| // |
| // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include <Layer.hpp> |
| #include <LayersFwd.hpp> |
| |
| #include <armnn/Types.hpp> |
| #include <armnn/backends/IBackendInternal.hpp> |
| #include <armnn/backends/ILayerSupport.hpp> |
| #include <armnn/BackendHelper.hpp> |
| #include <armnn/BackendRegistry.hpp> |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| #include <armnn/utility/TransformIterator.hpp> |
| |
| #include <armnn/backends/WorkloadFactory.hpp> |
| #include <armnn/backends/TensorHandle.hpp> |
| |
| #include <sstream> |
| |
| namespace armnn |
| { |
| |
| namespace |
| { |
| using LayerList = std::list<Layer*>; |
| using Iterator = LayerList::const_iterator; // Const so pointers in the list can't be modified externally. |
| |
| const TensorInfo OverrideDataType(const TensorInfo& info, Optional<DataType> type) |
| { |
| if (!type) |
| { |
| return info; |
| } |
| |
| return TensorInfo(info.GetShape(), |
| type.value(), |
| info.GetQuantizationScale(), |
| info.GetQuantizationOffset(), |
| info.IsConstant()); |
| } |
| |
| } // anonymous namespace |
| |
| inline armnn::Optional<armnn::DataType> GetBiasTypeFromWeightsType(armnn::Optional<armnn::DataType> weightsType) |
| { |
| if (!weightsType) |
| { |
| return weightsType; |
| } |
| |
| switch(weightsType.value()) |
| { |
| case armnn::DataType::BFloat16: |
| case armnn::DataType::Float16: |
| case armnn::DataType::Float32: |
| return weightsType; |
| case armnn::DataType::QAsymmS8: |
| case armnn::DataType::QAsymmU8: |
| case armnn::DataType::QSymmS8: |
| case armnn::DataType::QSymmS16: |
| return armnn::DataType::Signed32; |
| default: |
| ARMNN_ASSERT_MSG(false, "GetBiasTypeFromWeightsType(): Unsupported data type."); |
| } |
| return armnn::EmptyOptional(); |
| } |
| |
| |
| bool IWorkloadFactory::IsLayerConfigurationSupported(const BackendId& backendId, |
| const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported, |
| const ModelOptions& modelOptions) |
| { |
| Optional<std::string&> reason = outReasonIfUnsupported; |
| bool result; |
| const Layer& layer = *(PolymorphicDowncast<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 = LayerSupportHandle(backendObject->GetLayerSupport(modelOptions), backendId); |
| |
| switch(layer.GetType()) |
| { |
| case LayerType::Activation: |
| { |
| auto cLayer = PolymorphicDowncast<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::ArgMinMax: |
| { |
| auto cLayer = PolymorphicDowncast<const ArgMinMaxLayer*>(&layer); |
| const ArgMinMaxDescriptor& descriptor = cLayer->GetParameters(); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsArgMinMaxSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, DataType::Signed32), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::BatchMatMul: |
| { |
| auto cLayer = PolymorphicDowncast<const BatchMatMulLayer*>(&layer); |
| const BatchMatMulDescriptor& descriptor = cLayer->GetParameters(); |
| |
| 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.IsBatchMatMulSupported( |
| OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::BatchNormalization: |
| { |
| 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(); |
| 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 = PolymorphicDowncast<const BatchToSpaceNdLayer*>(&layer); |
| |
| result = layerSupportObject.IsBatchToSpaceNdSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Cast: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsCastSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::ChannelShuffle: |
| { |
| auto cLayer = PolymorphicDowncast<const ChannelShuffleLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| |
| const ChannelShuffleDescriptor descriptor = cLayer->GetParameters(); |
| |
| result = layerSupportObject.IsChannelShuffleSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::Comparison: |
| { |
| auto cLayer = PolymorphicDowncast<const ComparisonLayer*>(&layer); |
| |
| 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.IsComparisonSupported(OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, DataType::Boolean), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Constant: |
| { |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsConstantSupported(OverrideDataType(output, dataType), reason); |
| break; |
| } |
| case LayerType::ConvertBf16ToFp32: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsConvertBf16ToFp32Supported(input, output, 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::ConvertFp32ToBf16: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsConvertFp32ToBf16Supported(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 = PolymorphicDowncast<const Convolution2dLayer*>(&layer); |
| |
| const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| ARMNN_ASSERT_MSG(layer.GetInputSlot(1).GetConnection(), |
| "Convolution2dLayer: Weights should be connected as a Constant Layer."); |
| const TensorInfo weights = OverrideDataType(layer.GetInputSlot(1).GetConnection()->GetTensorInfo(), |
| dataType); |
| |
| const Convolution2dDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // Construct optional biases object based on the value of m_BiasEnabled |
| Optional<TensorInfo> biases; |
| if (descriptor.m_BiasEnabled) |
| { |
| ARMNN_ASSERT_MSG(layer.GetInputSlot(2).GetConnection(), |
| "Convolution2dLayer: Bias should be connected as a Constant Layer."); |
| biases = OverrideDataType(layer.GetInputSlot(2).GetConnection()->GetTensorInfo(), |
| GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| result = layerSupportObject.IsConvolution2dSupported( |
| input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reason); |
| break; |
| } |
| case LayerType::Convolution3d: |
| { |
| auto cLayer = PolymorphicDowncast<const Convolution3dLayer*>(&layer); |
| |
| const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| |
| ARMNN_ASSERT_MSG(layer.GetInputSlot(1).GetConnection(), |
| "Convolution3dLayer: Weights should be connected as a Constant Layer."); |
| const TensorInfo weights = OverrideDataType(layer.GetInputSlot(1).GetConnection()->GetTensorInfo(), |
| dataType); |
| |
| const Convolution3dDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // Construct optional biases object based on the value of m_BiasEnabled |
| Optional<TensorInfo> biases; |
| if (descriptor.m_BiasEnabled) |
| { |
| biases = OverrideDataType(layer.GetInputSlot(2).GetConnection()->GetTensorInfo(), |
| GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| result = layerSupportObject.IsConvolution3dSupported( |
| input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reason); |
| break; |
| } |
| case LayerType::Debug: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsDebugSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::DepthToSpace: |
| { |
| auto cLayer = PolymorphicDowncast<const DepthToSpaceLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsDepthToSpaceSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::DepthwiseConvolution2d: |
| { |
| 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); |
| const TensorInfo& weights = OverrideDataType(layer.GetInputSlot(1).GetConnection()->GetTensorInfo(), |
| dataType); |
| |
| ARMNN_ASSERT(cLayer->GetInputSlot(1).GetConnection() != 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->GetInputSlot(2).GetConnection()->GetTensorInfo(), |
| GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| result = layerSupportObject.IsDepthwiseConvolutionSupported(input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reason); |
| break; |
| } |
| case LayerType::Dequantize: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsDequantizeSupported(input, |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::DetectionPostProcess: |
| { |
| 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(); |
| |
| const TensorInfo& detectionBoxes = layer.GetOutputSlot(0).GetTensorInfo(); |
| const TensorInfo& detectionClasses = layer.GetOutputSlot(1).GetTensorInfo(); |
| const TensorInfo& detectionScores = layer.GetOutputSlot(2).GetTensorInfo(); |
| const TensorInfo& numDetections = layer.GetOutputSlot(3).GetTensorInfo(); |
| |
| const DetectionPostProcessDescriptor& descriptor = cLayer->GetParameters(); |
| result = layerSupportObject.IsDetectionPostProcessSupported(boxEncodings, |
| scores, |
| anchors, |
| detectionBoxes, |
| detectionClasses, |
| detectionScores, |
| numDetections, |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::ElementwiseUnary: |
| { |
| auto cLayer = PolymorphicDowncast<const ElementwiseUnaryLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsElementwiseUnarySupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Fill: |
| { |
| auto cLayer = PolymorphicDowncast<const FillLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| const FillDescriptor& descriptor = cLayer->GetParameters(); |
| |
| result = layerSupportObject.IsFillSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::FakeQuantization: |
| { |
| auto cLayer = PolymorphicDowncast<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 = PolymorphicDowncast<const FullyConnectedLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| const FullyConnectedDescriptor& descriptor = cLayer->GetParameters(); |
| TensorInfo weightsInfo; |
| const TensorInfo* weightsInfoPtr = nullptr; |
| |
| weightsInfo = OverrideDataType(layer.GetInputSlot(1).GetConnection()->GetTensorInfo(), dataType); |
| weightsInfoPtr = &weightsInfo; |
| |
| TensorInfo biasInfo; |
| const TensorInfo* biasInfoPtr = nullptr; |
| static const TensorInfo dummyBFloat16Bias(TensorShape({1,1,1,1}), DataType::BFloat16); |
| 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); |
| |
| if (descriptor.m_BiasEnabled) |
| { |
| biasInfo = OverrideDataType(layer.GetInputSlot(2).GetConnection()->GetTensorInfo(), dataType); |
| biasInfoPtr = &biasInfo; |
| } |
| else |
| { |
| // If biases are not enabled pass a dummy tensorinfo for the validation |
| switch(input.GetDataType()) |
| { |
| case DataType::BFloat16: |
| { |
| biasInfoPtr = &dummyBFloat16Bias; |
| break; |
| } |
| case DataType::Float16: |
| { |
| biasInfoPtr = &dummyFloat16Bias; |
| break; |
| } |
| case DataType::Float32: |
| { |
| biasInfoPtr = &dummyFloat32Bias; |
| break; |
| } |
| case DataType::QAsymmU8: |
| case DataType::QAsymmS8: |
| case DataType::QSymmS8: |
| case DataType::QSymmS16: |
| { |
| biasInfoPtr = &dummyQA8Bias; |
| break; |
| } |
| default: |
| { |
| ARMNN_ASSERT_MSG(false, "Unexpected bias type"); |
| } |
| } |
| } |
| result = layerSupportObject.IsFullyConnectedSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| *weightsInfoPtr, |
| *biasInfoPtr, |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::Gather: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| auto cLayer = PolymorphicDowncast<const GatherLayer*>(&layer); |
| const GatherDescriptor& descriptor = cLayer->GetParameters(); |
| result = layerSupportObject.IsGatherSupported(OverrideDataType(input0, dataType), |
| input1, |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::GatherNd: |
| { |
| 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.IsGatherNdSupported(OverrideDataType(input0, dataType), |
| input1, |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Input: |
| { |
| const TensorInfo& input = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsInputSupported(OverrideDataType(input, dataType), reason); |
| break; |
| } |
| case LayerType::InstanceNormalization: |
| { |
| auto cLayer = PolymorphicDowncast<const InstanceNormalizationLayer*>(&layer); |
| const InstanceNormalizationDescriptor& descriptor = cLayer->GetParameters(); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsInstanceNormalizationSupported( |
| OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| descriptor, |
| reason); |
| break; |
| } |
| case LayerType::L2Normalization: |
| { |
| auto cLayer = PolymorphicDowncast<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::LogicalBinary: |
| { |
| auto cLayer = PolymorphicDowncast<const LogicalBinaryLayer*>(&layer); |
| |
| 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.IsLogicalBinarySupported(input0, |
| input1, |
| output, |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::LogSoftmax: |
| { |
| auto cLayer = PolymorphicDowncast<const LogSoftmaxLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsLogSoftmaxSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Lstm: |
| { |
| auto cLayer = PolymorphicDowncast<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); |
| |
| LstmInputParamsInfo paramsInfo; |
| |
| paramsInfo.m_InputToForgetWeights = &inputToForgetWeights; |
| paramsInfo.m_InputToCellWeights = &inputToCellWeights; |
| paramsInfo.m_InputToOutputWeights = &inputToOutputWeights; |
| paramsInfo.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| paramsInfo.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| paramsInfo.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| paramsInfo.m_ForgetGateBias = &forgetGateBias; |
| paramsInfo.m_CellBias = &cellBias; |
| paramsInfo.m_OutputGateBias = &outputGateBias; |
| |
| |
| // Optional parameters |
| TensorInfo optInputToInputWeights; |
| TensorInfo optRecurrentToInputWeights; |
| TensorInfo optCellToInputWeights; |
| TensorInfo optInputGateBias; |
| TensorInfo optProjectionWeights; |
| TensorInfo optProjectionBias; |
| TensorInfo optCellToForgetWeights; |
| TensorInfo optCellToOutputWeights; |
| TensorInfo optInputLayerNormWeights; |
| TensorInfo optForgetLayerNormWeights; |
| TensorInfo optCellLayerNormWeights; |
| TensorInfo optOutputLayerNormWeights; |
| |
| if(!descriptor.m_CifgEnabled) |
| { |
| optInputToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputToInputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_InputToInputWeights = &optInputToInputWeights; |
| |
| optRecurrentToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_RecurrentToInputWeights = &optRecurrentToInputWeights; |
| optInputGateBias = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(), dataType); |
| paramsInfo.m_InputGateBias = &optInputGateBias; |
| } |
| |
| if(descriptor.m_ProjectionEnabled) |
| { |
| optProjectionWeights = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_ProjectionWeights = &optProjectionWeights; |
| if (cLayer->m_ProjectionParameters.m_ProjectionBias != nullptr) |
| { |
| optProjectionBias = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(), dataType); |
| paramsInfo.m_ProjectionBias = &optProjectionBias; |
| } |
| } |
| |
| if(descriptor.m_PeepholeEnabled) |
