diff options
author | Jan Eilers <jan.eilers@arm.com> | 2020-04-02 13:56:54 +0100 |
---|---|---|
committer | Jan Eilers <jan.eilers@arm.com> | 2020-04-10 10:11:11 +0100 |
commit | bb446e576e120512d5752a5d6dc1ddc636f563ba (patch) | |
tree | 147d0b5f2886af208199a24704afd845a4825bf8 /src/backends | |
parent | e5d0b93b152a26faf93538eb719d03e5b477d670 (diff) | |
download | armnn-bb446e576e120512d5752a5d6dc1ddc636f563ba.tar.gz |
IVGCVSW-4483 Remove boost::polymorphic_downcast
* exchange boost::polymorphic_downcast with armnn::PolymorphicDowncast
* remove unnecessary includes of boost::polymorphic_downcast
Signed-off-by: Jan Eilers <jan.eilers@arm.com>
Change-Id: Ie603fb82860fe05fee547dc78073230cc62b2e1f
Diffstat (limited to 'src/backends')
53 files changed, 330 insertions, 292 deletions
diff --git a/src/backends/aclCommon/BaseMemoryManager.cpp b/src/backends/aclCommon/BaseMemoryManager.cpp index b43eaf8da3..aaadc9479a 100644 --- a/src/backends/aclCommon/BaseMemoryManager.cpp +++ b/src/backends/aclCommon/BaseMemoryManager.cpp @@ -10,7 +10,6 @@ #include "arm_compute/runtime/OffsetLifetimeManager.h" #endif -#include <boost/polymorphic_cast.hpp> namespace armnn { diff --git a/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp b/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp index 83cec2a746..b14e148287 100644 --- a/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp +++ b/src/backends/aclCommon/test/CreateWorkloadClNeon.hpp @@ -6,6 +6,7 @@ #include <test/CreateWorkload.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/MemCopyWorkload.hpp> #include <reference/RefWorkloadFactory.hpp> #include <reference/RefTensorHandle.hpp> @@ -93,8 +94,8 @@ void CreateMemCopyWorkloads(IWorkloadFactory& factory) MemCopyQueueDescriptor queueDescriptor1 = workload1->GetData(); BOOST_TEST(queueDescriptor1.m_Inputs.size() == 1); BOOST_TEST(queueDescriptor1.m_Outputs.size() == 1); - auto inputHandle1 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor1.m_Inputs[0]); - auto outputHandle1 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor1.m_Outputs[0]); + auto inputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor1.m_Inputs[0]); + auto outputHandle1 = PolymorphicDowncast<IComputeTensorHandle*>(queueDescriptor1.m_Outputs[0]); BOOST_TEST((inputHandle1->GetTensorInfo() == TensorInfo({2, 3}, DataType::Float32))); BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(outputHandle1, {2, 3})); @@ -102,8 +103,8 @@ void CreateMemCopyWorkloads(IWorkloadFactory& factory) MemCopyQueueDescriptor queueDescriptor2 = workload2->GetData(); BOOST_TEST(queueDescriptor2.m_Inputs.size() == 1); BOOST_TEST(queueDescriptor2.m_Outputs.size() == 1); - auto inputHandle2 = boost::polymorphic_downcast<IComputeTensorHandle*>(queueDescriptor2.m_Inputs[0]); - auto outputHandle2 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor2.m_Outputs[0]); + auto inputHandle2 = PolymorphicDowncast<IComputeTensorHandle*>(queueDescriptor2.m_Inputs[0]); + auto outputHandle2 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor2.m_Outputs[0]); BOOST_TEST(CompareTensorHandleShape<IComputeTensorHandle>(inputHandle2, {2, 3})); BOOST_TEST((outputHandle2->GetTensorInfo() == TensorInfo({2, 3}, DataType::Float32))); } diff --git a/src/backends/backendsCommon/MemCopyWorkload.cpp b/src/backends/backendsCommon/MemCopyWorkload.cpp index 572c0fcc57..c1aa79cb10 100644 --- a/src/backends/backendsCommon/MemCopyWorkload.cpp +++ b/src/backends/backendsCommon/MemCopyWorkload.cpp @@ -8,7 +8,7 @@ #include <backendsCommon/MemCopyWorkload.hpp> #include <backendsCommon/CpuTensorHandle.hpp> -#include <boost/cast.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <cstring> @@ -27,9 +27,9 @@ void GatherTensorHandlePairs(const MemCopyQueueDescriptor& descriptor, for (unsigned int i = 0; i < numInputs; ++i) { - SrcTensorHandleType* const srcTensorHandle = boost::polymorphic_downcast<SrcTensorHandleType*>( + SrcTensorHandleType* const srcTensorHandle = PolymorphicDowncast<SrcTensorHandleType*>( descriptor.m_Inputs[i]); - DstTensorHandleType* const dstTensorHandle = boost::polymorphic_downcast<DstTensorHandleType*>( + DstTensorHandleType* const dstTensorHandle = PolymorphicDowncast<DstTensorHandleType*>( descriptor.m_Outputs[i]); tensorHandlePairs.emplace_back(srcTensorHandle, dstTensorHandle); diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp index a7e8576668..c55c70a1f7 100644 --- a/src/backends/backendsCommon/WorkloadFactory.cpp +++ b/src/backends/backendsCommon/WorkloadFactory.cpp @@ -10,6 +10,7 @@ #include <armnn/LayerSupport.hpp> #include <armnn/ILayerSupport.hpp> #include <armnn/BackendRegistry.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/WorkloadFactory.hpp> #include <armnn/backends/IBackendInternal.hpp> @@ -18,7 +19,6 @@ #include <backendsCommon/test/WorkloadTestUtils.hpp> -#include <boost/cast.hpp> #include <boost/iterator/transform_iterator.hpp> #include <cstring> @@ -49,7 +49,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, { Optional<std::string&> reason = outReasonIfUnsupported; bool result; - const Layer& layer = *(boost::polymorphic_downcast<const Layer*>(&connectableLayer)); + const Layer& layer = *(PolymorphicDowncast<const Layer*>(&connectableLayer)); auto const& backendRegistry = BackendRegistryInstance(); if (!backendRegistry.IsBackendRegistered(backendId)) @@ -70,7 +70,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, { case LayerType::Activation: { - auto cLayer = boost::polymorphic_downcast<const ActivationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ActivationLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsActivationSupported( @@ -94,7 +94,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::ArgMinMax: { - auto cLayer = boost::polymorphic_downcast<const ArgMinMaxLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ArgMinMaxLayer*>(&layer); const ArgMinMaxDescriptor& descriptor = cLayer->GetParameters(); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); @@ -108,7 +108,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::BatchNormalization: { - auto cLayer = boost::polymorphic_downcast<const BatchNormalizationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const BatchNormalizationLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); const TensorInfo& mean = cLayer->m_Mean->GetTensorInfo(); @@ -130,7 +130,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, { const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); - auto cLayer = boost::polymorphic_downcast<const BatchToSpaceNdLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const BatchToSpaceNdLayer*>(&layer); result = layerSupportObject->IsBatchToSpaceNdSupported(OverrideDataType(input, dataType), OverrideDataType(output, dataType), @@ -140,7 +140,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Comparison: { - auto cLayer = boost::polymorphic_downcast<const ComparisonLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ComparisonLayer*>(&layer); const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); @@ -189,7 +189,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Convolution2d: { - auto cLayer = boost::polymorphic_downcast<const Convolution2dLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const Convolution2dLayer*>(&layer); const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), dataType); @@ -227,7 +227,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::DepthToSpace: { - auto cLayer = boost::polymorphic_downcast<const DepthToSpaceLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const DepthToSpaceLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); @@ -240,7 +240,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::DepthwiseConvolution2d: { - auto cLayer = boost::polymorphic_downcast<const DepthwiseConvolution2dLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const DepthwiseConvolution2dLayer*>(&layer); const TensorInfo& input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), dataType); const TensorInfo& output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); @@ -277,7 +277,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::DetectionPostProcess: { - auto cLayer = boost::polymorphic_downcast<const DetectionPostProcessLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const DetectionPostProcessLayer*>(&layer); const TensorInfo& boxEncodings = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& scores = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); const TensorInfo& anchors = cLayer->m_Anchors->GetTensorInfo(); @@ -301,7 +301,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::ElementwiseUnary: { - auto cLayer = boost::polymorphic_downcast<const ElementwiseUnaryLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ElementwiseUnaryLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); @@ -314,7 +314,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::FakeQuantization: { - auto cLayer = boost::polymorphic_downcast<const FakeQuantizationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const FakeQuantizationLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); result = layerSupportObject->IsFakeQuantizationSupported(OverrideDataType(input, dataType), cLayer->GetParameters(), @@ -332,7 +332,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::FullyConnected: { - auto cLayer = boost::polymorphic_downcast<const FullyConnectedLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const FullyConnectedLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); @@ -414,7 +414,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::InstanceNormalization: { - auto cLayer = boost::polymorphic_downcast<const InstanceNormalizationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const InstanceNormalizationLayer*>(&layer); const InstanceNormalizationDescriptor& descriptor = cLayer->GetParameters(); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); @@ -429,7 +429,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::L2Normalization: { - auto cLayer = boost::polymorphic_downcast<const