| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| #pragma once |
| |
| #include "Network.hpp" |
| #include "LayerFwd.hpp" |
| #include "Profiling.hpp" |
| |
| #include <armnn/Tensor.hpp> |
| #include <armnn/backends/IBackendInternal.hpp> |
| #include <armnn/backends/IMemoryOptimizerStrategy.hpp> |
| #include <backendsCommon/TensorHandleFactoryRegistry.hpp> |
| #include <armnn/backends/Workload.hpp> |
| #include <armnn/backends/WorkloadFactory.hpp> |
| #include <backendsCommon/DefaultAllocator.hpp> |
| #include <backendsCommon/MemoryManager.hpp> |
| #include <backendsCommon/memoryOptimizerStrategyLibrary/strategies/SingleAxisPriorityList.hpp> |
| |
| |
| #include <ProfilingService.hpp> |
| #include <TimelineUtilityMethods.hpp> |
| |
| #include <common/include/LabelsAndEventClasses.hpp> |
| |
| #include <mutex> |
| #include <condition_variable> |
| #include <unordered_map> |
| |
| namespace cl |
| { |
| class Context; |
| class CommandQueue; |
| class Device; |
| } |
| |
| namespace armnn |
| { |
| |
| class LoadedNetwork |
| { |
| public: |
| using WorkloadQueue = std::vector<std::unique_ptr<IWorkload>>; |
| |
| ~LoadedNetwork() |
| { |
| FreeWorkingMemory(); |
| } |
| |
| /// Create a new unique WorkingMemHandle object. Create multiple handles if you wish to have |
| /// overlapped Execution by calling this function from different threads. |
| std::unique_ptr<IWorkingMemHandle> CreateWorkingMemHandle(NetworkId networkId); |
| |
| TensorInfo GetInputTensorInfo(LayerBindingId layerId) const; |
| TensorInfo GetOutputTensorInfo(LayerBindingId layerId) const; |
| |
| std::vector<ImportedInputId> ImportInputs(const InputTensors& inputTensors, |
| MemorySource forceImportMemorySource = MemorySource::Undefined); |
| std::vector<ImportedOutputId> ImportOutputs(const OutputTensors& outputTensors, |
| MemorySource forceImportMemorySource = MemorySource::Undefined); |
| |
| void ClearImportedInputs(const std::vector<ImportedInputId> inputIds); |
| void ClearImportedOutputs(const std::vector<ImportedOutputId> outputIds); |
| |
| /// Single thread execution of the loaded network |
| Status EnqueueWorkload(const InputTensors& inputTensors, const OutputTensors& outputTensors, |
| std::vector<ImportedInputId> preImportedInputIds = {}, |
| std::vector<ImportedOutputId> preImportedOutputIds = {}); |
| |
| /// Thread safe execution of the loaded network |
| Status Execute(const InputTensors& inputTensors, |
| const OutputTensors& outputTensors, |
| IWorkingMemHandle& workingMemHandle, |
| std::vector<ImportedInputId> preImportedInputs = {}, |
| std::vector<ImportedOutputId> preImportedOutputs = {}); |
| |
| static std::unique_ptr<LoadedNetwork> MakeLoadedNetwork(std::unique_ptr<IOptimizedNetwork> net, |
| std::string& errorMessage, |
| const INetworkProperties& networkProperties, |
| arm::pipe::ProfilingService& profilingService); |
| |
| // NOTE we return by reference as the purpose of this method is only to provide |
| // access to the private m_Profiler and in theory we should not need to increment |
| // the shared_ptr's reference counter |
| const std::shared_ptr<IProfiler>& GetProfiler() const { return m_OptimizedNetwork->GetProfiler(); } |
| |
| void FreeWorkingMemory(); |
| |
| void RegisterDebugCallback(const DebugCallbackFunction& func); |
| |
| void SendNetworkStructure(); |
| |
| bool IsAsyncEnabled() |
| { |
| return m_NetworkProperties.m_AsyncEnabled; |
| } |
| |
| arm::pipe::ProfilingGuid GetNetworkGuid(); |
| |
| private: |
| |
| |
| void AllocateWorkingMemory(std::lock_guard<std::mutex>& lock); |
| void AllocateAndExecuteConstantWorkloads(); |
| void AllocateAndExecuteConstantWorkloadsAsync(); |
| |
| std::unordered_map<LayerGuid, std::unique_ptr<IWorkload>> m_ConstantWorkloads; |
| std::unordered_map<LayerGuid, ITensorHandle*> m_ConstantTensorHandles; |
| |
| std::unique_ptr<IMemoryOptimizerStrategy> m_ConstantStrategy = std::make_unique<SingleAxisPriorityList>(); |
