| // |
| // Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "RefLayerSupport.hpp" |
| |
| #include <armnn/TypesUtils.hpp> |
| #include <armnn/Types.hpp> |
| #include <armnn/utility/IgnoreUnused.hpp> |
| #include <armnn/utility/NumericCast.hpp> |
| #include <armnn/utility/PolymorphicDowncast.hpp> |
| |
| #include <LayerSupportCommon.hpp> |
| #include <backendsCommon/LayerSupportRules.hpp> |
| |
| #include <array> |
| #include <vector> |
| |
| namespace armnn |
| { |
| |
| namespace |
| { |
| |
| template<typename Float32Func, typename Uint8Func, typename ... Params> |
| bool IsSupportedForDataTypeRef(Optional<std::string&> reasonIfUnsupported, |
| DataType dataType, |
| Float32Func floatFuncPtr, |
| Uint8Func uint8FuncPtr, |
| Params&&... params) |
| { |
| return IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| dataType, |
| &FalseFunc<Params...>, |
| floatFuncPtr, |
| uint8FuncPtr, |
| &FalseFunc<Params...>, |
| &FalseFunc<Params...>, |
| std::forward<Params>(params)...); |
| } |
| |
| } // anonymous namespace |
| |
| namespace |
| { |
| |
| std::string CreateIncorrectDimensionsErrorMsg(unsigned int expected, |
| unsigned int actual, |
| std::string& layerStr, |
| std::string& tensorName) |
| { |
| std::string errorMsg = "Reference " + layerStr + ": Expected " + std::to_string(expected) + " dimensions but got" + |
| " " + std::to_string(actual) + " dimensions instead, for the '" + tensorName + "' tensor."; |
| |
| return errorMsg; |
| } |
| |
| } // anonymous namespace |
| |
| bool RefLayerSupport::IsLayerSupported(const LayerType& type, |
| const std::vector<TensorInfo>& infos, |
| const BaseDescriptor& descriptor, |
| const Optional<LstmInputParamsInfo>& lstmParamsInfo, |
| const Optional<QuantizedLstmInputParamsInfo>& quantizedLstmInputParamsInfo, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| switch (type) |
| { |
| case LayerType::Activation: |
| return IsActivationSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ActivationDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Addition: |
| return IsAdditionSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::ArgMinMax: |
| return IsArgMinMaxSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ArgMinMaxDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::BatchMatMul: |
| return IsBatchMatMulSupported(infos[0], |
| infos[1], |
| infos[2], |
| *(PolymorphicDowncast<const BatchMatMulDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::BatchNormalization: |
| return IsBatchNormalizationSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| infos[5], |
| *(PolymorphicDowncast<const BatchNormalizationDescriptor*> |
| (&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::BatchToSpaceNd: |
| return IsBatchToSpaceNdSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const BatchToSpaceNdDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::BroadcastTo: |
| return IsBroadcastToSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const BroadcastToDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Comparison: |
| return IsComparisonSupported(infos[0], |
| infos[1], |
| infos[2], |
| *(PolymorphicDowncast<const ComparisonDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Concat: |
| { |
| std::vector<const TensorInfo*> inputInfos; |
| for (uint32_t i = 0; i < (infos.size() - 1); i++) |
| { |
| inputInfos.push_back(&infos[i]); |
| } |
| return IsConcatSupported(inputInfos, |
| infos[infos.size() - 1], |
| *(PolymorphicDowncast<const OriginsDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| } |
| case LayerType::Constant: |
| return IsConstantSupported(infos[0], reasonIfUnsupported); |
| case LayerType::ConvertFp16ToFp32: |
| return IsConvertFp16ToFp32Supported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::ConvertFp32ToFp16: |
| return IsConvertFp32ToFp16Supported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Convolution2d: |
| { |
| if (infos.size() != 4) |
| { |
| throw InvalidArgumentException("Invalid number of Convolution2d TensorInfos. " |
| "TensorInfos should be of format: {input, output, weights, biases}."); |
| } |
| |
| auto desc = *(PolymorphicDowncast<const Convolution2dDescriptor*>(&descriptor)); |
| if (infos[3] == TensorInfo()) |
| { |
| return IsConvolution2dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| EmptyOptional(), |
| reasonIfUnsupported); |
| } |
| else |
| { |
| return IsConvolution2dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| infos[3], |
| reasonIfUnsupported); |
| } |
| } |
| case LayerType::DepthToSpace: |
