::BackendId>& preferredBackends) - : m_Runtime(armnn::IRuntime::Create(armnn::IRuntime::CreationOptions())) + std::vector<armnn::BackendId>& preferredBackends, + bool isProfilingEnabled): + m_profiling(isProfilingEnabled), + m_Runtime(armnn::IRuntime::Create(armnn::IRuntime::CreationOptions())) { // Import the TensorFlow lite model. + m_profiling.ProfilingStart(); armnnTfLiteParser::ITfLiteParserPtr parser = armnnTfLiteParser::ITfLiteParser::Create(); armnn::INetworkPtr network = parser->CreateNetworkFromBinaryFile(modelPath.c_str()); @@ -151,16 +156,16 @@ ArmnnNetworkExecutor<Tout>::ArmnnNetworkExecutor(std::string& modelPath, )); } } - + m_profiling.ProfilingStopAndPrintUs("ArmnnNetworkExecutor time"); } -template <class Tout> +template <typename Tout> armnn::DataType ArmnnNetworkExecutor<Tout>::GetInputDataType() const { return m_inputBindingInfo.second.GetDataType(); } -template <class Tout> +template <typename Tout> void ArmnnNetworkExecutor<Tout>::PrepareTensors(const void* inputData, const size_t dataBytes) { assert(m_inputBindingInfo.second.GetNumBytes() >= dataBytes); @@ -168,9 +173,10 @@ void ArmnnNetworkExecutor<Tout>::PrepareTensors(const void* inputData, const siz m_InputTensors = {{ m_inputBindingInfo.first, armnn::ConstTensor(m_inputBindingInfo.second, inputData)}}; } -template <class Tout> +template <typename Tout> bool ArmnnNetworkExecutor<Tout>::Run(const void* inputData, const size_t dataBytes, InferenceResults<Tout>& outResults) { + m_profiling.ProfilingStart(); /* Prepare tensors if they are not ready */ ARMNN_LOG(debug) << "Preparing tensors..."; this->PrepareTensors(inputData, dataBytes); @@ -190,37 +196,37 @@ bool ArmnnNetworkExecutor<Tout>::Run(const void* inputData, const size_t dataByt outResults.reserve(m_outputLayerNamesList.size()); outResults = m_OutputBuffer; - + m_profiling.ProfilingStopAndPrintUs("Total inference time"); return (armnn::Status::Success == ret); } -template <class Tout> +template <typename Tout> float ArmnnNetworkExecutor<Tout>::GetQuantizationScale() { return this->m_inputBindingInfo.second.GetQuantizationScale(); } -template <class Tout> +template <typename Tout> int ArmnnNetworkExecutor<Tout>::GetQuantizationOffset() { return this->m_inputBindingInfo.second.GetQuantizationOffset(); } -template <class Tout> +template <typename Tout> float ArmnnNetworkExecutor<Tout>::GetOutputQuantizationScale(int tensorIndex) { assert(this->m_outputLayerNamesList.size() > tensorIndex); return this->m_outputBindingInfo[tensorIndex].second.GetQuantizationScale(); } -template <class Tout> +template <typename Tout> int ArmnnNetworkExecutor<Tout>::GetOutputQuantizationOffset(int tensorIndex) { assert(this->m_outputLayerNamesList.size() > tensorIndex); return this->m_outputBindingInfo[tensorIndex].second.GetQuantizationOffset(); } -template <class Tout> +template <typename Tout> Size ArmnnNetworkExecutor<Tout>::GetImageAspectRatio() { const auto shape = m_inputBindingInfo.second.GetShape(); |