| |
| LoadedNetwork(std::unique_ptr<IOptimizedNetwork> net, |
| const INetworkProperties& networkProperties, |
| arm::pipe::ProfilingService& profilingService); |
| |
| void EnqueueInput(const BindableLayer& layer, ITensorHandle* tensorHandle, const TensorInfo& tensorInfo); |
| |
| void EnqueueOutput(const BindableLayer& layer, ITensorHandle* tensorHandle, const TensorInfo& tensorInfo); |
| |
| void EnqueueInput(const ConstTensor& inputTensor, ITensorHandle* inputTensorHandle); |
| |
| void ImportOutputTensor(const Tensor& outputTensor, ITensorHandle* outputTensorHandle); |
| |
| bool Execute(std::unique_ptr<arm::pipe::TimelineUtilityMethods>& timelineUtils, |
| arm::pipe::ProfilingGuid inferenceGuid); |
| |
| const IWorkloadFactory& GetWorkloadFactory(const Layer& layer) const; |
| |
| inline LayerBindingId ValidateImportedInputID(ImportedInputId id); |
| inline LayerBindingId ValidateImportedOutputID(ImportedOutputId id); |
| |
| void CreateMemoryProfile(); |
| void CreateMemoryProfileAsync(); |
| |
| std::unique_ptr<MemoryManager> CreateExternalMemoryManger( |
| std::vector<std::pair<std::shared_ptr<TensorMemory>, MemorySource>>& tensorMemory); |
| |
| using BackendPtrMap = std::unordered_map<BackendId, IBackendInternalUniquePtr>; |
| |
| BackendPtrMap m_Backends; |
| std::vector<IBackendInternal::IMemoryManagerSharedPtr> m_BackendMemoryMangers; |
| |
| using WorkloadFactoryMap = std::unordered_map<BackendId, IBackendInternal::IWorkloadFactoryPtr>; |
| WorkloadFactoryMap m_WorkloadFactories; |
| |
| std::unique_ptr<IOptimizedNetwork> m_OptimizedNetwork; |
| |
| WorkloadQueue m_InputQueue; |
| WorkloadQueue m_WorkloadQueue; |
| WorkloadQueue m_OutputQueue; |
| |
| mutable std::mutex m_WorkingMemMutex; |
| |
| bool m_IsWorkingMemAllocated = false; |
| |
| INetworkProperties m_NetworkProperties; |
| |
| TensorHandleFactoryRegistry m_TensorHandleFactoryRegistry; |
| |
| arm::pipe::ProfilingService& m_ProfilingService; |
| |
| struct ImportedTensorHandlePin |
| { |
| ImportedTensorHandlePin() |
| {} |
| |
| ImportedTensorHandlePin(LayerBindingId layerBindingId, |
| std::unique_ptr<ITensorHandle> tensorHandle) |
| : m_LayerBindingId(layerBindingId) |
| , m_TensorHandle(std::move(tensorHandle)) |
| {} |
| |
| ImportedTensorHandlePin(ImportedTensorHandlePin&&) = default; |
| |
| ~ImportedTensorHandlePin() |
| { |
| if (m_TensorHandle) |
| { |
| m_TensorHandle->Unimport(); |
| } |
| } |
| |
| LayerBindingId m_LayerBindingId; |
| std::unique_ptr<ITensorHandle> m_TensorHandle; |
| }; |
| |
| std::vector<ImportedTensorHandlePin> m_PreImportedInputHandles; |
| std::vector<ImportedTensorHandlePin> m_PreImportedOutputHandles; |
| |
| ImportedInputId m_CurImportedInputId = 0; |
| ImportedInputId m_CurImportedOutputId = 0; |
| |
| std::unordered_map<BackendId, std::vector<MemBlock>> m_MemBlockMap; |
| std::unordered_map<BackendId, std::vector<MemBin>> m_MemBinMap; |
| |
| std::vector<ITensorHandle*> m_Tensorhandles; |
| |
| std::vector<std::pair<std::shared_ptr<TensorMemory>, MemorySource>> m_TensorMemory; |
| |
| std::unique_ptr<MemoryManager> m_ExternalMemoryManager; |
| |
| std::unordered_map<BackendId, bool> m_SupportsExternallyManagedMemory; |
| |
| // A set of vectors to record the workload queue indexes and their corresponding Input/Output Slot indexes |
| // which are connected to Inputs and Outputs for the network. |
| struct WorkloadIndices |
| { |
| unsigned int m_WorkloadIndex; |
| unsigned int m_SlotIndex; |
| }; |
| |
| struct OutputWorkloadIndices |
| { |
| WorkloadIndices m_OutputSlotIndices; |
| std::vector<WorkloadIndices> m_InputSlotIndices; |
| }; |
| std::unordered_map<LayerBindingId, std::vector<WorkloadIndices>> m_InputWorkloadSlotPairs; |
| std::unordered_map<LayerBindingId, OutputWorkloadIndices> m_OutputWorkloadSlotPairs; |
| std::vector<bool> m_IsInputImported; |
| std::vector<bool> m_IsOutputImported; |
| |
| }; |
| |
| } |