| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "CpuTensorHandle.hpp" |
| |
| #include <Layer.hpp> |
| #include <LayersFwd.hpp> |
| |
| #include <armnn/Types.hpp> |
| #include <armnn/LayerSupport.hpp> |
| #include <armnn/ILayerSupport.hpp> |
| |
| #include <backendsCommon/BackendRegistry.hpp> |
| #include <backendsCommon/WorkloadFactory.hpp> |
| #include <backendsCommon/IBackendInternal.hpp> |
| |
| #include <boost/cast.hpp> |
| #include <boost/iterator/transform_iterator.hpp> |
| |
| #include <cstring> |
| #include <sstream> |
| |
| namespace armnn |
| { |
| |
| namespace |
| { |
| |
| const TensorInfo OverrideDataType(const TensorInfo& info, Optional<DataType> type) |
| { |
| if (!type) |
| { |
| return info; |
| } |
| |
| return TensorInfo(info.GetShape(), type.value(), info.GetQuantizationScale(), info.GetQuantizationOffset()); |
| } |
| |
| Optional<DataType> GetBiasTypeFromWeightsType(Optional<DataType> weightsType) |
| { |
| if (!weightsType) |
| { |
| return weightsType; |
| } |
| |
| switch(weightsType.value()) |
| { |
| case DataType::Float16: |
| case DataType::Float32: |
| return weightsType; |
| case DataType::QuantisedAsymm8: |
| return DataType::Signed32; |
| default: |
| BOOST_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); |
| } |
| return EmptyOptional(); |
| } |
| |
| } // anonymous namespace |
| |
| bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, |
| const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported) |
| { |
| Optional<std::string&> reason = outReasonIfUnsupported; |
| bool result; |
| const Layer& layer = *(boost::polymorphic_downcast<const Layer*>(&connectableLayer)); |
| |
| auto const& backendRegistry = BackendRegistryInstance(); |
| if (!backendRegistry.IsBackendRegistered(backendId)) |
| { |
| std::stringstream ss; |
| ss << connectableLayer.GetName() << " is not supported on " << backendId |
| << " because this backend is not registered."; |
| |
| outReasonIfUnsupported = ss.str(); |
| return false; |
| } |
| |
| auto backendFactory = backendRegistry.GetFactory(backendId); |
| auto backendObject = backendFactory(); |
| auto layerSupportObject = backendObject->GetLayerSupport(); |
| |
| switch(layer.GetType()) |
| { |
| case LayerType::Activation: |
| { |
| auto cLayer = boost::polymorphic_downcast<const ActivationLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsActivationSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Addition: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsAdditionSupported( |
| OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::BatchNormalization: |
| { |
| auto cLayer = boost::polymorphic_downcast<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(); |
| const TensorInfo& var = cLayer->m_Variance->GetTensorInfo(); |
| const TensorInfo& beta = cLayer->m_Beta->GetTensorInfo(); |
| const TensorInfo& gamma = cLayer->m_Gamma->GetTensorInfo(); |
| result = layerSupportObject->IsBatchNormalizationSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| OverrideDataType(mean, dataType), |
| OverrideDataType(var, dataType), |
| OverrideDataType(beta, dataType), |
| OverrideDataType(gamma, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::BatchToSpaceNd: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| auto cLayer = boost::polymorphic_downcast<const BatchToSpaceNdLayer*>(&layer); |
| |
| result = layerSupportObject->IsBatchToSpaceNdSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Constant: |
| { |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsConstantSupported(OverrideDataType(output, dataType), reason); |
| break; |
| } |
| case LayerType::ConvertFp16ToFp32: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsConvertFp16ToFp32Supported(input, output, reason); |
| break; |
| } |
| case LayerType::ConvertFp32ToFp16: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsConvertFp32ToFp16Supported(input, output, reason); |
| break; |
| } |
| case LayerType::Convolution2d: |
| { |
| auto cLayer = boost::polymorphic_downcast<const Convolution2dLayer*>(&layer); |
| |
| const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); |
| |
| const Convolution2dDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // Construct optional biases object based on the value of m_BiasEnabled |
| Optional<TensorInfo> biases; |
| if (descriptor.m_BiasEnabled) |
| { |
| biases = |
| OverrideDataType(cLayer->m_Bias->GetTensorInfo(), GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| result = layerSupportObject->IsConvolution2dSupported( |