L2NormalizationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const L2NormalizationLayer*>(&layer); const L2NormalizationDescriptor& descriptor = cLayer->GetParameters(); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); @@ -444,7 +444,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::LogSoftmax: { - auto cLayer = boost::polymorphic_downcast<const LogSoftmaxLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const LogSoftmaxLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); @@ -457,7 +457,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Lstm: { - auto cLayer = boost::polymorphic_downcast<const LstmLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const LstmLayer*>(&layer); const LstmDescriptor& descriptor = cLayer->GetParameters(); // All inputs. @@ -645,7 +645,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Concat: { - auto cLayer = boost::polymorphic_downcast<const ConcatLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ConcatLayer*>(&layer); // Get vector of all inputs. auto getTensorInfo = [&dataType](const InputSlot& slot) @@ -685,7 +685,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Normalization: { - auto cLayer = boost::polymorphic_downcast<const NormalizationLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const NormalizationLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsNormalizationSupported(OverrideDataType(input, dataType), @@ -702,7 +702,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Permute: { - auto cLayer = boost::polymorphic_downcast<const PermuteLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const PermuteLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsPermuteSupported(OverrideDataType(input, dataType), @@ -713,7 +713,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Pad: { - auto cLayer = boost::polymorphic_downcast<const PadLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const PadLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsPadSupported( @@ -725,7 +725,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Pooling2d: { - auto cLayer = boost::polymorphic_downcast<const Pooling2dLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const Pooling2dLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsPooling2dSupported(OverrideDataType(input, dataType), @@ -736,7 +736,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::PreCompiled: { - auto cLayer = boost::polymorphic_downcast<const PreCompiledLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const PreCompiledLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); result = layerSupportObject->IsPreCompiledSupported(OverrideDataType(input, dataType), cLayer->GetParameters(), @@ -752,7 +752,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::QLstm: { - auto cLayer = boost::polymorphic_downcast<const QLstmLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const QLstmLayer*>(&layer); const QLstmDescriptor& descriptor = cLayer->GetParameters(); // Inputs @@ -840,7 +840,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::QuantizedLstm: { - auto cLayer = boost::polymorphic_downcast<const QuantizedLstmLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const QuantizedLstmLayer*>(&layer); // Inputs const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); @@ -904,7 +904,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Reshape: { - auto cLayer = boost::polymorphic_downcast<const ReshapeLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ReshapeLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsReshapeSupported(OverrideDataType(input, dataType), @@ -915,7 +915,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Resize: { - auto cLayer = boost::polymorphic_downcast<const ResizeLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const ResizeLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsResizeSupported(OverrideDataType(input, dataType), @@ -926,7 +926,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Slice: { - auto cLayer = boost::polymorphic_downcast<const SliceLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const SliceLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); @@ -939,7 +939,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Softmax: { - auto cLayer = boost::polymorphic_downcast<const SoftmaxLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const SoftmaxLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsSoftmaxSupported(OverrideDataType(input, dataType), @@ -950,7 +950,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::SpaceToBatchNd: { - auto cLayer = boost::polymorphic_downcast<const SpaceToBatchNdLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const SpaceToBatchNdLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsSpaceToBatchNdSupported(OverrideDataType(input, dataType), @@ -961,7 +961,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::SpaceToDepth: { - auto cLayer = boost::polymorphic_downcast<const SpaceToDepthLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const SpaceToDepthLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); @@ -974,7 +974,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Splitter: { - auto cLayer = boost::polymorphic_downcast<const SplitterLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const SplitterLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); // Get vector of all outputs. @@ -996,7 +996,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Stack: { - auto cLayer = boost::polymorphic_downcast<const StackLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const StackLayer*>(&layer); // Get vector of all inputs. auto getTensorInfo = [&dataType](const InputSlot& slot) @@ -1023,7 +1023,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::StandIn: { - auto cLayer = boost::polymorphic_downcast<const StandInLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const StandInLayer*>(&layer); // Get vector of all inputs. auto getTensorInfoIn = [&dataType](const InputSlot& slot) @@ -1064,7 +1064,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::StridedSlice: { - auto cLayer = boost::polymorphic_downcast<const StridedSliceLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const StridedSliceLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsStridedSliceSupported(OverrideDataType(input, dataType), @@ -1100,7 +1100,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Mean: { - auto cLayer = boost::polymorphic_downcast<const MeanLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const MeanLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsMeanSupported( @@ -1134,7 +1134,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::Transpose: { - auto cLayer = boost::polymorphic_downcast<const TransposeLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const TransposeLayer*>(&layer); const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); result = layerSupportObject->IsTransposeSupported(OverrideDataType(input, dataType), @@ -1145,7 +1145,7 @@ bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, } case LayerType::TransposeConvolution2d: { - auto cLayer = boost::polymorphic_downcast<const TransposeConvolution2dLayer*>(&layer); + auto cLayer = PolymorphicDowncast<const TransposeConvolution2dLayer*>(&layer); const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), dataType); @@ -1188,7 +1188,7 @@ bool IWorkloadFactory::IsLayerSupported(const IConnectableLayer& connectableLaye Optional<DataType> dataType, std::string& outReasonIfUnsupported) { - auto layer = boost::polymorphic_downcast<const Layer*>(&connectableLayer); + auto layer = PolymorphicDowncast<const Layer*>(&connectableLayer); return IsLayerSupported(layer->GetBackendId(), connectableLayer, dataType, outReasonIfUnsupported); } diff --git a/src/backends/backendsCommon/WorkloadUtils.cpp b/src/backends/backendsCommon/WorkloadUtils.cpp index bd5e81e678..37915cfc4d 100644 --- a/src/backends/backendsCommon/WorkloadUtils.cpp +++ b/src/backends/backendsCommon/WorkloadUtils.cpp @@ -7,6 +7,8 @@ #include <armnn/Utils.hpp> +#include <boost/numeric/conversion/cast.hpp> + namespace armnn { diff --git a/src/backends/backendsCommon/WorkloadUtils.hpp b/src/backends/backendsCommon/WorkloadUtils.hpp index a4da924725..354362ec8f 100644 --- a/src/backends/backendsCommon/WorkloadUtils.hpp +++ b/src/backends/backendsCommon/WorkloadUtils.hpp @@ -8,15 +8,13 @@ #include "CpuTensorHandle.hpp" #include <armnn/backends/ITensorHandle.hpp> - #include <armnn/Tensor.hpp> - +#include <armnn/utility/PolymorphicDowncast.hpp> #include <armnnUtils/Permute.hpp> #include <Half.hpp> #include <Profiling.hpp> -#include <boost/cast.hpp> namespace armnn { @@ -198,9 +196,9 @@ void GatherTensorHandlePairs(const DescriptorType& descriptor, for (unsigned int i = 0; i < numInputs; ++i) { SrcTensorHandleType* const srcTensorHandle = - boost::polymorphic_downcast<SrcTensorHandleType*>(descriptor.m_Inputs[i]); + PolymorphicDowncast<SrcTensorHandleType*>(descriptor.m_Inputs[i]); DstTensorHandleType* const dstTensorHandle = - boost::polymorphic_downcast<DstTensorHandleType*>(descriptor.m_Outputs[i]); + PolymorphicDowncast<DstTensorHandleType*>(descriptor.m_Outputs[i]); tensorHandlePairs.emplace_back(srcTensorHandle, dstTensorHandle); } diff --git a/src/backends/backendsCommon/test/DynamicBackendTests.hpp b/src/backends/backendsCommon/test/DynamicBackendTests.hpp index 1276776a4d..6371e53250 100644 --- a/src/backends/backendsCommon/test/DynamicBackendTests.hpp +++ b/src/backends/backendsCommon/test/DynamicBackendTests.hpp @@ -6,15 +6,12 @@ #pragma once #include <armnn/BackendRegistry.hpp> -#include <armnn/ILayerSupport.hpp> - #include <armnn/backends/DynamicBackend.hpp> - -#include <backendsCommon/DynamicBackendUtils.hpp> +#include <armnn/ILayerSupport.