// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #pragma once #include "ArmnnDriver.hpp" #include "ArmnnDriverImpl.hpp" #include "RequestThread.hpp" #include #include #include #include namespace armnn_driver { using armnnExecuteCallback_1_0 = std::function; struct ArmnnCallback_1_0 { armnnExecuteCallback_1_0 callback; }; struct ExecutionContext_1_0 {}; using CallbackContext_1_0 = CallbackContext; template class ArmnnPreparedModel : public V1_0::IPreparedModel { public: using HalModel = typename HalVersion::Model; ArmnnPreparedModel(armnn::NetworkId networkId, armnn::IRuntime* runtime, const HalModel& model, const std::string& requestInputsAndOutputsDumpDir, const bool gpuProfilingEnabled); virtual ~ArmnnPreparedModel(); virtual Return execute(const V1_0::Request& request, const ::android::sp& callback) override; /// execute the graph prepared from the request void ExecuteGraph(std::shared_ptr>& pMemPools, armnn::InputTensors& inputTensors, armnn::OutputTensors& outputTensors, CallbackContext_1_0 callback); /// Executes this model with dummy inputs (e.g. all zeroes). /// \return false on failure, otherwise true bool ExecuteWithDummyInputs(); private: template void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings); armnn::NetworkId m_NetworkId; armnn::IRuntime* m_Runtime; HalModel m_Model; // There must be a single RequestThread for all ArmnnPreparedModel objects to ensure serial execution of workloads // It is specific to this class, so it is declared as static here static RequestThread m_RequestThread; uint32_t m_RequestCount; const std::string& m_RequestInputsAndOutputsDumpDir; const bool m_GpuProfilingEnabled; }; }