| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include "ArmnnDriver.hpp" |
| #include "ArmnnDriverImpl.hpp" |
| #include "RequestThread.hpp" |
| #include "ModelToINetworkConverter.hpp" |
| |
| #include <NeuralNetworks.h> |
| #include <armnn/ArmNN.hpp> |
| #include <armnn/Threadpool.hpp> |
| |
| #include <string> |
| #include <vector> |
| |
| namespace armnn_driver |
| { |
| |
| using CallbackAsync_1_2 = std::function< |
| void(V1_0::ErrorStatus errorStatus, |
| std::vector<::android::hardware::neuralnetworks::V1_2::OutputShape> outputShapes, |
| const ::android::hardware::neuralnetworks::V1_2::Timing& timing, |
| std::string callingFunction)>; |
| |
| struct ExecutionContext_1_2 |
| { |
| ::android::hardware::neuralnetworks::V1_2::MeasureTiming measureTimings = |
| ::android::hardware::neuralnetworks::V1_2::MeasureTiming::NO; |
| TimePoint driverStart; |
| }; |
| |
| using CallbackContext_1_2 = CallbackContext<CallbackAsync_1_2, ExecutionContext_1_2>; |
| |
| template <typename HalVersion> |
| class ArmnnPreparedModel_1_2 : public V1_2::IPreparedModel |
| { |
| public: |
| using HalModel = typename V1_2::Model; |
| |
| ArmnnPreparedModel_1_2(armnn::NetworkId networkId, |
| armnn::IRuntime* runtime, |
| const HalModel& model, |
| const std::string& requestInputsAndOutputsDumpDir, |
| const bool gpuProfilingEnabled, |
| const bool asyncModelExecutionEnabled = false, |
| const unsigned int numberOfThreads = 1, |
| const bool importEnabled = false, |
| const bool exportEnabled = false); |
| |
| ArmnnPreparedModel_1_2(armnn::NetworkId networkId, |
| armnn::IRuntime* runtime, |
| const std::string& requestInputsAndOutputsDumpDir, |
| const bool gpuProfilingEnabled, |
| const bool asyncModelExecutionEnabled = false, |
| const unsigned int numberOfThreads = 1, |
| const bool importEnabled = false, |
| const bool exportEnabled = false, |
| const bool preparedFromCache = false); |
| |
| virtual ~ArmnnPreparedModel_1_2(); |
| |
| virtual Return<V1_0::ErrorStatus> execute(const V1_0::Request& request, |
| const ::android::sp<V1_0::IExecutionCallback>& callback) override; |
| |
| virtual Return<V1_0::ErrorStatus> execute_1_2(const V1_0::Request& request, V1_2::MeasureTiming measure, |
| const ::android::sp<V1_2::IExecutionCallback>& callback) override; |
| |
| virtual Return<void> executeSynchronously(const V1_0::Request &request, |
| V1_2::MeasureTiming measure, |
| V1_2::IPreparedModel::executeSynchronously_cb cb) override; |
| |
| virtual Return<void> configureExecutionBurst( |
| const ::android::sp<V1_2::IBurstCallback>& callback, |
| const android::hardware::MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel, |
| const android::hardware::MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel, |
| configureExecutionBurst_cb cb) override; |
| |
| /// execute the graph prepared from the request |
| template<typename CallbackContext> |
| bool ExecuteGraph(std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| armnn::InputTensors& inputTensors, |
| armnn::OutputTensors& outputTensors, |
| CallbackContext callback); |
| |
| /// Executes this model with dummy inputs (e.g. all zeroes). |
| /// \return false on failure, otherwise true |
| bool ExecuteWithDummyInputs(unsigned int numInputs, unsigned int numOutputs); |
| |
| private: |
| |
| template<typename CallbackContext> |
| class ArmnnThreadPoolCallback_1_2 : public armnn::IAsyncExecutionCallback |
| { |
| public: |
| ArmnnThreadPoolCallback_1_2(ArmnnPreparedModel_1_2<HalVersion>* model, |
| std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| std::vector<V1_2::OutputShape> outputShapes, |
| std::shared_ptr<armnn::InputTensors>& inputTensors, |
| std::shared_ptr<armnn::OutputTensors>& outputTensors, |
| CallbackContext callbackContext) : |
| m_Model(model), |
| m_MemPools(pMemPools), |
| m_OutputShapes(outputShapes), |
| m_InputTensors(inputTensors), |
| m_OutputTensors(outputTensors), |
| m_CallbackContext(callbackContext) |
| {} |
| |
| void Notify(armnn::Status status, armnn::InferenceTimingPair timeTaken) override; |
| |
| ArmnnPreparedModel_1_2<HalVersion>* m_Model; |
| std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>> m_MemPools; |
| std::vector<V1_2::OutputShape> m_OutputShapes; |
| std::shared_ptr<armnn::InputTensors> m_InputTensors; |
| std::shared_ptr<armnn::OutputTensors> m_OutputTensors; |
| CallbackContext m_CallbackContext; |
| }; |
| |
| Return<V1_0::ErrorStatus> Execute(const V1_0::Request& request, |
| V1_2::MeasureTiming measureTiming, |
| CallbackAsync_1_2 callback); |
| |
| Return<V1_0::ErrorStatus> PrepareMemoryForInputs( |
| armnn::InputTensors& inputs, |
| const V1_0::Request& request, |
| const std::vector<android::nn::RunTimePoolInfo>& memPools); |
| |
| Return<V1_0::ErrorStatus> PrepareMemoryForOutputs( |
| armnn::OutputTensors& outputs, |
| std::vector<V1_2::OutputShape> &outputShapes, |
| const V1_0::Request& request, |
| const std::vector<android::nn::RunTimePoolInfo>& memPools); |
| |
| Return <V1_0::ErrorStatus> PrepareMemoryForIO( |
| armnn::InputTensors& inputs, |
| armnn::OutputTensors& outputs, |
| std::vector<android::nn::RunTimePoolInfo>& memPools, |
| const V1_0::Request& request, |
| CallbackAsync_1_2 callback); |
| |
| template <typename TensorBindingCollection> |
| void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings); |
| |
| /// schedule the graph prepared from the request for execution |
| template<typename CallbackContext> |
| void ScheduleGraphForExecution( |
| std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| std::shared_ptr<armnn::InputTensors>& inputTensors, |
| std::shared_ptr<armnn::OutputTensors>& outputTensors, |
| CallbackContext m_CallbackContext); |
| |
| armnn::NetworkId m_NetworkId; |
| armnn::IRuntime* m_Runtime; |
| V1_2::Model 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<ArmnnPreparedModel_1_2, |
| HalVersion, |
| CallbackContext_1_2> m_RequestThread; |
| uint32_t m_RequestCount; |
| const std::string& m_RequestInputsAndOutputsDumpDir; |
| const bool m_GpuProfilingEnabled; |
| // Static to allow sharing of threadpool between ArmnnPreparedModel instances |
| static std::unique_ptr<armnn::Threadpool> m_Threadpool; |
| std::shared_ptr<IWorkingMemHandle> m_WorkingMemHandle; |
| const bool m_AsyncModelExecutionEnabled; |
| const bool m_EnableImport; |
| const bool m_EnableExport; |
| const bool m_PreparedFromCache; |
| }; |
| |
| } |