diff options
Diffstat (limited to 'src/armnn/LoadedNetwork.cpp')
-rw-r--r-- | src/armnn/LoadedNetwork.cpp | 28 |
1 files changed, 14 insertions, 14 deletions
diff --git a/src/armnn/LoadedNetwork.cpp b/src/armnn/LoadedNetwork.cpp index 9d181e535a..9da988b9e5 100644 --- a/src/armnn/LoadedNetwork.cpp +++ b/src/armnn/LoadedNetwork.cpp @@ -13,6 +13,7 @@ #include <armnn/BackendRegistry.hpp> #include <armnn/Logging.hpp> +#include <armnn/utility/Assert.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <armnn/backends/IMemoryManager.hpp> @@ -22,7 +23,6 @@ #include <LabelsAndEventClasses.hpp> #include <boost/polymorphic_cast.hpp> -#include <boost/assert.hpp> #include <boost/format.hpp> namespace armnn @@ -55,7 +55,7 @@ void AddLayerStructure(std::unique_ptr<TimelineUtilityMethods>& timelineUtils, for (auto&& input : layer.GetInputSlots()) { const IOutputSlot* source = input.GetConnectedOutputSlot(); - BOOST_ASSERT(source != NULL); + ARMNN_ASSERT(source != NULL); timelineUtils->CreateConnectionRelationship(ProfilingRelationshipType::RetentionLink, source->GetOwningLayerGuid(), layer.GetGuid()); @@ -304,7 +304,7 @@ TensorInfo LoadedNetwork::GetInputTensorInfo(LayerBindingId layerId) const { for (auto&& inputLayer : m_OptimizedNetwork->GetGraph().GetInputLayers()) { - BOOST_ASSERT_MSG(inputLayer->GetNumOutputSlots() == 1, "Input layer should have exactly 1 output slot"); + ARMNN_ASSERT_MSG(inputLayer->GetNumOutputSlots() == 1, "Input layer should have exactly 1 output slot"); if (inputLayer->GetBindingId() == layerId) { return inputLayer->GetOutputSlot(0).GetTensorInfo(); @@ -318,8 +318,8 @@ TensorInfo LoadedNetwork::GetOutputTensorInfo(LayerBindingId layerId) const { for (auto&& outputLayer : m_OptimizedNetwork->GetGraph().GetOutputLayers()) { - BOOST_ASSERT_MSG(outputLayer->GetNumInputSlots() == 1, "Output layer should have exactly 1 input slot"); - BOOST_ASSERT_MSG(outputLayer->GetInputSlot(0).GetConnection(), "Input slot on Output layer must be connected"); + 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->GetBindingId() == layerId) { return outputLayer->GetInputSlot(0).GetConnection()->GetTensorInfo(); @@ -346,10 +346,10 @@ const IWorkloadFactory& LoadedNetwork::GetWorkloadFactory(const Layer& layer) co workloadFactory = it->second.first.get(); - BOOST_ASSERT_MSG(workloadFactory, "No workload factory"); + ARMNN_ASSERT_MSG(workloadFactory, "No workload factory"); std::string reasonIfUnsupported; - BOOST_ASSERT_MSG(IWorkloadFactory::IsLayerSupported(layer, {}, reasonIfUnsupported), + ARMNN_ASSERT_MSG(IWorkloadFactory::IsLayerSupported(layer, {}, reasonIfUnsupported), "Factory does not support layer"); IgnoreUnused(reasonIfUnsupported); return *workloadFactory; @@ -540,11 +540,11 @@ void LoadedNetwork::EnqueueInput(const BindableLayer& layer, ITensorHandle* tens inputQueueDescriptor.m_Inputs.push_back(tensorHandle); info.m_InputTensorInfos.push_back(tensorInfo); - BOOST_ASSERT_MSG(layer.GetNumOutputSlots() == 1, "Can only handle Input Layer with one output"); + ARMNN_ASSERT_MSG(layer.GetNumOutputSlots() == 1, "Can only handle Input Layer with one output"); const OutputHandler& handler = layer.GetOutputHandler(); const TensorInfo& outputTensorInfo = handler.GetTensorInfo(); ITensorHandle* outputTensorHandle = handler.GetData(); - BOOST_ASSERT_MSG(outputTensorHandle != nullptr, + ARMNN_ASSERT_MSG(outputTensorHandle != nullptr, "Data should have been allocated."); inputQueueDescriptor.m_Outputs.push_back(outputTensorHandle); info.m_OutputTensorInfos.push_back(outputTensorInfo); @@ -574,7 +574,7 @@ 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); - BOOST_ASSERT_MSG(inputWorkload, "No input workload created"); + ARMNN_ASSERT_MSG(inputWorkload, "No input workload created"); std::unique_ptr<TimelineUtilityMethods> timelineUtils = TimelineUtilityMethods::GetTimelineUtils(m_ProfilingService); @@ -607,14 +607,14 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten outputQueueDescriptor.m_Outputs.push_back(tensorHandle); info.m_OutputTensorInfos.push_back(tensorInfo); - BOOST_ASSERT_MSG(layer.GetNumInputSlots() == 1, "Output Layer should have exactly one input."); + ARMNN_ASSERT_MSG(layer.GetNumInputSlots() == 1, "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(); - BOOST_ASSERT_MSG(inputTensorHandle != nullptr, "Data should have been allocated."); + ARMNN_ASSERT_MSG(inputTensorHandle != nullptr, "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: @@ -641,7 +641,7 @@ 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); - BOOST_ASSERT_MSG(syncWorkload, "No sync workload created"); + ARMNN_ASSERT_MSG(syncWorkload, "No sync workload created"); m_OutputQueue.push_back(move(syncWorkload)); } else @@ -667,7 +667,7 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten std::unique_ptr<IWorkload> outputWorkload = std::make_unique<CopyMemGenericWorkload>(outputQueueDescriptor, info); - BOOST_ASSERT_MSG(outputWorkload, "No output workload created"); + ARMNN_ASSERT_MSG(outputWorkload, "No output workload created"); std::unique_ptr<TimelineUtilityMethods> timelineUtils = TimelineUtilityMethods::GetTimelineUtils(m_ProfilingService); |