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> - +#include <backendsCommon/DynamicBackendUtils.hpp> #include <reference/workloads/RefConvolution2dWorkload.hpp> - #include <Runtime.hpp> #include <string> @@ -1212,7 +1209,7 @@ void RuntimeEmptyTestImpl() IRuntime::CreationOptions creationOptions; IRuntimePtr runtime = IRuntime::Create(creationOptions); - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.empty()); @@ -1253,7 +1250,7 @@ void RuntimeDynamicBackendsTestImpl() BOOST_TEST((backendIds.find(expectedRegisteredbackendId) != backendIds.end())); } - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.size() == expectedRegisteredbackendIds.size()); for (const BackendId& expectedRegisteredbackendId : expectedRegisteredbackendIds) @@ -1294,7 +1291,7 @@ void RuntimeDuplicateDynamicBackendsTestImpl() BOOST_TEST((backendIds.find(expectedRegisteredbackendId) != backendIds.end())); } - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.size() == expectedRegisteredbackendIds.size()); for (const BackendId& expectedRegisteredbackendId : expectedRegisteredbackendIds) @@ -1323,7 +1320,7 @@ void RuntimeInvalidDynamicBackendsTestImpl() const BackendRegistry& backendRegistry = BackendRegistryInstance(); BOOST_TEST(backendRegistry.Size() == 0); - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.empty()); } @@ -1343,7 +1340,7 @@ void RuntimeInvalidOverridePathTestImpl() const BackendRegistry& backendRegistry = BackendRegistryInstance(); BOOST_TEST(backendRegistry.Size() == 0); - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.empty()); } @@ -1382,7 +1379,7 @@ void CreateReferenceDynamicBackendTestImpl() BackendIdSet backendIds = backendRegistry.GetBackendIds(); BOOST_TEST((backendIds.find("CpuRef") != backendIds.end())); - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.size() == 1); BOOST_TEST((supportedBackendIds.find("CpuRef") != supportedBackendIds.end())); @@ -1433,7 +1430,7 @@ void CreateReferenceDynamicBackendTestImpl() // Create a convolution workload with the dummy settings auto workload = referenceWorkloadFactory->CreateConvolution2d(convolution2dQueueDescriptor, workloadInfo); BOOST_TEST((workload != nullptr)); - BOOST_TEST(workload.get() == boost::polymorphic_downcast<RefConvolution2dWorkload*>(workload.get())); + BOOST_TEST(workload.get() == PolymorphicDowncast<RefConvolution2dWorkload*>(workload.get())); } #endif @@ -1453,7 +1450,7 @@ void CreateSampleDynamicBackendTestImpl() BackendIdSet backendIds = backendRegistry.GetBackendIds(); BOOST_TEST((backendIds.find("SampleDynamic") != backendIds.end())); - const DeviceSpec& deviceSpec = *boost::polymorphic_downcast<const DeviceSpec*>(&runtime->GetDeviceSpec()); + const DeviceSpec& deviceSpec = *PolymorphicDowncast<const DeviceSpec*>(&runtime->GetDeviceSpec()); BackendIdSet supportedBackendIds = deviceSpec.GetSupportedBackends(); BOOST_TEST(supportedBackendIds.size()>= 1); BOOST_TEST((supportedBackendIds.find("SampleDynamic") != supportedBackendIds.end())); diff --git a/src/backends/backendsCommon/test/OptimizationViewsTests.cpp b/src/backends/backendsCommon/test/OptimizationViewsTests.cpp index 3aebe3e964..c972b4b15f 100644 --- a/src/backends/backendsCommon/test/OptimizationViewsTests.cpp +++ b/src/backends/backendsCommon/test/OptimizationViewsTests.cpp @@ -3,15 +3,19 @@ // SPDX-License-Identifier: MIT // -#include <boost/test/unit_test.hpp> + +#include "CommonTestUtils.hpp" +#include "MockBackend.hpp" + +#include <armnn/backends/OptimizationViews.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <Graph.hpp> +#include <Network.hpp> #include <SubgraphView.hpp> #include <SubgraphViewSelector.hpp> -#include <armnn/backends/OptimizationViews.hpp> -#include <Network.hpp> -#include "CommonTestUtils.hpp" -#include "MockBackend.hpp" +#include <boost/test/unit_test.hpp> + using namespace armnn; @@ -208,7 +212,7 @@ BOOST_AUTO_TEST_CASE(OptimizeViewsValidateDeviceMockBackend) BOOST_CHECK(optNet); // Check the optimised graph - OptimizedNetwork* optNetObjPtr = boost::polymorphic_downcast<OptimizedNetwork*>(optNet.get()); + OptimizedNetwork* optNetObjPtr = PolymorphicDowncast<OptimizedNetwork*>(optNet.get()); CheckLayers(optNetObjPtr->GetGraph()); } diff --git a/src/backends/cl/ClBackendContext.cpp b/src/backends/cl/ClBackendContext.cpp index f612c3743d..bfe93bdc01 100644 --- a/src/backends/cl/ClBackendContext.cpp +++ b/src/backends/cl/ClBackendContext.cpp @@ -8,14 +8,13 @@ #include <armnn/Logging.hpp> #include <armnn/utility/Assert.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/core/CL/OpenCL.h> #include <arm_compute/core/CL/CLKernelLibrary.h> #include <arm_compute/runtime/CL/CLScheduler.h> #include <arm_compute/runtime/CL/CLTunerTypes.h> -#include <boost/polymorphic_cast.hpp> - namespace armnn { @@ -161,7 +160,7 @@ ClBackendContext::ClBackendContext(const IRuntime::CreationOptions& options) bool useLegacyTunerAPI = options.m_GpuAccTunedParameters.get() != nullptr; if (useLegacyTunerAPI) { - auto clTunerParams = boost::polymorphic_downcast<ClTunedParameters*>( + auto clTunerParams = PolymorphicDowncast<ClTunedParameters*>( options.m_GpuAccTunedParameters.get()); tuner = &clTunerParams->m_Tuner; diff --git a/src/backends/cl/ClTensorHandleFactory.cpp b/src/backends/cl/ClTensorHandleFactory.cpp index 9df3f1a4a6..8af97f41e2 100644 --- a/src/backends/cl/ClTensorHandleFactory.cpp +++ b/src/backends/cl/ClTensorHandleFactory.cpp @@ -7,12 +7,12 @@ #include "ClTensorHandleFactory.hpp" #include "ClTensorHandle.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <arm_compute/runtime/CL/CLTensor.h> #include <arm_compute/core/Coordinates.h> #include <arm_compute/runtime/CL/CLSubTensor.h> -#include <boost/polymorphic_cast.hpp> - namespace armnn { @@ -42,7 +42,7 @@ std::unique_ptr<ITensorHandle> ClTensorHandleFactory::CreateSubTensorHandle(ITen } return std::make_unique<ClSubTensorHandle>( - boost::polymorphic_downcast<IClTensorHandle *>(&parent), shape, coords); + PolymorphicDowncast<IClTensorHandle *>(&parent), shape, coords); } std::unique_ptr<ITensorHandle> ClTensorHandleFactory::CreateTensorHandle(const TensorInfo& tensorInfo) const diff --git a/src/backends/cl/ClWorkloadFactory.cpp b/src/backends/cl/ClWorkloadFactory.cpp index b1bd46c4d7..b0d2fdf835 100644 --- a/src/backends/cl/ClWorkloadFactory.cpp +++ b/src/backends/cl/ClWorkloadFactory.cpp @@ -10,6 +10,7 @@ #include <armnn/Exceptions.hpp> #include <armnn/Utils.hpp> #include <armnn/utility/IgnoreUnused.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <backendsCommon/MakeWorkloadHelper.hpp> @@ -24,7 +25,6 @@ #include <arm_compute/runtime/CL/CLBufferAllocator.h> #include <arm_compute/runtime/CL/CLScheduler.h> -#include <boost/polymorphic_cast.hpp> #include <boost/format.hpp> namespace armnn @@ -125,7 +125,7 @@ std::unique_ptr<ITensorHandle> ClWorkloadFactory::CreateSubTensorHandle(ITensorH } return std::make_unique<ClSubTensorHandle>( - boost::polymorphic_downcast<IClTensorHandle*>(&parent), shape, coords); + PolymorphicDowncast<IClTensorHandle*>(&parent), shape, coords); } std::unique_ptr<IWorkload> ClWorkloadFactory::CreateAbs(const AbsQueueDescriptor& descriptor, diff --git a/src/backends/cl/test/ClCreateWorkloadTests.cpp b/src/backends/cl/test/ClCreateWorkloadTests.cpp index 92e771760f..b09b26f9b3 100644 --- a/src/backends/cl/test/ClCreateWorkloadTests.cpp +++ b/src/backends/cl/test/ClCreateWorkloadTests.cpp @@ -6,6 +6,7 @@ #include "ClContextControlFixture.hpp" #include "ClWorkloadFactoryHelper.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/MemCopyWorkload.hpp> #include <aclCommon/test/CreateWorkloadClNeon.hpp> @@ -35,8 +36,8 @@ static void ClCreateActivationWorkloadTest() // Checks that inputs/outputs are as we expect them (see definition of CreateActivationWorkloadTest). ActivationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {1, 1})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {1, 1})); @@ -66,9 +67,9 @@ static void ClCreateElementwiseWorkloadTest() // Checks that inputs/outputs are as we expect them (see definition of CreateElementwiseWorkloadTest). DescriptorType queueDescriptor = workload->GetData(); - auto inputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle1 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle2 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle1, {2, 3})); BOOST_TEST(CompareIClTensorHandleShape(inputHandle2, {2, 3})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 3})); @@ -159,8 +160,8 @@ static void ClCreateElementwiseUnaryWorkloadTest(armnn::UnaryOperation op) DescriptorType queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {2, 3})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 3})); @@ -184,8 +185,8 @@ static void ClCreateBatchNormalizationWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); switch (dataLayout) { @@ -232,8 +233,8 @@ BOOST_AUTO_TEST_CASE(CreateConvertFp16ToFp32Workload) auto workload = CreateConvertFp16ToFp32WorkloadTest<ClConvertFp16ToFp32Workload>(factory, graph); ConvertFp16ToFp32QueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {1, 3, 2, 3})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {1, 3, 2, 3})); @@ -250,8 +251,8 @@ BOOST_AUTO_TEST_CASE(CreateConvertFp32ToFp16Workload) auto workload = CreateConvertFp32ToFp16WorkloadTest<ClConvertFp32ToFp16Workload>(factory, graph); ConvertFp32ToFp16QueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {1, 3, 2, 3})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {1, 3, 2, 3})); @@ -277,8 +278,8 @@ static void ClConvolution2dWorkloadTest(DataLayout dataLayout) // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((inputHandle->GetShape() == inputShape)); BOOST_TEST((outputHandle->GetShape() == outputShape)); } @@ -315,8 +316,8 @@ static void ClDepthwiseConvolutionWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateDepthwiseConvolution2dWorkloadTest). DepthwiseConvolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 }) : std::initializer_list<unsigned int>({ 2, 5, 5, 2 }); @@ -343,8 +344,8 @@ static void ClDirectConvolution2dWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateDirectConvolution2dWorkloadTest). Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {2, 3, 6, 6})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 2, 6, 6})); } @@ -376,8 +377,8 @@ static void ClCreateFullyConnectedWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). FullyConnectedQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {3, 1, 4, 5})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {3, 7})); } @@ -404,8 +405,8 @@ static void ClNormalizationWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({3, 5, 5, 1}) : std::initializer_list<unsigned int>({3, 1, 5, 5}); @@ -452,8 +453,8 @@ static void ClPooling2dWorkloadTest(DataLayout dataLayout) // Check that inputs/outputs are as we expect them (see definition of CreatePooling2dWorkloadTest). Pooling2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((inputHandle->GetShape() == inputShape)); BOOST_TEST((outputHandle->GetShape() == outputShape)); @@ -497,9 +498,9 @@ static void ClCreatePreluWorkloadTest(const armnn::TensorShape& inputShape, // Checks that outputs and inputs are as we expect them (see definition of CreatePreluWorkloadTest). PreluQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto alphaHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto alphaHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((inputHandle->GetShape() == inputShape)); BOOST_TEST((alphaHandle->GetShape() == alphaShape)); @@ -532,8 +533,8 @@ static void ClCreateReshapeWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). ReshapeQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {4, 1})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {1, 4})); @@ -565,8 +566,8 @@ static void ClSoftmaxWorkloadTest() // Checks that inputs/outputs are as we expect them (see definition of ClSoftmaxFloatWorkload). SoftmaxQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {4, 1})); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {4, 1})); @@ -594,16 +595,16 @@ static void ClSplitterWorkloadTest() // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). SplitterQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {5, 7, 7})); - auto outputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); + auto outputHandle1 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST(CompareIClTensorHandleShape(outputHandle1, {2, 7, 7})); - auto outputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[2]); + auto outputHandle2 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[2]); BOOST_TEST(CompareIClTensorHandleShape(outputHandle2, {2, 7, 7})); - auto outputHandle0 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle0 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(outputHandle0, {1, 7, 7})); } @@ -738,8 +739,8 @@ static void ClL2NormalizationWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). L2NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 5, 20, 50, 67 }) : std::initializer_list<unsigned int>({ 5, 50, 67, 20 }); @@ -780,8 +781,8 @@ static void ClCreateLstmWorkloadTest() auto workload = CreateLstmWorkloadTest<LstmWorkloadType>(factory, graph); LstmQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 2, 2 })); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 2, 4 })); } @@ -802,8 +803,8 @@ static void ClResizeWorkloadTest(DataLayout dataLayout) auto queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); switch (dataLayout) { @@ -859,8 +860,8 @@ static void ClMeanWorkloadTest() // Checks that inputs/outputs are as we expect them (see definition of CreateMeanWorkloadTest). MeanQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); // The first dimension (batch size) in both input and output is singular thus it has been reduced by ACL. BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 1, 3, 7, 4 })); @@ -893,9 +894,9 @@ static void ClCreateConcatWorkloadTest(std::initializer_list<unsigned int> outpu auto workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis); ConcatQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle0 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle0 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle1 = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle0, { 2, 3, 2, 5 })); BOOST_TEST(CompareIClTensorHandleShape(inputHandle1, { 2, 3, 2, 5 })); @@ -942,8 +943,8 @@ static void ClSpaceToDepthWorkloadTest() auto workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph); SpaceToDepthQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 1, 2, 2, 1 })); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 1, 1, 1, 4 })); @@ -990,10 +991,10 @@ static void ClCreateStackWorkloadTest(const std::initializer_list<unsigned int>& StackQueueDescriptor queueDescriptor = workload->GetData(); for (unsigned int i = 0; i < numInputs; ++i) { - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[i]); + auto inputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Inputs[i]); BOOST_TEST(CompareIClTensorHandleShape(inputHandle, inputShape)); } - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle = PolymorphicDowncast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(CompareIClTensorHandleShape(outputHandle, outputShape)); } @@ -1016,7 +1017,6 @@ template <typename QuantizedLstmWorkloadType> static void ClCreateQuantizedLstmWorkloadTest() { using namespace armnn::armcomputetensorutils; - using boost::polymorphic_downcast; Graph graph; ClWorkloadFactory factory = @@ -1026,23 +1026,23 @@ static void ClCreateQuantizedLstmWorkloadTest() QuantizedLstmQueueDescriptor queueDescriptor = workload->GetData(); - IAclTensorHandle* inputHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + IAclTensorHandle* inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); BOOST_TEST((inputHandle->GetShape() == TensorShape({2, 2}))); BOOST_TEST((inputHandle->GetDataType() == arm_compute::DataType::QASYMM8)); - IAclTensorHandle* cellStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); + IAclTensorHandle* cellStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); BOOST_TEST((cellStateInHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((cellStateInHandle->GetDataType() == arm_compute::DataType::QSYMM16)); - IAclTensorHandle* outputStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]); + IAclTensorHandle* outputStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]); BOOST_TEST((outputStateInHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((outputStateInHandle->GetDataType() == arm_compute::DataType::QASYMM8)); - IAclTensorHandle* cellStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + IAclTensorHandle* cellStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((cellStateOutHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((cellStateOutHandle->GetDataType() == arm_compute::DataType::QSYMM16)); - IAclTensorHandle* outputStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); + IAclTensorHandle* outputStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST((outputStateOutHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((outputStateOutHandle->GetDataType() == arm_compute::DataType::QASYMM8)); } diff --git a/src/backends/cl/workloads/ClAbsWorkload.cpp b/src/backends/cl/workloads/ClAbsWorkload.cpp index 058c453c6b..d020eeb344 100644 --- a/src/backends/cl/workloads/ClAbsWorkload.cpp +++ b/src/backends/cl/workloads/ClAbsWorkload.cpp @@ -7,6 +7,8 @@ #include "ClWorkloadUtils.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <aclCommon/ArmComputeTensorUtils.hpp> #include <cl/ClTensorHandle.hpp> @@ -29,8 +31,8 @@ ClAbsWorkload::ClAbsWorkload(const AbsQueueDescriptor& descriptor, const Workloa { m_Data.ValidateInputsOutputs("ClAbsWorkload", 1, 1); - arm_compute::ICLTensor& input = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ICLTensor& output = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ICLTensor& input = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ICLTensor& output = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_AbsLayer.configure(&input, &output); } diff --git a/src/backends/cl/workloads/ClNegWorkload.cpp b/src/backends/cl/workloads/ClNegWorkload.cpp index cc6333fff9..9f83cd32c3 100644 --- a/src/backends/cl/workloads/ClNegWorkload.cpp +++ b/src/backends/cl/workloads/ClNegWorkload.cpp @@ -8,6 +8,7 @@ #include "ClWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <cl/ClTensorHandle.hpp> @@ -29,8 +30,8 @@ ClNegWorkload::ClNegWorkload(const ElementwiseUnaryQueueDescriptor& descriptor, { m_Data.ValidateInputsOutputs("ClNegWorkload", 1, 1); - arm_compute::ICLTensor& input = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ICLTensor& output = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ICLTensor& input = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ICLTensor& output = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_NegLayer.configure(&input, &output); } diff --git a/src/backends/cl/workloads/ClRsqrtWorkload.cpp b/src/backends/cl/workloads/ClRsqrtWorkload.cpp index be687595f7..a305a4a919 100644 --- a/src/backends/cl/workloads/ClRsqrtWorkload.cpp +++ b/src/backends/cl/workloads/ClRsqrtWorkload.cpp @@ -8,6 +8,7 @@ #include "ClWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <cl/ClTensorHandle.hpp> @@ -29,8 +30,8 @@ ClRsqrtWorkload::ClRsqrtWorkload(const RsqrtQueueDescriptor& descriptor, const W { m_Data.ValidateInputsOutputs("ClRsqrtWorkload", 1, 1); - arm_compute::ICLTensor& input = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ICLTensor& output = boost::polymorphic_downcast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ICLTensor& input = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ICLTensor& output = PolymorphicDowncast<ClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_RsqrtLayer.configure(&input, &output); } diff --git a/src/backends/cl/workloads/ClSliceWorkload.cpp b/src/backends/cl/workloads/ClSliceWorkload.cpp index fa99e7f54d..5ea4c4cefd 100644 --- a/src/backends/cl/workloads/ClSliceWorkload.cpp +++ b/src/backends/cl/workloads/ClSliceWorkload.cpp @@ -8,6 +8,7 @@ #include "ClWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <cl/ClTensorHandle.hpp> @@ -36,8 +37,8 @@ ClSliceWorkload::ClSliceWorkload(const SliceQueueDescriptor& descriptor, const W { m_Data.ValidateInputsOutputs("ClSliceWorkload", 1, 1); - arm_compute::ICLTensor& input = boost::polymorphic_downcast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ICLTensor& output = boost::polymorphic_downcast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ICLTensor& input = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ICLTensor& output = PolymorphicDowncast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::Coordinates starts; arm_compute::Coordinates ends; diff --git a/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp b/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp index d541e4ec52..1acb5c64e6 100644 --- a/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp +++ b/src/backends/cl/workloads/ClSpaceToDepthWorkload.cpp @@ -10,7 +10,6 @@ #include <aclCommon/ArmComputeTensorUtils.