diff options
Diffstat (limited to 'ArmnnPreparedModel.cpp')
| -rw-r--r-- | ArmnnPreparedModel.cpp | 96 |
1 files changed, 92 insertions, 4 deletions
diff --git a/ArmnnPreparedModel.cpp b/ArmnnPreparedModel.cpp index 60beac4f..978f3787 100644 --- a/ArmnnPreparedModel.cpp +++ b/ArmnnPreparedModel.cpp @@ -112,16 +112,23 @@ ArmnnPreparedModel<HalVersion>::ArmnnPreparedModel(armnn::NetworkId networkId, armnn::IRuntime* runtime, const HalModel& model, const std::string& requestInputsAndOutputsDumpDir, - const bool gpuProfilingEnabled) + const bool gpuProfilingEnabled, + const bool asyncModelExecutionEnabled) : m_NetworkId(networkId) , m_Runtime(runtime) , m_Model(model) , m_RequestCount(0) , m_RequestInputsAndOutputsDumpDir(requestInputsAndOutputsDumpDir) , m_GpuProfilingEnabled(gpuProfilingEnabled) + , m_AsyncModelExecutionEnabled(asyncModelExecutionEnabled) { // Enable profiling if required. m_Runtime->GetProfiler(m_NetworkId)->EnableProfiling(m_GpuProfilingEnabled); + + if (asyncModelExecutionEnabled) + { + m_WorkingMemHandle = m_Runtime->CreateWorkingMemHandle(networkId); + } } template<typename HalVersion> @@ -225,8 +232,6 @@ Return<V1_0::ErrorStatus> ArmnnPreparedModel<HalVersion>::execute( return V1_0::ErrorStatus::GENERAL_FAILURE; } - ALOGV("ArmnnPreparedModel::execute(...) before PostMsg"); - auto cb = [callback](V1_0::ErrorStatus errorStatus, std::string callingFunction) { NotifyCallbackAndCheck(callback, errorStatus, callingFunction); @@ -234,7 +239,17 @@ Return<V1_0::ErrorStatus> ArmnnPreparedModel<HalVersion>::execute( CallbackContext_1_0 armnnCb; armnnCb.callback = cb; + + if (m_AsyncModelExecutionEnabled) + { + ALOGV("ArmnnPreparedModel::execute(...) before ScheduleGraphForExecution"); + ScheduleGraphForExecution(pMemPools, pInputTensors, pOutputTensors, armnnCb); + ALOGV("ArmnnPreparedModel::execute(...) after ScheduleGraphForExecution"); + return V1_0::ErrorStatus::NONE; + } + // post the request for asynchronous execution + ALOGV("ArmnnPreparedModel::execute(...) before PostMsg"); m_RequestThread.PostMsg(this, pMemPools, pInputTensors, pOutputTensors, armnnCb); ALOGV("ArmnnPreparedModel::execute(...) after PostMsg"); return V1_0::ErrorStatus::NONE; // successfully queued @@ -254,7 +269,18 @@ void ArmnnPreparedModel<HalVersion>::ExecuteGraph( // run it try { - armnn::Status status = m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors); + armnn::Status status; + if (m_AsyncModelExecutionEnabled) + { + ALOGW("ArmnnPreparedModel::ExecuteGraph m_AsyncModelExecutionEnabled true"); + status = m_Runtime->Execute(*m_WorkingMemHandle, inputTensors, outputTensors); + } + else + { + ALOGW("ArmnnPreparedModel::ExecuteGraph m_AsyncModelExecutionEnabled false"); + status = m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors); + } + if (status != armnn::Status::Success) { ALOGW("EnqueueWorkload failed"); @@ -340,11 +366,73 @@ bool ArmnnPreparedModel<HalVersion>::ExecuteWithDummyInputs() return true; } +/// Schedule the graph prepared from the request for execution +template<typename HalVersion> +template<typename CallbackContext> +void ArmnnPreparedModel<HalVersion>::ScheduleGraphForExecution( + std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, + std::shared_ptr<armnn::InputTensors>& inputTensors, + std::shared_ptr<armnn::OutputTensors>& outputTensors, + CallbackContext callbackContext) +{ + ALOGV("ArmnnPreparedModel::ScheduleGraphForExecution(...)"); + + DumpTensorsIfRequired("Input", *inputTensors); + + + auto tpCb = std::make_shared< + ArmnnThreadPoolCallback<CallbackContext_1_0>>(this, + pMemPools, + inputTensors, + outputTensors, + callbackContext); + + m_Runtime->Schedule(m_NetworkId, + *tpCb->m_InputTensors, + *tpCb->m_OutputTensors, + armnn::QosExecPriority::High, + tpCb); + ALOGV("ArmnnPreparedModel::ScheduleGraphForExecution end"); +} + +template<typename HalVersion> +template <typename CallbackContext> +void ArmnnPreparedModel<HalVersion>::ArmnnThreadPoolCallback<CallbackContext>::Notify( + armnn::Status status, armnn::InferenceTimingPair timeTaken) +{ + armnn::IgnoreUnused(status, timeTaken); + ALOGV("ArmnnPreparedModel::ArmnnThreadPoolCallback_1_2 Notify"); + + m_Model->DumpTensorsIfRequired("Output", *m_OutputTensors); + + // Commit output buffers. + // Note that we update *all* pools, even if they aren't actually used as outputs - + // this is simpler and is what the CpuExecutor does. + for (android::nn::RunTimePoolInfo& pool : *m_MemPools) + { + // Type android::nn::RunTimePoolInfo has changed between Android P & Q and Android R, where + // update() has been removed and flush() added. + #if defined(ARMNN_ANDROID_R) || defined(ARMNN_ANDROID_S) // Use the new Android implementation. + pool.flush(); + #else + pool.update(); + #endif + } + + m_CallbackContext.callback(V1_0::ErrorStatus::NONE, "ArmnnPreparedModel::ArmnnThreadPoolCallback_1_2 Notify"); + return; +} + /// /// Class template specializations /// template class ArmnnPreparedModel<hal_1_0::HalPolicy>; +template void ArmnnPreparedModel<hal_1_0::HalPolicy>::ScheduleGraphForExecution<CallbackContext_1_0>( + std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, + std::shared_ptr<armnn::InputTensors>& inputTensors, + std::shared_ptr<armnn::OutputTensors>& outputTensors, + CallbackContext_1_0 callbackContext); #ifdef ARMNN_ANDROID_NN_V1_1 template class ArmnnPreparedModel<hal_1_1::HalPolicy>; |