| { |
| if(!descriptor.m_CifgEnabled) |
| { |
| optCellToInputWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(), |
| dataType); |
| paramsInfo.m_CellToInputWeights = &optCellToInputWeights; |
| } |
| optCellToForgetWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellToForgetWeights = &optCellToForgetWeights; |
| optCellToOutputWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellToOutputWeights = &optCellToOutputWeights; |
| } |
| |
| if(descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| optInputLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_InputLayerNormWeights = &optInputLayerNormWeights; |
| } |
| |
| optForgetLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_ForgetLayerNormWeights = &optForgetLayerNormWeights; |
| |
| optCellLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellLayerNormWeights = &optCellLayerNormWeights; |
| |
| optOutputLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_OutputLayerNormWeights = &optOutputLayerNormWeights; |
| } |
| |
| result = layerSupportObject.IsLstmSupported( |
| input, |
| outputStateIn, |
| cellStateIn, |
| scratchBuffer, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| paramsInfo, |
| 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::MemCopy: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsMemCopySupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::MemImport: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsMemImportSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Merge: |
| { |
| 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.IsMergeSupported(OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Concat: |
| { |
| auto cLayer = PolymorphicDowncast<const ConcatLayer*>(&layer); |
| |
| // Get vector of all inputs. |
| auto getTensorInfo = [&dataType](const InputSlot& slot) |
| { |
| return OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType); |
| }; |
| |
| auto beginI = MakeTransformIterator(layer.GetInputSlots().begin(), getTensorInfo); |
| auto endI = MakeTransformIterator(layer.GetInputSlots().end(), getTensorInfo); |
| std::vector<TensorInfo> inputs(beginI, endI); |
| |
| auto getTensorInfoPtr = [](const TensorInfo& info) |
| { |
| return &info; |
| }; |
| |
| auto beginPtr = MakeTransformIterator(inputs.begin(), getTensorInfoPtr); |
| auto endPtr = MakeTransformIterator(inputs.end(), getTensorInfoPtr); |
| std::vector<const TensorInfo*> inputPtrs(beginPtr, endPtr); |
| |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsConcatSupported(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 = 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), |
| 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 = 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Pad: |
| { |
| auto cLayer = PolymorphicDowncast<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 = 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Pooling3d: |
| { |
| auto cLayer = PolymorphicDowncast<const Pooling3dLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsPooling3dSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::PreCompiled: |
| { |
| auto cLayer = PolymorphicDowncast<const PreCompiledLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| result = layerSupportObject.IsPreCompiledSupported(OverrideDataType(input, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Quantize: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsQuantizeSupported(input, output, reason); |
| break; |
| } |
| case LayerType::QLstm: |
| { |
| auto cLayer = PolymorphicDowncast<const QLstmLayer*>(&layer); |
| const QLstmDescriptor& descriptor = cLayer->GetParameters(); |
| |
| // Inputs |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& previousOutputIn = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& previousCellStateIn = layer.GetInputSlot(2).GetConnection()->GetTensorInfo(); |
| |
| // Outputs |
| const TensorInfo& outputStateOut = layer.GetOutputSlot(0).GetTensorInfo(); |
| const TensorInfo& cellStateOut = layer.GetOutputSlot(1).GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(2).GetTensorInfo(); |
| |
| // Lstm parameters |
| LstmInputParamsInfo paramsInfo; |
| |
| // Basic parameters |
| ARMNN_ASSERT(cLayer->m_BasicParameters.m_InputToForgetWeights.get() != nullptr); |
| ARMNN_ASSERT(cLayer->m_BasicParameters.m_InputToCellWeights.get() != nullptr); |
| ARMNN_ASSERT(cLayer->m_BasicParameters.m_InputToOutputWeights.get() != nullptr); |
| paramsInfo.m_InputToForgetWeights = &cLayer->m_BasicParameters.m_InputToForgetWeights->GetTensorInfo(); |
| paramsInfo.m_InputToCellWeights = &cLayer->m_BasicParameters.m_InputToCellWeights->GetTensorInfo(); |
| paramsInfo.m_InputToOutputWeights = &cLayer->m_BasicParameters.m_InputToOutputWeights->GetTensorInfo(); |
| |
| paramsInfo.m_RecurrentToForgetWeights = |
| &cLayer->m_BasicParameters.m_RecurrentToForgetWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToCellWeights = |
| &cLayer->m_BasicParameters.m_RecurrentToCellWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToOutputWeights = |
| &cLayer->m_BasicParameters.m_RecurrentToOutputWeights->GetTensorInfo(); |
| |
| paramsInfo.m_ForgetGateBias = &cLayer->m_BasicParameters.m_ForgetGateBias->GetTensorInfo(); |
| paramsInfo.m_CellBias = &cLayer->m_BasicParameters.m_CellBias->GetTensorInfo(); |
| paramsInfo.m_OutputGateBias = &cLayer->m_BasicParameters.m_OutputGateBias->GetTensorInfo(); |
| |
| if(!descriptor.m_CifgEnabled) |
| { |
| paramsInfo.m_InputToInputWeights = &cLayer->m_CifgParameters.m_InputToInputWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToInputWeights = |
| &cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(); |
| paramsInfo.m_InputGateBias = &cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(); |
| } |
| |
| if(descriptor.m_ProjectionEnabled) |
| { |
| paramsInfo.m_ProjectionWeights = &cLayer->m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(); |
| |
| // Projection bias is optional even if projection is enabled |
| if (cLayer->m_ProjectionParameters.m_ProjectionBias != nullptr) |
| { |
| paramsInfo.m_ProjectionBias = &cLayer->m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(); |
| } |
| } |
| |
| if(descriptor.m_PeepholeEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| paramsInfo.m_CellToInputWeights = |
| &cLayer->m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(); |
| } |
| |
| paramsInfo.m_CellToForgetWeights = |
| &cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(); |
| paramsInfo.m_CellToOutputWeights = &cLayer->m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(); |
| } |
| |
| if(descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| paramsInfo.m_InputLayerNormWeights = |
| &cLayer->m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(); |
| } |
| |
| paramsInfo.m_ForgetLayerNormWeights = |
| &cLayer->m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(); |
| paramsInfo.m_CellLayerNormWeights = |
| &cLayer->m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(); |
| paramsInfo.m_OutputLayerNormWeights = |
| &cLayer->m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(); |
| } |
| |
| result = layerSupportObject.IsQLstmSupported(input, |
| previousOutputIn, |