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <cl/ClTensorHandle.hpp> -#include <boost/polymorphic_pointer_cast.hpp> namespace armnn { diff --git a/src/backends/neon/NeonTensorHandleFactory.cpp b/src/backends/neon/NeonTensorHandleFactory.cpp index 26b14af144..a8b5b81412 100644 --- a/src/backends/neon/NeonTensorHandleFactory.cpp +++ b/src/backends/neon/NeonTensorHandleFactory.cpp @@ -7,6 +7,7 @@ #include "NeonTensorHandle.hpp" #include <armnn/utility/IgnoreUnused.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> namespace armnn { @@ -36,7 +37,7 @@ std::unique_ptr<ITensorHandle> NeonTensorHandleFactory::CreateSubTensorHandle(IT } return std::make_unique<NeonSubTensorHandle>( - boost::polymorphic_downcast<IAclTensorHandle*>(&parent), shape, coords); + PolymorphicDowncast<IAclTensorHandle*>(&parent), shape, coords); } std::unique_ptr<ITensorHandle> NeonTensorHandleFactory::CreateTensorHandle(const TensorInfo& tensorInfo) const diff --git a/src/backends/neon/NeonWorkloadFactory.cpp b/src/backends/neon/NeonWorkloadFactory.cpp index 47f72050a5..b3104b9576 100644 --- a/src/backends/neon/NeonWorkloadFactory.cpp +++ b/src/backends/neon/NeonWorkloadFactory.cpp @@ -11,6 +11,7 @@ #include <armnn/Utils.hpp> #include <armnn/utility/IgnoreUnused.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <backendsCommon/MakeWorkloadHelper.hpp> @@ -69,7 +70,7 @@ std::unique_ptr<ITensorHandle> NeonWorkloadFactory::CreateSubTensorHandle(ITenso } return std::make_unique<NeonSubTensorHandle>( - boost::polymorphic_downcast<IAclTensorHandle*>(&parent), shape, coords); + PolymorphicDowncast<IAclTensorHandle*>(&parent), shape, coords); } std::unique_ptr<ITensorHandle> NeonWorkloadFactory::CreateTensorHandle(const TensorInfo& tensorInfo, diff --git a/src/backends/neon/test/NeonCreateWorkloadTests.cpp b/src/backends/neon/test/NeonCreateWorkloadTests.cpp index 3e1888cb54..447bad155f 100644 --- a/src/backends/neon/test/NeonCreateWorkloadTests.cpp +++ b/src/backends/neon/test/NeonCreateWorkloadTests.cpp @@ -6,6 +6,7 @@ #include "NeonWorkloadFactoryHelper.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/MemCopyWorkload.hpp> #include <aclCommon/test/CreateWorkloadClNeon.hpp> @@ -72,8 +73,8 @@ static void NeonCreateActivationWorkloadTest() // Checks that inputs/outputs are as we expect them (see definition of CreateActivationWorkloadTest). ActivationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({1, 1}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({1, 1}, DataType))); } @@ -103,9 +104,9 @@ static void NeonCreateElementwiseWorkloadTest() auto workload = CreateElementwiseWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>(factory, graph); DescriptorType queueDescriptor = workload->GetData(); - auto inputHandle1 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle2 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle2 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle1, TensorInfo({2, 3}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle2, TensorInfo({2, 3}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({2, 3}, DataType))); @@ -201,8 +202,8 @@ static void NeonCreateBatchNormalizationWorkloadTest(DataLayout dataLayout) // Checks that outputs and inputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 4, 4} : TensorShape{2, 4, 4, 3}; TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{2, 3, 4, 4} : TensorShape{2, 4, 4, 3}; @@ -247,8 +248,8 @@ static void NeonCreateConvolution2dWorkloadTest(DataLayout dataLayout = DataLayo // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo(inputShape, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo(outputShape, DataType))); } @@ -287,8 +288,8 @@ static void NeonCreateDepthWiseConvolutionWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). DepthwiseConvolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? std::initializer_list<unsigned int>({ 2, 2, 5, 5 }) : std::initializer_list<unsigned int>({ 2, 5, 5, 2 }); @@ -322,8 +323,8 @@ static void NeonCreateFullyConnectedWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). FullyConnectedQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({3, 1, 4, 5}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({3, 7}, DataType))); } @@ -351,8 +352,8 @@ static void NeonCreateNormalizationWorkloadTest(DataLayout dataLayout) // Checks that outputs and inputs are as we expect them (see definition of CreateNormalizationWorkloadTest). NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 5, 5, 1} : TensorShape{3, 1, 5, 5}; TensorShape outputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{3, 5, 5, 1} : TensorShape{3, 1, 5, 5}; @@ -398,8 +399,8 @@ static void NeonCreatePooling2dWorkloadTest(DataLayout dataLayout = DataLayout:: // Checks that outputs and inputs are as we expect them (see definition of CreatePooling2dWorkloadTest). Pooling2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo(inputShape, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo(outputShape, DataType))); } @@ -449,9 +450,9 @@ static void NeonCreatePreluWorkloadTest(const armnn::TensorShape& inputShape, // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). PreluQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto alphaHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto alphaHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo(inputShape, dataType))); BOOST_TEST(TestNeonTensorHandleInfo(alphaHandle, TensorInfo(alphaShape, dataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo(outputShape, dataType))); @@ -485,8 +486,8 @@ static void NeonCreateReshapeWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). ReshapeQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({4, 1}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({1, 4}, DataType))); } @@ -518,8 +519,8 @@ static void NeonCreateResizeWorkloadTest(DataLayout dataLayout) auto queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); switch (dataLayout) { @@ -565,8 +566,8 @@ static void NeonCreateSoftmaxWorkloadTest() // Checks that outputs and inputs are as we expect them (see definition of CreateSoftmaxWorkloadTest). SoftmaxQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({4, 1}, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({4, 1}, DataType))); } @@ -593,8 +594,8 @@ static void NeonSpaceToDepthWorkloadTest() auto workload = CreateSpaceToDepthWorkloadTest<SpaceToDepthWorkloadType, DataType>(factory, graph); SpaceToDepthQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({ 1, 2, 2, 1 }, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({ 1, 1, 1, 4 }, DataType))); @@ -630,16 +631,16 @@ BOOST_AUTO_TEST_CASE(CreateSplitterWorkload) // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). SplitterQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({5, 7, 7}, DataType::Float32))); - auto outputHandle0 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle0 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle0, TensorInfo({1, 7, 7}, DataType::Float32))); - auto outputHandle1 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); + auto outputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle1, TensorInfo({2, 7, 7}, DataType::Float32))); - auto outputHandle2 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[2]); + auto outputHandle2 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[2]); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle2, TensorInfo({2, 7, 7}, DataType::Float32))); } @@ -743,8 +744,8 @@ static void NeonCreateL2NormalizationWorkloadTest(DataLayout dataLayout) // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). L2NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); TensorShape inputShape = (dataLayout == DataLayout::NCHW) ? TensorShape{ 5, 20, 50, 67 } : TensorShape{ 5, 50, 67, 20 }; @@ -788,8 +789,8 @@ static void NeonCreateLstmWorkloadTest() LstmQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo({ 2, 2 }, DataType::Float32))); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo({ 2, 4 }, DataType::Float32))); @@ -811,9 +812,9 @@ static void NeonCreateConcatWorkloadTest(std::initializer_list<unsigned int> out auto workload = CreateConcatWorkloadTest<ConcatWorkloadType, DataType>(factory, graph, outputShape, concatAxis); ConcatQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle0 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle1 = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle0 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle1 = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle0, TensorInfo({ 2, 3, 2, 5 }, DataType))); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle1, TensorInfo({ 2, 3, 2, 5 }, DataType))); @@ -871,10 +872,10 @@ static void NeonCreateStackWorkloadTest(const std::initializer_list<unsigned int StackQueueDescriptor queueDescriptor = workload->GetData(); for (unsigned int i = 0; i < numInputs; ++i) { - auto inputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[i]); + auto inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[i]); BOOST_TEST(TestNeonTensorHandleInfo(inputHandle, TensorInfo(inputShape, DataType))); } - auto outputHandle = boost::polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST(TestNeonTensorHandleInfo(outputHandle, TensorInfo(outputShape, DataType))); } @@ -898,8 +899,6 @@ BOOST_AUTO_TEST_CASE(CreateStackUint8Workload) template <typename QuantizedLstmWorkloadType> static void