| input, |
| output, |
| descriptor, |
| OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType), |
| biases, |
| reason); |
| break; |
| } |
| case LayerType::MemCopy: |
| { |
| // MemCopy supported for CpuRef, CpuAcc and GpuAcc backends, |
| // (also treat Undefined as CpuRef to avoid breaking lots of Unit tests). |
| result = backendId == Compute::CpuRef || backendId == Compute::Undefined |
| || backendId == Compute::CpuAcc || backendId == Compute::GpuAcc; |
| reason.value() = "Unsupported backend type"; |
| break; |
| } |
| case LayerType::DepthwiseConvolution2d: |
| { |
| auto cLayer = boost::polymorphic_downcast<const DepthwiseConvolution2dLayer*>(&layer); |
| const TensorInfo& input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo& output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); |
| |
| const DepthwiseConvolution2dDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // Construct optional biases object based on the value of m_BiasEnabled |
| Optional<TensorInfo> biases; |
| if (descriptor.m_BiasEnabled) |
| { |
| biases = |
| OverrideDataType(cLayer->m_Bias->GetTensorInfo(), GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| result = layerSupportObject->IsDepthwiseConvolutionSupported( |
| input, |
| output, |
| descriptor, |
| OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType), |
| biases, |
| reason); |
| break; |
| } |
| case LayerType::FakeQuantization: |
| { |
| auto cLayer = boost::polymorphic_downcast<const FakeQuantizationLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject->IsFakeQuantizationSupported(OverrideDataType(input, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Floor: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsFloorSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::FullyConnected: |
| { |
| auto cLayer = boost::polymorphic_downcast<const FullyConnectedLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| BOOST_ASSERT(cLayer->m_Weight.get() != nullptr); |
| |
| TensorInfo biasInfo; |
| const TensorInfo * biasInfoPtr = nullptr; |
| static const TensorInfo dummyFloat16Bias(TensorShape({1,1,1,1}), DataType::Float16); |
| static const TensorInfo dummyFloat32Bias(TensorShape({1,1,1,1}), DataType::Float32); |
| static const TensorInfo dummyQA8Bias(TensorShape({1,1,1,1}), DataType::Signed32); |
| |
| const FullyConnectedDescriptor& descriptor = cLayer->GetParameters(); |
| if (descriptor.m_BiasEnabled) |
| { |
| BOOST_ASSERT(cLayer->m_Bias.get() != nullptr); |
| biasInfo = OverrideDataType(cLayer->m_Bias->GetTensorInfo(), GetBiasTypeFromWeightsType(dataType)); |
| biasInfoPtr = &biasInfo; |
| } |
| else |
| { |
| // If biases are not enabled pass a dummy tensorinfo for the validation |
| switch(input.GetDataType()) |
| { |
| case DataType::Float16: |
| { |
| biasInfoPtr = &dummyFloat16Bias; |
| break; |
| } |
| case DataType::Float32: |
| { |
| biasInfoPtr = &dummyFloat32Bias; |
| break; |
| } |
| case DataType::QuantisedAsymm8: |
| { |
| biasInfoPtr = &dummyQA8Bias; |
| break; |
| } |
| default: |
| { |
| BOOST_ASSERT_MSG(false, "Unexpected bias type"); |
| } |
| } |
| } |
| |
| result = layerSupportObject->IsFullyConnectedSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType), |
| *biasInfoPtr, |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::Input: |
| { |
| const TensorInfo& input = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsInputSupported(OverrideDataType(input, dataType), reason); |
| break; |
| } |
| case LayerType::L2Normalization: |
| { |
| auto cLayer = boost::polymorphic_downcast<const L2NormalizationLayer*>(&layer); |
| const L2NormalizationDescriptor& descriptor = cLayer->GetParameters(); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject->IsL2NormalizationSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::Lstm: |
| { |
| auto cLayer = boost::polymorphic_downcast<const LstmLayer*>(&layer); |
| const LstmDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // All inputs. |
| const TensorInfo& input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo& outputStateIn = OverrideDataType(layer.GetInputSlot(1).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo& cellStateIn = OverrideDataType(layer.GetInputSlot(2).GetConnection()->GetTensorInfo(), |
| dataType); |
| // All outputs |
| const TensorInfo& scratchBuffer = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| const TensorInfo& outputStateOut = OverrideDataType(layer.GetOutputSlot(1).GetTensorInfo(), dataType); |