| previousCellStateIn, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| paramsInfo, |
| reason); |
| break; |
| } |
| case LayerType::QuantizedLstm: |
| { |
| auto cLayer = PolymorphicDowncast<const QuantizedLstmLayer*>(&layer); |
| |
| // Inputs |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& previousCellStateIn = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& previousOutputIn = layer.GetInputSlot(2).GetConnection()->GetTensorInfo(); |
| |
| // Outputs |
| const TensorInfo& cellStateOut = layer.GetOutputSlot(0).GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(1).GetTensorInfo(); |
| |
| // QuantizedLstm parameters |
| QuantizedLstmInputParamsInfo paramsInfo; |
| |
| paramsInfo.m_InputToInputWeights = |
| &cLayer->m_QuantizedLstmParameters.m_InputToInputWeights->GetTensorInfo(); |
| paramsInfo.m_InputToForgetWeights = |
| &cLayer->m_QuantizedLstmParameters.m_InputToForgetWeights->GetTensorInfo(); |
| paramsInfo.m_InputToCellWeights = |
| &cLayer->m_QuantizedLstmParameters.m_InputToCellWeights->GetTensorInfo(); |
| paramsInfo.m_InputToOutputWeights = |
| &cLayer->m_QuantizedLstmParameters.m_InputToOutputWeights->GetTensorInfo(); |
| |
| paramsInfo.m_RecurrentToInputWeights = |
| &cLayer->m_QuantizedLstmParameters.m_RecurrentToInputWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToForgetWeights = |
| &cLayer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToCellWeights = |
| &cLayer->m_QuantizedLstmParameters.m_RecurrentToCellWeights->GetTensorInfo(); |
| paramsInfo.m_RecurrentToOutputWeights = |
| &cLayer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights->GetTensorInfo(); |
| |
| paramsInfo.m_InputGateBias = |
| &cLayer->m_QuantizedLstmParameters.m_InputGateBias->GetTensorInfo(); |
| paramsInfo.m_ForgetGateBias = |
| &cLayer->m_QuantizedLstmParameters.m_ForgetGateBias->GetTensorInfo(); |
| paramsInfo.m_CellBias = |
| &cLayer->m_QuantizedLstmParameters.m_CellBias->GetTensorInfo(); |
| paramsInfo.m_OutputGateBias = |
| &cLayer->m_QuantizedLstmParameters.m_OutputGateBias->GetTensorInfo();; |
| |
| result = layerSupportObject.IsQuantizedLstmSupported(input, |
| previousCellStateIn, |
| previousOutputIn, |
| cellStateOut, |
| output, |
| paramsInfo, |
| 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::Rank: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsRankSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Reshape: |
| { |
| 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Resize: |
| { |
| 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Shape: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsShapeSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Slice: |
| { |
| auto cLayer = PolymorphicDowncast<const SliceLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsSliceSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Softmax: |
| { |
| 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::SpaceToBatchNd: |
| { |
| 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::SpaceToDepth: |
| { |
| auto cLayer = PolymorphicDowncast<const SpaceToDepthLayer*>(&layer); |
| |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsSpaceToDepthSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Splitter: |
| { |
| auto cLayer = PolymorphicDowncast<const SplitterLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| |
| // Get vector of all outputs. |
| auto getTensorInfo = [&dataType](const OutputSlot& slot) |
| { |
| return OverrideDataType(slot.GetTensorInfo(), dataType); |
| }; |
| auto beginI = MakeTransformIterator(layer.GetOutputSlots().begin(), getTensorInfo); |
| auto endI = MakeTransformIterator(layer.GetOutputSlots().end(), getTensorInfo); |
| std::vector<TensorInfo> outputs(beginI, endI); |
| |
| const std::vector<std::reference_wrapper<TensorInfo>> outputPtrs(outputs.begin(), outputs.end()); |
| |
| result = layerSupportObject.IsSplitterSupported(OverrideDataType(input, dataType), |
| outputPtrs, |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::Stack: |
| { |
| auto cLayer = PolymorphicDowncast<const StackLayer*>(&layer); |
| |
| // Get vector of all inputs. |
| auto getTensorInfo = [&dataType](const InputSlot& slot) |
| { |
| return OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType); |
| }; |
| auto beginI = MakeTransformIterator(layer.GetInputSlots().begin(), getTensorInfo); |
| auto endI = MakeTransformIterator(layer.GetInputSlots().end(), getTensorInfo); |
| std::vector<TensorInfo> inputs(beginI, endI); |
| |
| auto getTensorInfoPtr = [](const TensorInfo& info) |
| { |
| return &info; |
| }; |
| auto beginPtr = MakeTransformIterator(inputs.begin(), getTensorInfoPtr); |
| auto endPtr = MakeTransformIterator(inputs.end(), getTensorInfoPtr); |
| std::vector<const TensorInfo*> inputPtrs(beginPtr, endPtr); |
| |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsStackSupported(inputPtrs, output, cLayer->GetParameters(), reason); |
| |
| break; |
| } |
| case LayerType::StandIn: |
| { |
| auto cLayer = PolymorphicDowncast<const StandInLayer*>(&layer); |
| |
| // Get vector of all inputs. |
| auto getTensorInfoIn = [&dataType](const InputSlot& slot) |
| { |
| return OverrideDataType(slot.GetConnectedOutputSlot()->GetTensorInfo(), dataType); |
| }; |
| auto getTensorInfoOut = [&dataType](const OutputSlot& slot) |
| { |
| return OverrideDataType(slot.GetTensorInfo(), dataType); |
| }; |
| auto beginI = MakeTransformIterator(layer.GetInputSlots().begin(), getTensorInfoIn); |
| auto endI = MakeTransformIterator(layer.GetInputSlots().end(), getTensorInfoIn); |
| std::vector<TensorInfo> inputs(beginI, endI); |
| |
| auto beginO = MakeTransformIterator(layer.GetOutputSlots().begin(), getTensorInfoOut); |
| auto endO = MakeTransformIterator(layer.GetOutputSlots().end(), getTensorInfoOut); |
| std::vector<TensorInfo> outputs(beginO, endO); |
| |
| |
| auto getTensorInfoPtr = [](const TensorInfo& info) |
| { |
| return &info; |
| }; |
| auto beginPtrI = MakeTransformIterator(inputs.begin(), getTensorInfoPtr); |
| auto endPtrI = MakeTransformIterator(inputs.end(), getTensorInfoPtr); |
| std::vector<const TensorInfo*> inputPtrs(beginPtrI, endPtrI); |
| |
| auto beginPtrO = MakeTransformIterator(outputs.begin(), getTensorInfoPtr); |
| auto endPtrO = MakeTransformIterator(outputs.end(), getTensorInfoPtr); |
| std::vector<const TensorInfo*> outputPtrs(beginPtrO, endPtrO); |
| |
| |
| result = layerSupportObject.IsStandInSupported(inputPtrs, |
| outputPtrs, |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::StridedSlice: |
| { |
| 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), |
| 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::Switch: |
| { |
| const TensorInfo& input0 = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& input1 = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output0 = layer.GetOutputSlot(0).GetTensorInfo(); |
| const TensorInfo& output1 = layer.GetOutputSlot(1).GetTensorInfo(); |
| result = layerSupportObject.IsSwitchSupported(OverrideDataType(input0, dataType), |
| OverrideDataType(input1, dataType), |
| OverrideDataType(output0, dataType), |
| OverrideDataType(output1, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Mean: |
| { |
| auto cLayer = PolymorphicDowncast<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; |