NeonCreateQuantizedLstmWorkloadTest() { - using boost::polymorphic_downcast; - Graph graph; NeonWorkloadFactory factory = NeonWorkloadFactoryHelper::GetFactory(NeonWorkloadFactoryHelper::GetMemoryManager()); @@ -907,23 +906,23 @@ static void NeonCreateQuantizedLstmWorkloadTest() QuantizedLstmQueueDescriptor queueDescriptor = workload->GetData(); - IAclTensorHandle* inputHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); + IAclTensorHandle* inputHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[0]); BOOST_TEST((inputHandle->GetShape() == TensorShape({2, 2}))); BOOST_TEST((inputHandle->GetDataType() == arm_compute::DataType::QASYMM8)); - IAclTensorHandle* cellStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); + IAclTensorHandle* cellStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[1]); BOOST_TEST((cellStateInHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((cellStateInHandle->GetDataType() == arm_compute::DataType::QSYMM16)); - IAclTensorHandle* outputStateInHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]); + IAclTensorHandle* outputStateInHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Inputs[2]); BOOST_TEST((outputStateInHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((outputStateInHandle->GetDataType() == arm_compute::DataType::QASYMM8)); - IAclTensorHandle* cellStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); + IAclTensorHandle* cellStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((cellStateOutHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((cellStateOutHandle->GetDataType() == arm_compute::DataType::QSYMM16)); - IAclTensorHandle* outputStateOutHandle = polymorphic_downcast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); + IAclTensorHandle* outputStateOutHandle = PolymorphicDowncast<IAclTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST((outputStateOutHandle->GetShape() == TensorShape({2, 4}))); BOOST_TEST((outputStateOutHandle->GetDataType() == arm_compute::DataType::QASYMM8)); } diff --git a/src/backends/neon/workloads/NeonAbsWorkload.cpp b/src/backends/neon/workloads/NeonAbsWorkload.cpp index 7f8ed5a006..ea14ac3897 100644 --- a/src/backends/neon/workloads/NeonAbsWorkload.cpp +++ b/src/backends/neon/workloads/NeonAbsWorkload.cpp @@ -9,8 +9,7 @@ #include <aclCommon/ArmComputeTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> - -#include <boost/cast.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> namespace armnn { @@ -28,8 +27,8 @@ NeonAbsWorkload::NeonAbsWorkload(const AbsQueueDescriptor& descriptor, const Wor { m_Data.ValidateInputsOutputs("NeonAbsWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_AbsLayer.configure(&input, &output); } diff --git a/src/backends/neon/workloads/NeonActivationWorkload.cpp b/src/backends/neon/workloads/NeonActivationWorkload.cpp index 916d67449c..4b2169a6ee 100644 --- a/src/backends/neon/workloads/NeonActivationWorkload.cpp +++ b/src/backends/neon/workloads/NeonActivationWorkload.cpp @@ -5,7 +5,9 @@ #include "NeonActivationWorkload.hpp" #include "NeonWorkloadUtils.hpp" + #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/runtime/NEON/functions/NEActivationLayer.h> @@ -36,8 +38,8 @@ NeonActivationWorkload::NeonActivationWorkload(const ActivationQueueDescriptor& const arm_compute::ActivationLayerInfo activationLayerInfo = ConvertActivationDescriptorToAclActivationLayerInfo(m_Data.m_Parameters); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEActivationLayer>(); layer->configure(&input, &output, activationLayerInfo); diff --git a/src/backends/neon/workloads/NeonAdditionWorkload.cpp b/src/backends/neon/workloads/NeonAdditionWorkload.cpp index a025c0b8f5..cb0c8a471f 100644 --- a/src/backends/neon/workloads/NeonAdditionWorkload.cpp +++ b/src/backends/neon/workloads/NeonAdditionWorkload.cpp @@ -7,6 +7,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <arm_compute/runtime/NEON/functions/NEArithmeticAddition.h> @@ -35,9 +36,9 @@ NeonAdditionWorkload::NeonAdditionWorkload(const AdditionQueueDescriptor& descri { m_Data.ValidateInputsOutputs("NeonAdditionWorkload", 2, 1); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input2 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input2 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEArithmeticAddition>(); layer->configure(&input1, &input2, &output, arm_compute::ConvertPolicy::SATURATE); diff --git a/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp b/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp index 0fa9d43b15..0fb819db0b 100644 --- a/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp +++ b/src/backends/neon/workloads/NeonArgMinMaxWorkload.cpp @@ -10,6 +10,7 @@ #include <backendsCommon/CpuTensorHandle.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <armnnUtils/TensorUtils.hpp> #include <arm_compute/runtime/NEON/functions/NEArgMinMaxLayer.h> @@ -54,8 +55,8 @@ NeonArgMinMaxWorkload::NeonArgMinMaxWorkload(const ArgMinMaxQueueDescriptor& des const WorkloadInfo& info) : BaseWorkload<ArgMinMaxQueueDescriptor>(descriptor, info) { - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto numDims = info.m_InputTensorInfos[0].GetNumDimensions(); auto unsignedAxis = armnnUtils::GetUnsignedAxis(numDims, m_Data.m_Parameters.m_Axis); diff --git a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp index cd931e3797..ff777dbf9b 100644 --- a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp +++ b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp @@ -7,8 +7,9 @@ #include "NeonWorkloadUtils.hpp" -#include <backendsCommon/CpuTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> +#include <backendsCommon/CpuTensorHandle.hpp> #include <arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h> @@ -53,8 +54,8 @@ NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload( { m_Data.ValidateInputsOutputs("NeonBatchNormalizationWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonConstantWorkload.cpp b/src/backends/neon/workloads/NeonConstantWorkload.cpp index b9cb807779..1cffbe1448 100644 --- a/src/backends/neon/workloads/NeonConstantWorkload.cpp +++ b/src/backends/neon/workloads/NeonConstantWorkload.cpp @@ -9,6 +9,7 @@ #include <BFloat16.hpp> #include <Half.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <neon/NeonTensorHandle.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <backendsCommon/Workload.hpp> @@ -41,9 +42,9 @@ void NeonConstantWorkload::Execute() const ARMNN_ASSERT(data.m_LayerOutput != nullptr); arm_compute::ITensor& output = - boost::polymorphic_downcast<NeonTensorHandle*>(data.m_Outputs[0])->GetTensor(); + PolymorphicDowncast<NeonTensorHandle*>(data.m_Outputs[0])->GetTensor(); arm_compute::DataType computeDataType = - boost::polymorphic_downcast<NeonTensorHandle*>(data.m_Outputs[0])->GetDataType(); + PolymorphicDowncast<NeonTensorHandle*>(data.m_Outputs[0])->GetDataType(); switch (computeDataType) { diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp index 5d45642eef..144baec0ca 100644 --- a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp @@ -5,8 +5,9 @@ #include "NeonConvolution2dWorkload.hpp" -#include <backendsCommon/CpuTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> +#include <backendsCommon/CpuTensorHandle.hpp> #include <neon/workloads/NeonWorkloadUtils.hpp> #include <arm_compute/runtime/NEON/functions/NEConvolutionLayer.h> @@ -65,8 +66,8 @@ NeonConvolution2dWorkload::NeonConvolution2dWorkload( // todo: check tensor shapes match. - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonDequantizeWorkload.cpp b/src/backends/neon/workloads/NeonDequantizeWorkload.cpp index 8b229a1cda..9ae82ff79f 100644 --- a/src/backends/neon/workloads/NeonDequantizeWorkload.cpp +++ b/src/backends/neon/workloads/NeonDequantizeWorkload.cpp @@ -10,6 +10,7 @@ #include <arm_compute/runtime/NEON/functions/NEDequantizationLayer.h> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <neon/NeonTensorHandle.hpp> @@ -32,8 +33,8 @@ NeonDequantizeWorkload::NeonDequantizeWorkload(const DequantizeQueueDescriptor& { m_Data.ValidateInputsOutputs("NeonDequantizeWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); std::unique_ptr<arm_compute::NEDequantizationLayer> layer(new arm_compute::NEDequantizationLayer()); layer->configure(&input, &output); diff --git a/src/backends/neon/workloads/NeonDetectionPostProcessWorkload.cpp b/src/backends/neon/workloads/NeonDetectionPostProcessWorkload.cpp index 2ed47e4463..36f1cd98de 100644 --- a/src/backends/neon/workloads/NeonDetectionPostProcessWorkload.cpp +++ b/src/backends/neon/workloads/NeonDetectionPostProcessWorkload.cpp @@ -9,8 +9,7 @@ #include <aclCommon/ArmComputeTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> - -#include <boost/cast.