diff options
Diffstat (limited to 'src/armnn/LoadedNetwork.cpp')
| -rw-r--r-- | src/armnn/LoadedNetwork.cpp | 50 |
1 files changed, 32 insertions, 18 deletions
diff --git a/src/armnn/LoadedNetwork.cpp b/src/armnn/LoadedNetwork.cpp index 5b64085869..1000eceda0 100644 --- a/src/armnn/LoadedNetwork.cpp +++ b/src/armnn/LoadedNetwork.cpp @@ -41,7 +41,8 @@ std::string ToErrorMessage(const char * prefix, const ExceptionType & error) } // anonymous std::unique_ptr<LoadedNetwork> LoadedNetwork::MakeLoadedNetwork(std::unique_ptr<OptimizedNetwork> net, - std::string & errorMessage) + std::string& errorMessage, + const INetworkProperties& networkProperties) { std::unique_ptr<LoadedNetwork> loadedNetwork; @@ -55,7 +56,7 @@ std::unique_ptr<LoadedNetwork> LoadedNetwork::MakeLoadedNetwork(std::unique_ptr< try { - loadedNetwork.reset(new LoadedNetwork(std::move(net))); + loadedNetwork.reset(new LoadedNetwork(std::move(net), networkProperties)); } catch (const armnn::RuntimeException& error) { @@ -73,8 +74,11 @@ std::unique_ptr<LoadedNetwork> LoadedNetwork::MakeLoadedNetwork(std::unique_ptr< return loadedNetwork; } -LoadedNetwork::LoadedNetwork(std::unique_ptr<OptimizedNetwork> net) - : m_OptimizedNetwork(std::move(net)) +LoadedNetwork::LoadedNetwork(std::unique_ptr<OptimizedNetwork> net, + const INetworkProperties& networkProperties) : + m_OptimizedNetwork(std::move(net)), + m_IsImportEnabled(networkProperties.m_ImportEnabled), + m_IsExportEnabled(networkProperties.m_ExportEnabled) { // Create a profiler and register it for the current thread. m_Profiler = std::make_shared<Profiler>(); @@ -392,7 +396,7 @@ void LoadedNetwork::EnqueueInput(const BindableLayer& layer, ITensorHandle* tens info.m_OutputTensorInfos.push_back(outputTensorInfo); MemorySourceFlags importFlags = outputTensorHandle->GetImportFlags(); - if (CheckFlag(importFlags, MemorySource::Malloc)) // Try import the input tensor + if (CheckFlag(importFlags, MemorySource::Malloc) && m_IsImportEnabled) // Try import the input tensor { // This assumes a CPU Tensor handle void* mem = tensorHandle->Map(false); @@ -402,13 +406,16 @@ void LoadedNetwork::EnqueueInput(const BindableLayer& layer, ITensorHandle* tens return; // No need for a workload since the import has been done. } tensorHandle->Unmap(); + throw MemoryImportException("EnqueueInput: Memory Import failed"); } + else + { + // Create a mem copy workload for input since we did not import + auto inputWorkload = std::make_unique<CopyMemGenericWorkload>(inputQueueDescriptor, info); - // Create a mem copy workload for input since we could not import - auto inputWorkload = std::make_unique<CopyMemGenericWorkload>(inputQueueDescriptor, info); - - BOOST_ASSERT_MSG(inputWorkload, "No input workload created"); - m_InputQueue.push_back(move(inputWorkload)); + BOOST_ASSERT_MSG(inputWorkload, "No input workload created"); + m_InputQueue.push_back(move(inputWorkload)); + } } void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* tensorHandle, const TensorInfo& tensorInfo) @@ -444,7 +451,8 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten // b) The tensor has zero padding // c) There is only one connection to the OutputSlot and it is to an OutputLayer. // d) The output pointer is allocated via malloc. (Other types will be supported in a later release) - if (layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetOwningLayer().GetType() != LayerType::Input) + if (layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetOwningLayer().GetType() != LayerType::Input + && m_IsExportEnabled) { if (layer.GetInputSlots()[0].GetConnectedOutputSlot()->GetNumConnections() == 1) { @@ -467,17 +475,23 @@ void LoadedNetwork::EnqueueOutput(const BindableLayer& layer, ITensorHandle* ten return; //No need to add the output workload below } + else + { + throw MemoryExportException("EnqueueOutput: Memory Export failed"); + } } } } + else + { + // If we got here then we couldn't import the memory, so add an output workload which performs a memcopy. + outputQueueDescriptor.m_Inputs.push_back(inputTensorHandle); + info.m_InputTensorInfos.push_back(inputTensorInfo); - // If we got here then we couldn't import the memory, so add an output workload which performs a memcopy. - outputQueueDescriptor.m_Inputs.push_back(inputTensorHandle); - info.m_InputTensorInfos.push_back(inputTensorInfo); - - auto outputWorkload = std::make_unique<CopyMemGenericWorkload>(outputQueueDescriptor, info); - BOOST_ASSERT_MSG(outputWorkload, "No output workload created"); - m_OutputQueue.push_back(move(outputWorkload)); + auto outputWorkload = std::make_unique<CopyMemGenericWorkload>(outputQueueDescriptor, info); + BOOST_ASSERT_MSG(outputWorkload, "No output workload created"); + m_OutputQueue.push_back(move(outputWorkload)); + } } void LoadedNetwork::AllocateWorkingMemory() |