| } |
| case LayerType::Prelu: |
| { |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& alpha = layer.GetInputSlot(1).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| result = layerSupportObject.IsPreluSupported(OverrideDataType(input, dataType), |
| OverrideDataType(alpha, dataType), |
| OverrideDataType(output, dataType), |
| reason); |
| break; |
| } |
| case LayerType::Transpose: |
| { |
| 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), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::TransposeConvolution2d: |
| { |
| auto cLayer = PolymorphicDowncast<const TransposeConvolution2dLayer*>(&layer); |
| |
| const TensorInfo input = OverrideDataType(layer.GetInputSlot(0).GetConnection()->GetTensorInfo(), |
| dataType); |
| const TensorInfo output = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| |
| const TransposeConvolution2dDescriptor& descriptor = cLayer->GetParameters(); |
| |
| Optional<TensorInfo> biases; |
| if (descriptor.m_BiasEnabled) |
| { |
| ARMNN_ASSERT(cLayer->m_Bias.get() != nullptr); |
| biases = OverrideDataType(cLayer->m_Bias->GetTensorInfo(), |
| GetBiasTypeFromWeightsType(dataType)); |
| } |
| |
| ARMNN_ASSERT(cLayer->m_Weight.get() != nullptr); |
| const TensorInfo weights = OverrideDataType(cLayer->m_Weight->GetTensorInfo(), dataType); |
| |
| result = layerSupportObject.IsTransposeConvolution2dSupported(input, |
| output, |
| descriptor, |
| weights, |
| biases, |
| reason); |
| |
| break; |
| } |
| case LayerType::Reduce: |
| { |
| auto cLayer = PolymorphicDowncast<const ReduceLayer*>(&layer); |
| const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); |
| const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); |
| |
| result = layerSupportObject.IsReduceSupported(OverrideDataType(input, dataType), |
| OverrideDataType(output, dataType), |
| cLayer->GetParameters(), |
| reason); |
| break; |
| } |
| case LayerType::UnidirectionalSequenceLstm: |
| { |
| auto cLayer = PolymorphicDowncast<const UnidirectionalSequenceLstmLayer*>(&layer); |
| const UnidirectionalSequenceLstmDescriptor& 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); |
| // Outputs |
| const TensorInfo& outputStateOut = OverrideDataType(layer.GetOutputSlot(0).GetTensorInfo(), dataType); |
| const TensorInfo& cellStateOut = OverrideDataType(layer.GetOutputSlot(1).GetTensorInfo(), dataType); |
| const TensorInfo& output = OverrideDataType(layer.GetOutputSlot(2).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); |
| |
| LstmInputParamsInfo paramsInfo; |
| |
| paramsInfo.m_InputToForgetWeights = &inputToForgetWeights; |
| paramsInfo.m_InputToCellWeights = &inputToCellWeights; |
| paramsInfo.m_InputToOutputWeights = &inputToOutputWeights; |
| paramsInfo.m_RecurrentToForgetWeights = &recurrentToForgetWeights; |
| paramsInfo.m_RecurrentToCellWeights = &recurrentToCellWeights; |
| paramsInfo.m_RecurrentToOutputWeights = &recurrentToOutputWeights; |
| paramsInfo.m_ForgetGateBias = &forgetGateBias; |
| paramsInfo.m_CellBias = &cellBias; |
| paramsInfo.m_OutputGateBias = &outputGateBias; |
| |
| // Optional parameters |
| TensorInfo optInputToInputWeights; |
| TensorInfo optRecurrentToInputWeights; |
| TensorInfo optCellToInputWeights; |
| TensorInfo optInputGateBias; |
| TensorInfo optProjectionWeights; |
| TensorInfo optProjectionBias; |
| TensorInfo optCellToForgetWeights; |
| TensorInfo optCellToOutputWeights; |
| TensorInfo optInputLayerNormWeights; |
| TensorInfo optForgetLayerNormWeights; |
| TensorInfo optCellLayerNormWeights; |
| TensorInfo optOutputLayerNormWeights; |
| |
| if(!descriptor.m_CifgEnabled) |
| { |
| optInputToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputToInputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_InputToInputWeights = &optInputToInputWeights; |
| |
| optRecurrentToInputWeights = |
| OverrideDataType(cLayer->m_CifgParameters.m_RecurrentToInputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_RecurrentToInputWeights = &optRecurrentToInputWeights; |
| optInputGateBias = |
| OverrideDataType(cLayer->m_CifgParameters.m_InputGateBias->GetTensorInfo(), dataType); |
| paramsInfo.m_InputGateBias = &optInputGateBias; |
| } |
| |
| if(descriptor.m_ProjectionEnabled) |
| { |
| optProjectionWeights = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_ProjectionWeights = &optProjectionWeights; |
| if (cLayer->m_ProjectionParameters.m_ProjectionBias != nullptr) |
| { |
| optProjectionBias = |
| OverrideDataType(cLayer->m_ProjectionParameters.m_ProjectionBias->GetTensorInfo(), dataType); |
| paramsInfo.m_ProjectionBias = &optProjectionBias; |
| } |
| } |
| |
| if(descriptor.m_PeepholeEnabled) |
| { |
| if(!descriptor.m_CifgEnabled) |
| { |
| optCellToInputWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToInputWeights->GetTensorInfo(), |
| dataType); |
| paramsInfo.m_CellToInputWeights = &optCellToInputWeights; |
| } |
| optCellToForgetWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToForgetWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellToForgetWeights = &optCellToForgetWeights; |
| optCellToOutputWeights = |
| OverrideDataType(cLayer->m_PeepholeParameters.m_CellToOutputWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellToOutputWeights = &optCellToOutputWeights; |
| } |
| |
| if(descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| optInputLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_InputLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_InputLayerNormWeights = &optInputLayerNormWeights; |
| } |
| |
| optForgetLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_ForgetLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_ForgetLayerNormWeights = &optForgetLayerNormWeights; |
| |
| optCellLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_CellLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_CellLayerNormWeights = &optCellLayerNormWeights; |
| |
| optOutputLayerNormWeights = OverrideDataType( |
| cLayer->m_LayerNormParameters.m_OutputLayerNormWeights->GetTensorInfo(), dataType); |
| paramsInfo.m_OutputLayerNormWeights = &optOutputLayerNormWeights; |
| } |
| |
| result = layerSupportObject.IsUnidirectionalSequenceLstmSupported(input, |
| outputStateIn, |
| cellStateIn, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| paramsInfo, |
| reason); |
| break; |
| } |
| default: |
| { |
| ARMNN_ASSERT_MSG(false, "WorkloadFactory did not recognise type of layer."); |
| reason.value() = "Unrecognised layer type"; |
| result = false; |
| break; |
| } |
| } |
| return result; |
| } |
| |
| bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, |
| const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported) |
| { |
| return IsLayerConfigurationSupported(backendId, connectableLayer, dataType, outReasonIfUnsupported); |
| } |
| |
| bool IWorkloadFactory::IsLayerSupported(const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported) |
| { |
| auto layer = PolymorphicDowncast<const Layer*>(&connectableLayer); |
| return IsLayerConfigurationSupported(layer->GetBackendId(), connectableLayer, dataType, outReasonIfUnsupported); |
| } |
| |
| // TODO merge with defaulted modelOptions above |
| bool IWorkloadFactory::IsLayerSupported(const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported, |