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> namespace armnn { @@ -85,7 +84,7 @@ NeonDetectionPostProcessWorkload::NeonDetectionPostProcessWorkload( auto AclTensorRef = [](ITensorHandle* tensor) -> arm_compute::ITensor& { - return boost::polymorphic_downcast<IAclTensorHandle*>(tensor)->GetTensor(); + return PolymorphicDowncast<IAclTensorHandle*>(tensor)->GetTensor(); }; arm_compute::ITensor& boxEncodings = AclTensorRef(m_Data.m_Inputs[0]); diff --git a/src/backends/neon/workloads/NeonDivisionWorkload.cpp b/src/backends/neon/workloads/NeonDivisionWorkload.cpp index 6fdb455f25..fc353f136d 100644 --- a/src/backends/neon/workloads/NeonDivisionWorkload.cpp +++ b/src/backends/neon/workloads/NeonDivisionWorkload.cpp @@ -4,7 +4,9 @@ // #include "NeonDivisionWorkload.hpp" + #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> namespace armnn @@ -29,9 +31,9 @@ NeonDivisionWorkload::NeonDivisionWorkload(const DivisionQueueDescriptor& descri { m_Data.ValidateInputsOutputs("NeonDivisionWorkload", 2, 1); - arm_compute::ITensor& input0 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input0 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_DivLayer.configure(&input0, &input1, &output); } diff --git a/src/backends/neon/workloads/NeonFloorFloatWorkload.cpp b/src/backends/neon/workloads/NeonFloorFloatWorkload.cpp index 5b4e9094fd..c49df33a54 100644 --- a/src/backends/neon/workloads/NeonFloorFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonFloorFloatWorkload.cpp @@ -7,9 +7,9 @@ #include "NeonWorkloadUtils.hpp" -#include <arm_compute/runtime/NEON/functions/NEFloor.h> +#include <armnn/utility/PolymorphicDowncast.hpp> -#include <boost/polymorphic_cast.hpp> +#include <arm_compute/runtime/NEON/functions/NEFloor.h> namespace armnn { @@ -19,8 +19,8 @@ NeonFloorFloatWorkload::NeonFloorFloatWorkload(const FloorQueueDescriptor& descr { m_Data.ValidateInputsOutputs("NeonFloorFloatWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEFloor>(); layer->configure(&input, &output); diff --git a/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp index 338c7eb1f6..e808c60c0c 100644 --- a/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp +++ b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp @@ -8,6 +8,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h> @@ -51,8 +52,8 @@ NeonFullyConnectedWorkload::NeonFullyConnectedWorkload(const FullyConnectedQueue { m_Data.ValidateInputsOutputs("NeonFullyConnectedWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_WeightsTensor = std::make_unique<arm_compute::Tensor>(); BuildArmComputeTensor(*m_WeightsTensor, m_Data.m_Weight->GetTensorInfo()); diff --git a/src/backends/neon/workloads/NeonL2NormalizationFloatWorkload.cpp b/src/backends/neon/workloads/NeonL2NormalizationFloatWorkload.cpp index 9de6c82702..d54607d31e 100644 --- a/src/backends/neon/workloads/NeonL2NormalizationFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonL2NormalizationFloatWorkload.cpp @@ -8,6 +8,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/runtime/NEON/functions/NEL2NormalizeLayer.h> @@ -33,8 +34,8 @@ NeonL2NormalizationFloatWorkload::NeonL2NormalizationFloatWorkload(const L2Norma { m_Data.ValidateInputsOutputs("NeonL2NormalizationFloatWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonMaximumWorkload.cpp b/src/backends/neon/workloads/NeonMaximumWorkload.cpp index c433d81973..46d500bfdc 100644 --- a/src/backends/neon/workloads/NeonMaximumWorkload.cpp +++ b/src/backends/neon/workloads/NeonMaximumWorkload.cpp @@ -5,6 +5,7 @@ #include "NeonMaximumWorkload.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> namespace armnn @@ -29,9 +30,9 @@ NeonMaximumWorkload::NeonMaximumWorkload(const MaximumQueueDescriptor& descripto { m_Data.ValidateInputsOutputs("NeonMaximumWorkload", 2, 1); - arm_compute::ITensor& input0 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input0 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_MaxLayer.configure(&input0, &input1, &output); } diff --git a/src/backends/neon/workloads/NeonMinimumWorkload.cpp b/src/backends/neon/workloads/NeonMinimumWorkload.cpp index 2867a8079f..53e483a182 100644 --- a/src/backends/neon/workloads/NeonMinimumWorkload.cpp +++ b/src/backends/neon/workloads/NeonMinimumWorkload.cpp @@ -4,7 +4,9 @@ // #include "NeonMinimumWorkload.hpp" + #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> namespace armnn @@ -29,9 +31,9 @@ NeonMinimumWorkload::NeonMinimumWorkload(const MinimumQueueDescriptor& descripto { m_Data.ValidateInputsOutputs("NeonMinimumWorkload", 2, 1); - arm_compute::ITensor& input0 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input0 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_MinLayer.configure(&input0, &input1, &output); } diff --git a/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp b/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp index 66fbedfa63..d813970901 100644 --- a/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp +++ b/src/backends/neon/workloads/NeonMultiplicationWorkload.cpp @@ -7,6 +7,8 @@ #include "NeonWorkloadUtils.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h> namespace armnn @@ -37,9 +39,9 @@ NeonMultiplicationWorkload::NeonMultiplicationWorkload(const MultiplicationQueue { m_Data.ValidateInputsOutputs("NeonMultiplicationWorkload", 2, 1); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input2 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input2 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); // At the time of writing, configure() will fail if a rounding policy other than TO_ZERO is supplied to it, // when providing a scale of 1.0 for F32 tensors, even though the provided rounding policy appears to be diff --git a/src/backends/neon/workloads/NeonNegWorkload.cpp b/src/backends/neon/workloads/NeonNegWorkload.cpp index afe05583fd..06c146754c 100644 --- a/src/backends/neon/workloads/NeonNegWorkload.cpp +++ b/src/backends/neon/workloads/NeonNegWorkload.cpp @@ -9,8 +9,7 @@ #include <aclCommon/ArmComputeTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> - -#include <boost/cast.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> namespace armnn { @@ -28,8 +27,8 @@ NeonNegWorkload::NeonNegWorkload(const ElementwiseUnaryQueueDescriptor& descript { m_Data.ValidateInputsOutputs("NeonNegWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_NegLayer.configure(&input, &output); } diff --git a/src/backends/neon/workloads/NeonNormalizationFloatWorkload.cpp b/src/backends/neon/workloads/NeonNormalizationFloatWorkload.cpp index 8cb4ec975d..77fc429b95 100644 --- a/src/backends/neon/workloads/NeonNormalizationFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonNormalizationFloatWorkload.cpp @@ -8,6 +8,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeUtils.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/runtime/NEON/functions/NENormalizationLayer.h> @@ -77,8 +78,8 @@ NeonNormalizationFloatWorkload::NeonNormalizationFloatWorkload(const Normalizati throw InvalidArgumentException("Normalization requires input and output tensors to have equal dimensionality."); } - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonPooling2dWorkload.cpp b/src/backends/neon/workloads/NeonPooling2dWorkload.cpp index 9934c29a41..968d5ce02d 100644 --- a/src/backends/neon/workloads/NeonPooling2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonPooling2dWorkload.cpp @@ -7,6 +7,8 @@ #include "NeonWorkloadUtils.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <neon/NeonTensorHandle.hpp> #include <aclCommon/ArmComputeUtils.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> @@ -37,8 +39,8 @@ NeonPooling2dWorkload::NeonPooling2dWorkload( { m_Data.ValidateInputsOutputs("NeonPooling2dWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonPreluWorkload.cpp b/src/backends/neon/workloads/NeonPreluWorkload.cpp index 107090e704..8e6ea301de 100644 --- a/src/backends/neon/workloads/NeonPreluWorkload.cpp +++ b/src/backends/neon/workloads/NeonPreluWorkload.cpp @@ -5,7 +5,9 @@ #include "NeonPreluWorkload.hpp" #include "NeonWorkloadUtils.hpp" + #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/runtime/NEON/functions/NEPReluLayer.h> @@ -31,9 +33,9 @@ NeonPreluWorkload::NeonPreluWorkload(const PreluQueueDescriptor& descriptor, { m_Data.ValidateInputsOutputs("NeonPreluWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& alpha = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& alpha = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEPReluLayer>(); layer->configure(&input, &alpha, &output); diff --git a/src/backends/neon/workloads/NeonReshapeWorkload.cpp b/src/backends/neon/workloads/NeonReshapeWorkload.cpp index 659bb94723..8b11da7253 100644 --- a/src/backends/neon/workloads/NeonReshapeWorkload.cpp +++ b/src/backends/neon/workloads/NeonReshapeWorkload.cpp @@ -7,9 +7,9 @@ #include "NeonWorkloadUtils.hpp" -#include <arm_compute/runtime/NEON/functions/NEReshapeLayer.h> +#include <armnn/utility/PolymorphicDowncast.hpp> -#include <boost/polymorphic_cast.hpp> +#include <arm_compute/runtime/NEON/functions/NEReshapeLayer.h> namespace armnn { @@ -29,8 +29,8 @@ NeonReshapeWorkload::NeonReshapeWorkload(const ReshapeQueueDescriptor& descripto { m_Data.ValidateInputsOutputs("NeonReshapeWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEReshapeLayer>(); layer->configure(&input, &output); diff --git a/src/backends/neon/workloads/NeonResizeWorkload.cpp b/src/backends/neon/workloads/NeonResizeWorkload.cpp index e936ab7446..9e3be2655c 100644 --- a/src/backends/neon/workloads/NeonResizeWorkload.cpp +++ b/src/backends/neon/workloads/NeonResizeWorkload.cpp @@ -9,7 +9,9 @@ #include <aclCommon/ArmComputeUtils.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> + #include <neon/NeonTensorHandle.hpp> using namespace armnn::armcomputetensorutils; @@ -45,8 +47,8 @@ NeonResizeWorkload::NeonResizeWorkload(const ResizeQueueDescriptor& descriptor, { m_Data.ValidateInputsOutputs("NeonResizeWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/neon/workloads/NeonRsqrtWorkload.cpp b/src/backends/neon/workloads/NeonRsqrtWorkload.cpp index b6292833dd..44980df996 100644 --- a/src/backends/neon/workloads/NeonRsqrtWorkload.cpp +++ b/src/backends/neon/workloads/NeonRsqrtWorkload.cpp @@ -9,8 +9,8 @@ #include <aclCommon/ArmComputeTensorHandle.