| const TensorInfo& cellStateOut = OverrideDataType(layer.GetOutputSlot(2).GetTensorInfo(), dataType); |
| const TensorInfo& output = OverrideDataType(layer.GetOutputSlot(3).GetTensorInfo(), dataType); |
| |
| // Basic parameters |
| const TensorInfo& inputToForgetWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_InputToForgetWeights->GetTensorInfo(), dataType); |
| const TensorInfo& inputToCellWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_InputToCellWeights->GetTensorInfo(), dataType); |
| const TensorInfo& inputToOutputWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_InputToOutputWeights->GetTensorInfo(), dataType); |
| const TensorInfo& recurrentToForgetWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToForgetWeights->GetTensorInfo(), dataType); |
| const TensorInfo& recurrentToCellWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToCellWeights->GetTensorInfo(), dataType); |
| const TensorInfo& recurrentToOutputWeights |
| = OverrideDataType(cLayer->m_BasicParameters.m_RecurrentToOutputWeights->GetTensorInfo(), dataType); |
| const TensorInfo& forgetGateBias |
| = OverrideDataType(cLayer->m_BasicParameters.m_ForgetGateBias->GetTensorInfo(), dataType); |
| const TensorInfo& cellBias |
| = OverrideDataType(cLayer->m_BasicParameters.m_CellBias->GetTensorInfo(), dataType); |
| const TensorInfo& outputGateBias |
| = OverrideDataType(cLayer->m_BasicParameters.m_OutputGateBias->GetTensorInfo(), dataType); |
| |
| // Optional parameters |
| const TensorInfo* inputToInputWeights = nullptr; |
| const TensorInfo* recurrentToInputWeights = nullptr; |
| const TensorInfo* cellToInputWeights = nullptr; |
| const TensorInfo* inputGateBias = nullptr; |
| const TensorInfo* projectionWeights = nullptr; |
| const TensorInfo* projectionBias = nullptr; |
| const TensorInfo* cellToForgetWeights = nullptr; |
| const TensorInfo* cellToOutputWeights = nullptr; |
| |
| TensorInfo optInputToInputWeights; |
| TensorInfo optRecurrentToInputWeights; |
| TensorInfo optCellToInputWeights; |
| TensorInfo optInputGateBias; |
| TensorInfo optProjectionWeights; |
| TensorInfo optProjectionBias; |
| TensorInfo optCellToForgetWeights; |
| TensorInfo optCellToOutputWeights; |
| |
| if(!descriptor.m_CifgEnabled) |
| { |
| optInputToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputToInputWeights->GetTensorInfo(), dataType); |
| inputToInputWeights = &optInputToInputWeights; |
| |
| optRecurrentToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(), dataType); |
| recurrentToInputWeights = &optRecurrentToInputWeights; |
| if (cLayer->m_CifgParameters.m_CellToInputWeights != nullptr) |
| { |
| optCellToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_CellToInputWeights->GetTensorInfo(), dataType); |
| cellToInputWeights = &optCellToInputWeights; |
| } |
| optInputGateBias = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(), dataType); |
| inputGateBias = &optInputGateBias; |
| } |
| |
| if(descriptor.m_ProjectionEnabled) |
| { |
| optProjectionWeights = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(), dataType); |
| projectionWeights = &optProjectionWeights; |
| if (cLayer->m_ProjectionParameters.m_ProjectionBias != nullptr) |
| { |
| optProjectionBias = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(), dataType); |
| projectionBias = &optProjectionBias; |
| } |
| } |
| |
| if(descriptor.m_PeepholeEnabled) |
| { |
| optCellToForgetWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(), dataType); |
| cellToForgetWeights = &optCellToForgetWeights; |
| optCellToOutputWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(), dataType); |
| cellToOutputWeights = &optCellToOutputWeights; |
| } |
| |
| result = layerSupportObject->IsLstmSupported( |
| input, |
| outputStateIn, |
| cellStateIn, |
| scratchBuffer, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| inputToForgetWeights, |
| inputToCellWeights, |
| inputToOutputWeights, |
| recurrentToForgetWeights, |
| recurrentToCellWeights, |
| recurrentToOutputWeights, |
| forgetGateBias, |
| cellBias, |
| outputGateBias, |
| inputToInputWeights, |
| recurrentToInputWeights, |
| cellToInputWeights, |
| inputGateBias, |
| projectionWeights, |
| projectionBias, |
| cellToForgetWeights, |
| cellToOutputWeights, |
| reason); |
| break; |
| } |
| case LayerType::Maximum: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject->IsMaximumSupported(OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Merger: |