| const ModelOptions& modelOptions) |
| { |
| auto layer = PolymorphicDowncast<const Layer*>(&connectableLayer); |
| return IsLayerConfigurationSupported(layer->GetBackendId(), |
| connectableLayer, |
| dataType, |
| outReasonIfUnsupported, |
| modelOptions); |
| } |
| |
| bool IWorkloadFactory::IsLayerSupported(const BackendId& backendId, |
| const IConnectableLayer& connectableLayer, |
| Optional<DataType> dataType, |
| std::string& outReasonIfUnsupported, |
| const ModelOptions& modelOptions) |
| { |
| return IsLayerConfigurationSupported(backendId, |
| connectableLayer, |
| dataType, |
| outReasonIfUnsupported, |
| modelOptions); |
| } |
| ARMNN_NO_DEPRECATE_WARN_BEGIN |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateWorkload(LayerType type, |
| const QueueDescriptor& descriptor, |
| const WorkloadInfo& info) const |
| { |
| switch(type) |
| { |
| case LayerType::Activation : |
| { |
| auto activationQueueDescriptor = PolymorphicDowncast<const ActivationQueueDescriptor*>(&descriptor); |
| return CreateActivation(*activationQueueDescriptor, info); |
| } |
| case LayerType::Addition : |
| { |
| auto additionQueueDescriptor = PolymorphicDowncast<const AdditionQueueDescriptor*>(&descriptor); |
| return CreateAddition(*additionQueueDescriptor, info); |
| } |
| case LayerType::ArgMinMax : |
| { |
| auto argMinMaxQueueDescriptor = PolymorphicDowncast<const ArgMinMaxQueueDescriptor*>(&descriptor); |
| return CreateArgMinMax(*argMinMaxQueueDescriptor, info); |
| } |
| case LayerType::BatchNormalization : |
| { |
| auto batchNormQueueDescriptor = PolymorphicDowncast<const BatchNormalizationQueueDescriptor*>(&descriptor); |
| return CreateBatchNormalization(*batchNormQueueDescriptor, info); |
| } |
| case LayerType::BatchToSpaceNd : |
| { |
| auto batchToSpaceNdQueueDescriptor |
| = PolymorphicDowncast<const BatchToSpaceNdQueueDescriptor*>(&descriptor); |
| return CreateBatchToSpaceNd(*batchToSpaceNdQueueDescriptor, info); |
| } |
| case LayerType::Cast : |
| { |
| auto castQueueDescriptor = PolymorphicDowncast<const CastQueueDescriptor*>(&descriptor); |
| return CreateCast(*castQueueDescriptor, info); |
| } |
| case LayerType::ChannelShuffle : |
| { |
| auto channelShuffleQueueDescriptor |
| = PolymorphicDowncast<const ChannelShuffleQueueDescriptor*>(&descriptor); |
| return CreateChannelShuffle(*channelShuffleQueueDescriptor, info); |
| } |
| case LayerType::Comparison : |
| { |
| auto comparisonQueueDescriptor = PolymorphicDowncast<const ComparisonQueueDescriptor*>(&descriptor); |
| return CreateComparison(*comparisonQueueDescriptor, info); |
| } |
| case LayerType::Concat : |
| { |
| auto concatQueueDescriptor = PolymorphicDowncast<const ConcatQueueDescriptor*>(&descriptor); |
| return CreateConcat(*concatQueueDescriptor, info); |
| } |
| case LayerType::Constant : |
| { |
| auto constantQueueDescriptor = PolymorphicDowncast<const ConstantQueueDescriptor*>(&descriptor); |
| return CreateConstant(*constantQueueDescriptor, info); |
| } |
| case LayerType::ConvertBf16ToFp32 : |
| { |
| auto convertBf16ToFp32QueueDescriptor |
| = PolymorphicDowncast<const ConvertBf16ToFp32QueueDescriptor*>(&descriptor); |
| return CreateConvertBf16ToFp32(*convertBf16ToFp32QueueDescriptor, info); |
| } |
| case LayerType::ConvertFp16ToFp32: |
| { |
| auto convertFp16ToFp32QueueDescriptor |
| = PolymorphicDowncast<const ConvertFp16ToFp32QueueDescriptor*>(&descriptor); |
| return CreateConvertFp16ToFp32(*convertFp16ToFp32QueueDescriptor, info); |
| } |
| case LayerType::ConvertFp32ToBf16: |
| { |
| auto convertFp32ToBf16QueueDescriptor |
| = PolymorphicDowncast<const ConvertFp32ToBf16QueueDescriptor*>(&descriptor); |
| return CreateConvertFp32ToBf16(*convertFp32ToBf16QueueDescriptor, info); |
| } |
| case LayerType::ConvertFp32ToFp16: |
| { |
| auto convertFp32ToFp16QueueDescriptor |
| = PolymorphicDowncast<const ConvertFp32ToFp16QueueDescriptor*>(&descriptor); |
| return CreateConvertFp32ToFp16(*convertFp32ToFp16QueueDescriptor, info); |
| } |
| case LayerType::Convolution2d: |
| { |
| auto convolution2dQueueDescriptor = PolymorphicDowncast<const Convolution2dQueueDescriptor*>(&descriptor); |
| return CreateConvolution2d(*convolution2dQueueDescriptor, info); |
| } |
| case LayerType::Convolution3d: |
| { |
| auto convolution3dQueueDescriptor = PolymorphicDowncast<const Convolution3dQueueDescriptor*>(&descriptor); |
| return CreateConvolution3d(*convolution3dQueueDescriptor, info); |
| } |
| case LayerType::Debug: |
| { |
| auto debugQueueDescriptor = PolymorphicDowncast<const DebugQueueDescriptor*>(&descriptor); |
| return CreateDebug(*debugQueueDescriptor, info); |
| } |
| case LayerType::DepthToSpace: |
| { |
| auto depthToSpaceQueueDescriptor = PolymorphicDowncast<const DepthToSpaceQueueDescriptor*>(&descriptor); |
| return CreateDepthToSpace(*depthToSpaceQueueDescriptor, info); |
| } |
| case LayerType::DepthwiseConvolution2d: |
| { |
| auto depthwiseConvolution2DQueueDescriptor |
| = PolymorphicDowncast<const DepthwiseConvolution2dQueueDescriptor*>(&descriptor); |
| return CreateDepthwiseConvolution2d(*depthwiseConvolution2DQueueDescriptor, info); |
| } |
| case LayerType::Dequantize: |
| { |
| auto dequantizeQueueDescriptor = PolymorphicDowncast<const DequantizeQueueDescriptor*>(&descriptor); |
| return CreateDequantize(*dequantizeQueueDescriptor, info); |
| } |
| case LayerType::DetectionPostProcess: |
| { |
| auto detectionPostProcessQueueDescriptor |
| = PolymorphicDowncast<const DetectionPostProcessQueueDescriptor*>(&descriptor); |
| return CreateDetectionPostProcess(*detectionPostProcessQueueDescriptor, info); |
| } |
| case LayerType::Division: |
| { |
| auto divisionQueueDescriptor = PolymorphicDowncast<const DivisionQueueDescriptor*>(&descriptor); |
| return CreateDivision(*divisionQueueDescriptor, info); |
| } |
| case LayerType::ElementwiseUnary: |
| { |
| auto elementwiseUnaryQueueDescriptor |
| = PolymorphicDowncast<const ElementwiseUnaryQueueDescriptor*>(&descriptor); |
| return CreateElementwiseUnary(*elementwiseUnaryQueueDescriptor, info); |
| |
| } |
| case LayerType::FakeQuantization: |
| { |
| auto fakeQuantizationQueueDescriptor |
| = PolymorphicDowncast<const FakeQuantizationQueueDescriptor*>(&descriptor); |
| return CreateFakeQuantization(*fakeQuantizationQueueDescriptor, info); |
| } |
| case LayerType::Fill: |
| { |
| auto fillQueueDescriptor = PolymorphicDowncast<const FillQueueDescriptor*>(&descriptor); |
| return CreateFill(*fillQueueDescriptor, info); |
| } |
| case LayerType::Floor: |
| { |
| auto floorQueueDescriptor = PolymorphicDowncast<const FloorQueueDescriptor*>(&descriptor); |
| return CreateFloor(*floorQueueDescriptor, info); |
| } |
| case LayerType::FullyConnected: |
| { |
| auto fullyConnectedQueueDescriptor |
| = PolymorphicDowncast<const FullyConnectedQueueDescriptor*>(&descriptor); |
| return CreateFullyConnected(*fullyConnectedQueueDescriptor, info); |
| } |
| case LayerType::Gather: |
| { |
| auto gatherQueueDescriptor = PolymorphicDowncast<const GatherQueueDescriptor*>(&descriptor); |
| return CreateGather(*gatherQueueDescriptor, info); |
| } |
| case LayerType::Input: |
| { |