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> -#include <boost/cast.hpp> namespace armnn { @@ -28,8 +28,8 @@ NeonRsqrtWorkload::NeonRsqrtWorkload(const RsqrtQueueDescriptor& descriptor, con { m_Data.ValidateInputsOutputs("NeonRsqrtWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); m_RsqrtLayer.configure(&input, &output); } diff --git a/src/backends/neon/workloads/NeonSliceWorkload.cpp b/src/backends/neon/workloads/NeonSliceWorkload.cpp index 171edc6c59..32cc042eab 100644 --- a/src/backends/neon/workloads/NeonSliceWorkload.cpp +++ b/src/backends/neon/workloads/NeonSliceWorkload.cpp @@ -7,6 +7,8 @@ #include "NeonWorkloadUtils.hpp" +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <aclCommon/ArmComputeTensorUtils.hpp> #include <neon/NeonTensorHandle.hpp> @@ -37,8 +39,8 @@ NeonSliceWorkload::NeonSliceWorkload(const SliceQueueDescriptor& descriptor, { m_Data.ValidateInputsOutputs("NeonSliceWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::Coordinates starts; arm_compute::Coordinates ends; diff --git a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp index 152d19cc04..a4690a7985 100644 --- a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp @@ -8,6 +8,8 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> + #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h> namespace armnn @@ -20,8 +22,8 @@ NeonSoftmaxFloatWorkload::NeonSoftmaxFloatWorkload(const SoftmaxQueueDescriptor& m_Data.ValidateInputsOutputs("NeonSoftmaxFloatWorkload", 1, 1); // The ArmCompute softmax layer uses 2D input/output tensors, so flatten the first three dimensions. - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager); unsigned int aclAxis = ComputeSoftmaxAclAxis(m_Data.m_Parameters, info.m_InputTensorInfos[0]); diff --git a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp index 15a7066861..05d93b963c 100644 --- a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp +++ b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp @@ -7,6 +7,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h> @@ -20,8 +21,8 @@ NeonSoftmaxUint8Workload::NeonSoftmaxUint8Workload(const SoftmaxQueueDescriptor& { m_Data.ValidateInputsOutputs("NeonSoftmaxUint8Workload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); const auto outputQuantization = output.info()->quantization_info(); diff --git a/src/backends/neon/workloads/NeonSpaceToDepthWorkload.cpp b/src/backends/neon/workloads/NeonSpaceToDepthWorkload.cpp index a4204b21e6..2982cd181d 100644 --- a/src/backends/neon/workloads/NeonSpaceToDepthWorkload.cpp +++ b/src/backends/neon/workloads/NeonSpaceToDepthWorkload.cpp @@ -5,6 +5,8 @@ #include "NeonSpaceToDepthWorkload.hpp" #include "NeonWorkloadUtils.hpp" + +#include <armnn/utility/PolymorphicDowncast.hpp> #include <ResolveType.hpp> namespace armnn @@ -33,12 +35,12 @@ NeonSpaceToDepthWorkload::NeonSpaceToDepthWorkload(const SpaceToDepthQueueDescri arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); input.info()->set_data_layout(aclDataLayout); int32_t blockSize = boost::numeric_cast<int32_t>(desc.m_Parameters.m_BlockSize); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); output.info()->set_data_layout(aclDataLayout); m_Layer.reset(new arm_compute::NESpaceToDepthLayer()); diff --git a/src/backends/neon/workloads/NeonSplitterWorkload.cpp b/src/backends/neon/workloads/NeonSplitterWorkload.cpp index 224e97af2d..19fa7c6389 100644 --- a/src/backends/neon/workloads/NeonSplitterWorkload.cpp +++ b/src/backends/neon/workloads/NeonSplitterWorkload.cpp @@ -9,6 +9,7 @@ #include <aclCommon/ArmComputeTensorUtils.hpp> #include <aclCommon/ArmComputeUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <neon/NeonTensorHandle.hpp> @@ -74,7 +75,7 @@ NeonSplitterWorkload::NeonSplitterWorkload(const SplitterQueueDescriptor& descri return; } - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); std::vector<arm_compute::ITensor *> aclOutputs; for (auto output : m_Data.m_Outputs) diff --git a/src/backends/neon/workloads/NeonStridedSliceWorkload.cpp b/src/backends/neon/workloads/NeonStridedSliceWorkload.cpp index 356c0aea83..282005c7cc 100644 --- a/src/backends/neon/workloads/NeonStridedSliceWorkload.cpp +++ b/src/backends/neon/workloads/NeonStridedSliceWorkload.cpp @@ -9,6 +9,7 @@ #include <neon/NeonTensorHandle.hpp> #include <aclCommon/ArmComputeUtils.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/WorkloadUtils.hpp> namespace armnn @@ -50,8 +51,8 @@ NeonStridedSliceWorkload::NeonStridedSliceWorkload(const StridedSliceQueueDescri { m_Data.ValidateInputsOutputs("NeonStridedSliceWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::Coordinates starts; arm_compute::Coordinates ends; diff --git a/src/backends/neon/workloads/NeonSubtractionWorkload.cpp b/src/backends/neon/workloads/NeonSubtractionWorkload.cpp index f4b4707633..ccc2bfe58b 100644 --- a/src/backends/neon/workloads/NeonSubtractionWorkload.cpp +++ b/src/backends/neon/workloads/NeonSubtractionWorkload.cpp @@ -7,6 +7,7 @@ #include "NeonWorkloadUtils.hpp" #include <aclCommon/ArmComputeTensorUtils.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <backendsCommon/CpuTensorHandle.hpp> #include <arm_compute/runtime/NEON/functions/NEArithmeticSubtraction.h> @@ -34,9 +35,9 @@ NeonSubtractionWorkload::NeonSubtractionWorkload(const SubtractionQueueDescripto { m_Data.ValidateInputsOutputs("NeonSubtractionWorkload", 2, 1); - arm_compute::ITensor& input1 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& input2 = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input1 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& input2 = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[1])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); auto layer = std::make_unique<arm_compute::NEArithmeticSubtraction>(); layer->configure(&input1, &input2, &output, arm_compute::ConvertPolicy::SATURATE); diff --git a/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp index ffca2076fe..985f540e6a 100644 --- a/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp +++ b/src/backends/neon/workloads/NeonTransposeConvolution2dWorkload.cpp @@ -9,6 +9,7 @@ #include <Profiling.hpp> #include <armnn/Types.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <aclCommon/ArmComputeTensorUtils.hpp> @@ -60,8 +61,8 @@ NeonTransposeConvolution2dWorkload::NeonTransposeConvolution2dWorkload( { m_Data.ValidateInputsOutputs("NeonTransposeConvolution2dWorkload", 1, 1); - arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); diff --git a/src/backends/reference/test/RefCreateWorkloadTests.cpp b/src/backends/reference/test/RefCreateWorkloadTests.cpp index b83d205970..29bfbc0ee2 100644 --- a/src/backends/reference/test/RefCreateWorkloadTests.cpp +++ b/src/backends/reference/test/RefCreateWorkloadTests.cpp @@ -5,6 +5,7 @@ #include <test/CreateWorkload.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <reference/RefTensorHandle.hpp> #include <reference/RefWorkloadFactory.hpp> #include <reference/workloads/RefWorkloads.hpp> @@ -16,8 +17,8 @@ template<typename Workload> void CheckInputOutput(std::unique_ptr<Workload> workload, const TensorInfo& inputInfo, const TensorInfo& outputInfo) { auto queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((inputHandle->GetTensorInfo() == inputInfo)); BOOST_TEST((outputHandle->GetTensorInfo() == outputInfo)); } @@ -29,9 +30,9 @@ void CheckInputsOutput(std::unique_ptr<Workload> workload, const TensorInfo& outputInfo) { auto queueDescriptor = workload->GetData(); - auto inputHandle0 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle1 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto inputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[1]); + auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((inputHandle0->GetTensorInfo() == inputInfo0)); BOOST_TEST((inputHandle1->GetTensorInfo() == inputInfo1)); BOOST_TEST((outputHandle->GetTensorInfo() == outputInfo)); @@ -538,16 +539,16 @@ static void RefCreateSplitterWorkloadTest() // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). SplitterQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); + auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[0]); BOOST_TEST((inputHandle->GetTensorInfo() == TensorInfo({ 5, 7, 7 }, DataType))); - auto outputHandle0 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle0 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((outputHandle0->GetTensorInfo() == TensorInfo({ 1, 7, 7 }, DataType))); - auto outputHandle1 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]); + auto outputHandle1 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[1]); BOOST_TEST((outputHandle1->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); - auto outputHandle2 = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]); + auto outputHandle2 = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[2]); BOOST_TEST((outputHandle2->GetTensorInfo() == TensorInfo({ 2, 7, 7 }, DataType))); } @@ -910,7 +911,7 @@ static void RefCreateConstantWorkloadTest(const armnn::TensorShape& outputShape) // Check output is as expected auto queueDescriptor = workload->GetData(); - auto outputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((outputHandle->GetTensorInfo() == TensorInfo(outputShape, DataType))); } @@ -950,7 +951,7 @@ static void RefCreatePreluWorkloadTest(const armnn::TensorShape& inputShape, // Check output is as expected auto queueDescriptor = workload->GetData(); - auto outputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((outputHandle->GetTensorInfo() == TensorInfo(outputShape, dataType))); } @@ -1054,10 +1055,10 @@ static void RefCreateStackWorkloadTest(const armnn::TensorShape& inputShape, StackQueueDescriptor queueDescriptor = workload->GetData(); for (unsigned int i = 0; i < numInputs; ++i) { - auto inputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Inputs[i]); + auto inputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Inputs[i]); BOOST_TEST((inputHandle->GetTensorInfo() == TensorInfo(inputShape, DataType))); } - auto outputHandle = boost::polymorphic_downcast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); + auto outputHandle = PolymorphicDowncast<RefTensorHandle*>(queueDescriptor.m_Outputs[0]); BOOST_TEST((outputHandle->GetTensorInfo() == TensorInfo(outputShape, DataType))); } diff --git a/src/backends/reference/workloads/RefWorkloadUtils.hpp b/src/backends/reference/workloads/RefWorkloadUtils.hpp index f1b31571db..a36ed45970 100644 --- a/src/backends/reference/workloads/RefWorkloadUtils.hpp +++ b/src/backends/reference/workloads/RefWorkloadUtils.hpp @@ -9,12 +9,12 @@ #include <armnn/Tensor.hpp> #include <armnn/Types.hpp> +#include <armnn/utility/PolymorphicDowncast.hpp> #include <reference/RefTensorHandle.hpp> #include <BFloat16.hpp> #include <Half.hpp> -#include <boost/polymorphic_cast.hpp> namespace armnn { @@ -27,7 +27,7 @@ inline const TensorInfo& GetTensorInfo(const ITensorHandle* tensorHandle) { // We know that reference workloads use RefTensorHandles for inputs and outputs const RefTensorHandle* refTensorHandle = - boost::polymorphic_downcast<const RefTensorHandle*>(tensorHandle); + PolymorphicDowncast<const RefTensorHandle*>(tensorHandle); return refTensorHandle->GetTensorInfo(); } |