diff options
Diffstat (limited to 'src/armnn/LoadedNetwork.cpp')
| -rw-r--r-- | src/armnn/LoadedNetwork.cpp | 117 |
1 files changed, 93 insertions, 24 deletions
diff --git a/src/armnn/LoadedNetwork.cpp b/src/armnn/LoadedNetwork.cpp index 91113c5ecb..d0bafc02d9 100644 --- a/src/armnn/LoadedNetwork.cpp +++ b/src/armnn/LoadedNetwork.cpp @@ -1,5 +1,5 @@ // -// Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved. +// Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // @@ -60,7 +60,10 @@ void AddLayerStructure(std::unique_ptr<TimelineUtilityMethods>& timelineUtils, for (auto&& input : layer.GetInputSlots()) { const IOutputSlot* source = input.GetConnectedOutputSlot(); - ARMNN_ASSERT(source != NULL); + if (!source) + { + throw armnn::NullPointerException("Null source found on input to layer \"" + layerName + "\"."); + } timelineUtils->CreateConnectionRelationship(ProfilingRelationshipType::RetentionLink, source->GetOwningLayerGuid(), layer.GetGuid()); @@ -643,7 +646,10 @@ void LoadedNetwork::AllocateAndExecuteConstantWorkloadsAsync() { const auto& outSlot = layer->GetOutputSlots()[0]; const auto factoryId = outSlot.GetTensorHandleFactoryId(); - ARMNN_ASSERT(factoryId != ITensorHandleFactory::LegacyFactoryId); + if (factoryId == ITensorHandleFactory::LegacyFactoryId) + { + throw armnn::Exception("factoryId must not be of type \"Legacy\"."); + } auto& workloadFactory = GetWorkloadFactory(*layer); layer->CreateTensorHandles(m_TensorHandleFactoryRegistry, workloadFactory); @@ -710,7 +716,11 @@ TensorInfo LoadedNetwork::GetInputTensorInfo(LayerBindingId layerId) const { for (auto&& inputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetInputLayers()) { - ARMNN_ASSERT_MSG(inputLayer->GetNumOutputSlots() == 1, "Input layer should have exactly 1 output slot"); + if (inputLayer->GetNumOutputSlots() != 1) + { + throw armnn::GraphValidationException("Input layer should have exactly 1 output slot"); + } + if (inputLayer->GetBindingId() == layerId) { return inputLayer->GetOutputSlot(0).GetTensorInfo(); @@ -724,8 +734,16 @@ TensorInfo LoadedNetwork::GetOutputTensorInfo(LayerBindingId layerId) const { for (auto&& outputLayer : m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().GetOutputLayers()) { - ARMNN_ASSERT_MSG(outputLayer->GetNumInputSlots() == 1, "Output layer should have exactly 1 input slot"); - ARMNN_ASSERT_MSG(outputLayer->GetInputSlot(0).GetConnection(), "Input slot on Output layer must be connected"); + if (outputLayer->GetNumInputSlots() != 1) + { + throw armnn::GraphValidationException("Output layer should have exactly 1 input slot"); + } + + if (!outputLayer->GetInputSlot(0).GetConnection()) + { + throw armnn::GraphValidationException("Input slot on Output layer must be connected"); + } + if (outputLayer->GetBindingId() == layerId) { return outputLayer->GetInputSlot(0).GetTensorInfo(); @@ -750,7 +768,10 @@ const IWorkloadFactory& LoadedNetwork::GetWorkloadFactory(const Layer& layer) co workloadFactory = it->second.get(); - ARMNN_ASSERT_MSG(workloadFactory, "No workload factory"); + if (!workloadFactory) + { + throw armnn::NullPointerException("No workload factory"); + } return *workloadFactory; } @@ -962,14 +983,22 @@ Status LoadedNetwork::EnqueueWorkload(const InputTensors& inputTensors, m_IsOutputImported[outputIndex] = true; } - ARMNN_ASSERT_MSG(inputTensorHandle != nullptr, "Data should have been allocated."); + if (!inputTensorHandle) + { + throw armnn::NullPointerException("Data should have been allocated."); + } + MemSyncQueueDescriptor syncDesc; syncDesc.m_Inputs.push_back(inputTensorHandle); WorkloadInfo info; - info.m_InputTensorInfos.push_back( - outputLayer->GetInputSlot(0).GetTensorInfo()); + info.m_InputTensorInfos.push_back(outputLayer->GetInputSlot(0).GetTensorInfo()); + auto syncWorkload = std::make_unique<SyncMemGenericWorkload>(syncDesc, info); - ARMNN_ASSERT_MSG(syncWorkload, "No sync workload created"); + if (!syncWorkload) + { + throw armnn::NullPointerException("No sync workload created"); + } + m_OutputQueue.push_back(std::move(syncWorkload)); importedOutputIdIndex++; } @@ -1058,12 +1087,20 @@ void LoadedNetwork::EnqueueInput(const BindableLayer& layer, ITensorHandle* tens inputQueueDescriptor.m_Inputs.push_back(tensorHandle); info.m_InputTensorInfos.push_back(tensorInfo); - ARMNN_ASSERT_MSG(layer.GetNumOutputSlots() == 1, "Can only handle Input Layer with one output"); + if (layer.GetNumOutputSlots() != 1) + { + throw armnn::GraphValidationException("Can only handle Input Layer with one output"); + } + const OutputHandler& handler = layer.GetOutputHandler(); const TensorInfo& outputTensorInfo = handler.GetTensorInfo(); ITensorHandle* outputTensorHandle = handler.GetData(); - ARMNN_ASSERT_MSG(outputTensorHandle != nullptr, - "Data should have been allocated."); + + if (!outputTensorHandle) + { + throw armnn::NullPointerException("Data should have been allocated."); + } + inputQueueDescriptor.m_Outputs.push_back(outputTensorHandle); info.m_OutputTensorInfos.push_back(outputTensorInfo); @@ -1090,7 +1127,10 @@ void LoadedNetwork::EnqueueInput(const BindableLayer& layer, ITensorHandle* tens // Create a mem copy workload for input since we did not import std::unique_ptr<IWorkload> inputWorkload = std::make_unique<CopyMemGenericWorkload>(inputQueueDescriptor, info); - ARMNN_ASSERT_MSG(inputWorkload, "No input workload created"); + if (!inputWorkload) + { + throw armnn::NullPointerException("No input workload created"); + } std::unique_ptr<TimelineUtilityMethods> timelineUtils = TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService); @@ -1123,14 +1163,20 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten outputQueueDescriptor.m_Outputs.push_back(tensorHandle); info.m_OutputTensorInfos.push_back(tensorInfo); - ARMNN_ASSERT_MSG(layer.GetNumInputSlots() == 1, "Output Layer should have exactly one input."); + if (layer.GetNumInputSlots() != 1) + { + throw armnn::GraphValidationException("Output Layer should have exactly one input."); + } // Gets the output handler from the previous node. const OutputHandler& outputHandler = layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetOutputHandler(); const TensorInfo& inputTensorInfo = outputHandler.GetTensorInfo(); ITensorHandle* inputTensorHandle = outputHandler.GetData(); - ARMNN_ASSERT_MSG(inputTensorHandle != nullptr, "Data should have been allocated."); + if (!inputTensorHandle) + { + throw armnn::NullPointerException("Data should have been allocated."); + } // Try import the output tensor. // Note: We can only import the output pointer if all of the following hold true: @@ -1160,7 +1206,10 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten syncDesc.m_Inputs.push_back(inputTensorHandle); info.m_InputTensorInfos.push_back(inputTensorInfo); auto syncWorkload = std::make_unique<SyncMemGenericWorkload>(syncDesc, info); - ARMNN_ASSERT_MSG(syncWorkload, "No sync workload created"); + if (!syncWorkload) + { + throw armnn::NullPointerException("No sync workload created"); + } m_OutputQueue.push_back(std::move(syncWorkload)); } else @@ -1178,7 +1227,10 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten std::unique_ptr<IWorkload> outputWorkload = std::make_unique<CopyMemGenericWorkload>(outputQueueDescriptor, info); - ARMNN_ASSERT_MSG(outputWorkload, "No output workload created"); + if (!outputWorkload) + { + throw armnn::NullPointerException("No output workload created"); + } std::unique_ptr<TimelineUtilityMethods> timelineUtils = TimelineUtilityMethods::GetTimelineUtils(*m_ProfilingService); @@ -1361,7 +1413,11 @@ void LoadedNetwork::EnqueueInput(const ConstTensor& inputTensor, ITensorHandle* // e) m_IsExportEnabled must be set to true void LoadedNetwork::ImportOutputTensor(const Tensor& outputTensor, ITensorHandle* outputTensorHandle) { - ARMNN_ASSERT_MSG(outputTensorHandle != nullptr, "Data should have been allocated."); + if (!outputTensorHandle) + { + throw armnn::NullPointerException("Data should have been allocated."); + } + MemorySourceFlags importFlags = outputTensorHandle->GetImportFlags(); if (CheckFlag(importFlags, m_NetworkProperties.m_OutputSource)) { @@ -1534,7 +1590,10 @@ std::vector<ImportedInputId> LoadedNetwork::ImportInputs(const InputTensors& inp const TensorInfo& tensorInfo = outputSlot.GetTensorInfo(); ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.GetFactory(factoryId); - ARMNN_ASSERT(handleFactory); + if (!handleFactory) + { + throw armnn::NullPointerException("handleFactory must not be null."); + } ImportedTensorHandlePin importedTensorHandlePin{layerBindingId, handleFactory->CreateTensorHandle(tensorInfo, false)}; @@ -1667,7 +1726,10 @@ std::vector<ImportedOutputId> LoadedNetwork::ImportOutputs(const OutputTensors& const TensorInfo& tensorInfo = inputSlot.GetTensorInfo(); ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.GetFactory(factoryId); - ARMNN_ASSERT(handleFactory); + if (!handleFactory) + { + throw armnn::NullPointerException("handleFactory must not be null."); + } ImportedTensorHandlePin importedTensorHandlePin{layerBindingId, handleFactory->CreateTensorHandle(tensorInfo, false)}; @@ -1987,7 +2049,10 @@ std::unique_ptr<IWorkingMemHandle> LoadedNetwork::CreateWorkingMemHandle(Network else { ITensorHandleFactory* handleFactory = m_TensorHandleFactoryRegistry.GetFactory(factoryId); - ARMNN_ASSERT(handleFactory); + if (!handleFactory) + { + throw armnn::NullPointerException("handleFactory must not be null."); + } return handleFactory->CreateTensorHandle(tensorInfo, false); } }; @@ -2098,7 +2163,11 @@ std::unique_ptr<IWorkingMemHandle> LoadedNetwork::CreateWorkingMemHandle(Network // so that the next tensor handle with a non overlapping lifetime can share its memory. for (auto& slot : layer->GetInputSlots()) { - ARMNN_ASSERT(slot.GetConnection()); + if (!slot.GetConnection()) + { + throw armnn::GraphValidationException("slot must be a valid input slot."); + } + auto outputSlot = slot.GetConnectedOutputSlot(); auto key = outputSlot->GetOwningLayer().GetGuid(); |