| auto inputQueueDescriptor = PolymorphicDowncast<const InputQueueDescriptor*>(&descriptor); |
| return CreateInput(*inputQueueDescriptor, info); |
| } |
| case LayerType::InstanceNormalization: |
| { |
| auto instanceNormalizationQueueDescriptor |
| = PolymorphicDowncast<const InstanceNormalizationQueueDescriptor*>(&descriptor); |
| return CreateInstanceNormalization(*instanceNormalizationQueueDescriptor, info); |
| } |
| case LayerType::L2Normalization: |
| { |
| auto l2NormalizationQueueDescriptor |
| = PolymorphicDowncast<const L2NormalizationQueueDescriptor*>(&descriptor); |
| return CreateL2Normalization(*l2NormalizationQueueDescriptor, info); |
| } |
| case LayerType::LogicalBinary: |
| { |
| auto logicalBinaryQueueDescriptor = PolymorphicDowncast<const LogicalBinaryQueueDescriptor*>(&descriptor); |
| return CreateLogicalBinary(*logicalBinaryQueueDescriptor, info); |
| } |
| case LayerType::LogSoftmax: |
| { |
| auto logSoftmaxQueueDescriptor = PolymorphicDowncast<const LogSoftmaxQueueDescriptor*>(&descriptor); |
| return CreateLogSoftmax(*logSoftmaxQueueDescriptor, info); |
| } |
| case LayerType::Lstm: |
| { |
| auto lstmQueueDescriptor = PolymorphicDowncast<const LstmQueueDescriptor*>(&descriptor); |
| return CreateLstm(*lstmQueueDescriptor, info); |
| } |
| case LayerType::Maximum: |
| { |
| auto maximumQueueDescriptor = PolymorphicDowncast<const MaximumQueueDescriptor*>(&descriptor); |
| return CreateMaximum(*maximumQueueDescriptor, info); |
| } |
| case LayerType::Mean: |
| { |
| auto meanQueueDescriptor = PolymorphicDowncast<const MeanQueueDescriptor*>(&descriptor); |
| return CreateMean(*meanQueueDescriptor, info); |
| } |
| case LayerType::MemCopy: |
| { |
| auto memCopyQueueDescriptor = PolymorphicDowncast<const MemCopyQueueDescriptor*>(&descriptor); |
| return CreateMemCopy(*memCopyQueueDescriptor, info); |
| } |
| case LayerType::MemImport: |
| { |
| auto memImportQueueDescriptor = PolymorphicDowncast<const MemImportQueueDescriptor*>(&descriptor); |
| return CreateMemImport(*memImportQueueDescriptor, info); |
| } |
| case LayerType::Minimum: |
| { |
| auto minimumQueueDescriptor = PolymorphicDowncast<const MinimumQueueDescriptor*>(&descriptor); |
| return CreateMinimum(*minimumQueueDescriptor, info); |
| } |
| case LayerType::Multiplication: |
| { |
| auto multiplicationQueueDescriptor |
| = PolymorphicDowncast<const MultiplicationQueueDescriptor*>(&descriptor); |
| return CreateMultiplication(*multiplicationQueueDescriptor, info); |
| } |
| case LayerType::Normalization: |
| { |
| auto normalizationQueueDescriptor = PolymorphicDowncast<const NormalizationQueueDescriptor*>(&descriptor); |
| return CreateNormalization(*normalizationQueueDescriptor, info); |
| } |
| case LayerType::Output: |
| { |
| auto outputQueueDescriptor = PolymorphicDowncast<const OutputQueueDescriptor*>(&descriptor); |
| return CreateOutput(*outputQueueDescriptor, info); |
| } |
| case LayerType::Pad: |
| { |
| auto padQueueDescriptor = PolymorphicDowncast<const PadQueueDescriptor*>(&descriptor); |
| return CreatePad(*padQueueDescriptor, info); |
| } |
| case LayerType::Permute: |
| { |
| auto permuteQueueDescriptor = PolymorphicDowncast<const PermuteQueueDescriptor*>(&descriptor); |
| return CreatePermute(*permuteQueueDescriptor, info); |
| } |
| case LayerType::Pooling2d: |
| { |
| auto pooling2dQueueDescriptor = PolymorphicDowncast<const Pooling2dQueueDescriptor*>(&descriptor); |
| return CreatePooling2d(*pooling2dQueueDescriptor, info); |
| } |
| case LayerType::Pooling3d: |
| { |
| auto pooling3dQueueDescriptor = PolymorphicDowncast<const Pooling3dQueueDescriptor*>(&descriptor); |
| return CreatePooling3d(*pooling3dQueueDescriptor, info); |
| } |
| case LayerType::PreCompiled: |
| { |
| auto preCompiledQueueDescriptor = PolymorphicDowncast<const PreCompiledQueueDescriptor*>(&descriptor); |
| return CreatePreCompiled(*preCompiledQueueDescriptor, info); |
| } |
| case LayerType::Prelu: |
| { |
| auto preluQueueDescriptor = PolymorphicDowncast<const PreluQueueDescriptor*>(&descriptor); |
| return CreatePrelu(*preluQueueDescriptor, info); |
| } |
| case LayerType::QLstm: |
| { |
| auto qlstmQueueDescriptor = PolymorphicDowncast<const QLstmQueueDescriptor*>(&descriptor); |
| return CreateQLstm(*qlstmQueueDescriptor, info); |
| } |
| case LayerType::Quantize: |
| { |
| auto quantizeQueueDescriptor = PolymorphicDowncast<const QuantizeQueueDescriptor*>(&descriptor); |
| return CreateQuantize(*quantizeQueueDescriptor, info); |
| } |
| case LayerType::Rank: |
| { |
| auto rankQueueDescriptor = PolymorphicDowncast<const RankQueueDescriptor*>(&descriptor); |
| return CreateRank(*rankQueueDescriptor, info); |
| } |
| case LayerType::Reduce: |
| { |
| auto reduceQueueDescriptor = PolymorphicDowncast<const ReduceQueueDescriptor*>(&descriptor); |
| return CreateReduce(*reduceQueueDescriptor, info); |
| } |
| case LayerType::Reshape: |
| { |
| auto reshapeQueueDescriptor = PolymorphicDowncast<const ReshapeQueueDescriptor*>(&descriptor); |
| return CreateReshape(*reshapeQueueDescriptor, info); |
| } |
| case LayerType::Resize: |
| { |
| auto resizeQueueDescriptor = PolymorphicDowncast<const ResizeQueueDescriptor*>(&descriptor); |
| return CreateResize(*resizeQueueDescriptor, info); |
| } |
| case LayerType::Shape: |
| { |
| auto shapeQueueDescriptor = PolymorphicDowncast<const ShapeQueueDescriptor*>(&descriptor); |
| return CreateShape(*shapeQueueDescriptor, info); |
| } |
| case LayerType::Slice: |
| { |
| auto sliceQueueDescriptor = PolymorphicDowncast<const SliceQueueDescriptor*>(&descriptor); |
| return CreateSlice(*sliceQueueDescriptor, info); |
| } |
| case LayerType::Softmax: |
| { |
| auto softmaxQueueDescriptor = PolymorphicDowncast<const SoftmaxQueueDescriptor*>(&descriptor); |
| return CreateSoftmax(*softmaxQueueDescriptor, info); |
| } |
| case LayerType::SpaceToBatchNd: |
| { |
| auto spaceToBatchNdQueueDescriptor |
| = PolymorphicDowncast<const SpaceToBatchNdQueueDescriptor*>(&descriptor); |
| return CreateSpaceToBatchNd(*spaceToBatchNdQueueDescriptor, info); |
| } |
| case LayerType::SpaceToDepth: |
| { |
| auto spaceToDepthQueueDescriptor = PolymorphicDowncast<const SpaceToDepthQueueDescriptor*>(&descriptor); |
| return CreateSpaceToDepth(*spaceToDepthQueueDescriptor, info); |
| } |
| case LayerType::Splitter: |
| { |
| auto splitterQueueDescriptor = PolymorphicDowncast<const SplitterQueueDescriptor*>(&descriptor); |
| return CreateSplitter(*splitterQueueDescriptor, info); |
| } |
| case LayerType::Stack: |
| { |
| auto stackQueueDescriptor = PolymorphicDowncast<const StackQueueDescriptor*>(&descriptor); |
| return CreateStack(*stackQueueDescriptor, info); |
| } |
| case LayerType::StridedSlice: |
| { |
| auto stridedSliceQueueDescriptor = PolymorphicDowncast<const StridedSliceQueueDescriptor*>(&descriptor); |
| return CreateStridedSlice(*stridedSliceQueueDescriptor, info); |
| } |
| case LayerType::Subtraction: |
| { |
| auto subtractionQueueDescriptor = PolymorphicDowncast<const SubtractionQueueDescriptor*>(&descriptor); |
| return CreateSubtraction(*subtractionQueueDescriptor, info); |
| } |
| case LayerType::Transpose: |
| { |
| auto transposeQueueDescriptor = PolymorphicDowncast<const TransposeQueueDescriptor*>(&descriptor); |