| { |
| auto cLayer = boost::polymorphic_downcast<const MergerLayer*>(&layer); |
| |
| // Get vector of all inputs. |
| auto getTensorInfo = [&dataType](const InputSlot& slot) |
| { |
| return OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType); |
| }; |
| auto beginI = boost::make_transform_iterator(layer.GetInputSlots().begin(), getTensorInfo); |
| auto endI = boost::make_transform_iterator(layer.GetInputSlots().end(), getTensorInfo); |
| std::vector<TensorInfo> inputs(beginI, endI); |
| |
| auto getTensorInfoPtr = [](const TensorInfo& info) |
| { |
| return &info; |
| }; |
| auto beginPtr = boost::make_transform_iterator(inputs.begin(), getTensorInfoPtr); |
| auto endPtr = boost::make_transform_iterator(inputs.end(), getTensorInfoPtr); |
| std::vector<const TensorInfo*> inputPtrs(beginPtr, endPtr); |
| |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject->IsMergerSupported(inputPtrs, output, cLayer->GetParameters(), reason); |
| break; |
| } |
| case LayerType::Multiplication: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsMultiplicationSupported( |
| OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Normalization: |
| { |
| auto cLayer = boost::polymorphic_downcast<const NormalizationLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsNormalizationSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Output: |
| { |
| const TensorInfo& output = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject->IsOutputSupported(OverrideDataType(output, dataType), reason); |
| break; |
| } |
| case LayerType::Permute: |
| { |
| auto cLayer = boost::polymorphic_downcast<const PermuteLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsPermuteSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Pad: |
| { |
| auto cLayer = boost::polymorphic_downcast<const PadLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsPadSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Pooling2d: |
| { |
| auto cLayer = boost::polymorphic_downcast<const Pooling2dLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsPooling2dSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Division: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsDivisionSupported( |
| OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Reshape: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject->IsReshapeSupported(OverrideDataType(input, dataType), reason); |
| break; |
| } |
| case LayerType::ResizeBilinear: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject->IsResizeBilinearSupported(OverrideDataType(input, dataType), reason); |
| break; |
| } |
| case LayerType::Softmax: |
| { |
| auto cLayer = boost::polymorphic_downcast<const SoftmaxLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsSoftmaxSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::SpaceToBatchNd: |
| { |
| auto cLayer = boost::polymorphic_downcast<const SpaceToBatchNdLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsSpaceToBatchNdSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Splitter: |
| { |
| auto cLayer = boost::polymorphic_downcast<const SplitterLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject->IsSplitterSupported(OverrideDataType(input, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::StridedSlice: |
| { |
| auto cLayer = boost::polymorphic_downcast<const StridedSliceLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsStridedSliceSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Subtraction: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsSubtractionSupported( |
| OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Mean: |
| { |
| auto cLayer = boost::polymorphic_downcast<const MeanLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsMeanSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Minimum: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject->IsMinimumSupported(OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| default: |
| { |
| BOOST_ASSERT_MSG(false, "WorkloadFactory did not recognise type of layer."); |
| reason.value() = "Unrecognised layer type"; |
| result = false; |
| break; |
| } |
| } |
| return result; |
| } |
| |
| bool IWorkloadFactory::IsLayerSupported(const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported) |
| { |
| auto layer = boost::polymorphic_downcast<const Layer*>(&connectableLayer); |
| return IsLayerSupported(layer->GetBackendId(), connectableLayer, dataType, outReasonIfUnsupported); |
| } |
| |
| } |