| return CreateTranspose(*transposeQueueDescriptor, info); |
| } |
| case LayerType::TransposeConvolution2d: |
| { |
| auto transposeConvolution2dQueueDescriptor |
| = PolymorphicDowncast<const TransposeConvolution2dQueueDescriptor*>(&descriptor); |
| return CreateTransposeConvolution2d(*transposeConvolution2dQueueDescriptor, info); |
| } |
| case LayerType::UnidirectionalSequenceLstm: |
| { |
| auto unidirectionalSequenceLstmQueueDescriptor |
| = PolymorphicDowncast<const UnidirectionalSequenceLstmQueueDescriptor*>(&descriptor); |
| return CreateUnidirectionalSequenceLstm(*unidirectionalSequenceLstmQueueDescriptor, info); |
| } |
| default: |
| return nullptr; |
| } |
| } |
| ARMNN_NO_DEPRECATE_WARN_END |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateActivation(const ActivationQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateAddition(const AdditionQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateArgMinMax(const ArgMinMaxQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateBatchNormalization( |
| const BatchNormalizationQueueDescriptor& /*descriptor*/, const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateBatchToSpaceNd(const BatchToSpaceNdQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*Info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateCast(const CastQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateChannelShuffle(const ChannelShuffleQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateComparison(const ComparisonQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConcat(const ConcatQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConstant(const ConstantQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvertBf16ToFp32(const ConvertBf16ToFp32QueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvertFp16ToFp32(const ConvertFp16ToFp32QueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvertFp32ToBf16(const ConvertFp32ToBf16QueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvertFp32ToFp16(const ConvertFp32ToFp16QueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvolution2d(const Convolution2dQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateConvolution3d(const Convolution3dQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDebug(const DebugQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDepthToSpace(const DepthToSpaceQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDepthwiseConvolution2d( |
| const DepthwiseConvolution2dQueueDescriptor& /*descriptor*/, const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDequantize( |
| const DequantizeQueueDescriptor& /*descriptor*/, const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDetectionPostProcess( |
| const DetectionPostProcessQueueDescriptor& /*descriptor*/, const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateDivision(const DivisionQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateElementwiseUnary(const ElementwiseUnaryQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateFakeQuantization(const FakeQuantizationQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateFill(const FillQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateFloor(const FloorQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateFullyConnected(const FullyConnectedQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateGather(const GatherQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateInstanceNormalization( |
| const InstanceNormalizationQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateL2Normalization(const L2NormalizationQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateLogicalBinary(const LogicalBinaryQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateLogicalUnary(const ElementwiseUnaryQueueDescriptor& /*desc*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateLogSoftmax(const LogSoftmaxQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateLstm(const LstmQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMaximum(const MaximumQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMean(const MeanQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*Info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMemCopy(const MemCopyQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMemImport(const MemImportQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMerge(const MergeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMinimum(const MinimumQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateMultiplication(const MultiplicationQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateNormalization(const NormalizationQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateOutput(const OutputQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePad(const PadQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*Info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePermute(const PermuteQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePooling2d(const Pooling2dQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePooling3d(const Pooling3dQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePreCompiled(const PreCompiledQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreatePrelu(const PreluQueueDescriptor &/*descriptor*/, |
| const WorkloadInfo &/*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateQuantize(const QuantizeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*Info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateQLstm(const QLstmQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateQuantizedLstm(const QuantizedLstmQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateRank(const RankQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateReduce(const ReduceQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateReshape(const ReshapeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateResize(const ResizeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateShape(const ShapeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSlice(const SliceQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSoftmax(const SoftmaxQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSplitter(const SplitterQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSpaceToBatchNd(const SpaceToBatchNdQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSpaceToDepth(const SpaceToDepthQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateStack(const StackQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateStridedSlice(const StridedSliceQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSubtraction(const SubtractionQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateSwitch(const SwitchQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateTranspose(const TransposeQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateTransposeConvolution2d( |
| const TransposeConvolution2dQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateUnidirectionalSequenceLstm( |
| const UnidirectionalSequenceLstmQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| std::unique_ptr<IWorkload> IWorkloadFactory::CreateInput( |
| const InputQueueDescriptor& /*descriptor*/, |
| const WorkloadInfo& /*info*/) const |
| { |
| return std::unique_ptr<IWorkload>(); |
| } |
| |
| } // namepsace armnn |