| return IsDepthToSpaceSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const DepthToSpaceDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::DepthwiseConvolution2d: |
| { |
| if (infos.size() != 4) |
| { |
| throw InvalidArgumentException("Invalid number of DepthwiseConvolution2d TensorInfos. " |
| "TensorInfos should be of format: {input, output, weights, biases}."); |
| } |
| |
| auto desc = *(PolymorphicDowncast<const DepthwiseConvolution2dDescriptor*>(&descriptor)); |
| if (infos[3] == TensorInfo()) |
| { |
| return IsDepthwiseConvolutionSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| EmptyOptional(), |
| reasonIfUnsupported); |
| } |
| else |
| { |
| return IsDepthwiseConvolutionSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| infos[3], |
| reasonIfUnsupported); |
| } |
| } |
| case LayerType::Dequantize: |
| return IsDequantizeSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Division: |
| return IsDivisionSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::ElementwiseBinary: |
| { |
| std::array<DataType, 7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| bool supported = true; |
| supported &= CheckSupportRule(TypeAnyOf(infos[0], supportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(infos[1], supportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(infos[2], supportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(infos[0], infos[1]), reasonIfUnsupported, |
| "Reference elementwise unary: input types not matching"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(infos[0], infos[2]), reasonIfUnsupported, |
| "Reference elementwise unary: input and output types not matching"); |
| |
| return supported; |
| } |
| case LayerType::ElementwiseUnary: |
| return IsElementwiseUnarySupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ElementwiseUnaryDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Fill: |
| return IsFillSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const FillDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Floor: |
| return IsFloorSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::FullyConnected: |
| return IsFullyConnectedSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| *(PolymorphicDowncast<const FullyConnectedDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Gather: |
| return IsGatherSupported(infos[0], |
| infos[1], |
| infos[2], |
| *(PolymorphicDowncast<const GatherDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::GatherNd: |
| return IsGatherNdSupported(infos[0], |
| infos[1], |
| infos[2], |
| reasonIfUnsupported); |
| case LayerType::Input: |
| return IsInputSupported(infos[0], reasonIfUnsupported); |
| case LayerType::InstanceNormalization: |
| return IsInstanceNormalizationSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const InstanceNormalizationDescriptor*> |
| (&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::L2Normalization: |
| return IsL2NormalizationSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const L2NormalizationDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::LogicalBinary: |
| return IsLogicalBinarySupported(infos[0], |
| infos[1], |
| infos[2], |
| *(PolymorphicDowncast<const LogicalBinaryDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::LogSoftmax: |
| return IsLogSoftmaxSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const LogSoftmaxDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Lstm: |
| return IsLstmSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| infos[5], |
| infos[6], |
| *(PolymorphicDowncast<const LstmDescriptor*>(&descriptor)), |
| lstmParamsInfo.value(), |
| reasonIfUnsupported); |
| case LayerType::QLstm: |
| return IsQLstmSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| infos[5], |
| *(PolymorphicDowncast<const QLstmDescriptor*>(&descriptor)), |
| lstmParamsInfo.value(), |
| reasonIfUnsupported); |
| case LayerType::Maximum: |
| return IsMaximumSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::Mean: |
| return IsMeanSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const MeanDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Minimum: |
| return IsMinimumSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::Multiplication: |
| return IsMultiplicationSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::Normalization: |
| return IsNormalizationSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const NormalizationDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Output: |
| return IsOutputSupported(infos[0], reasonIfUnsupported); |
| case LayerType::Pad: |
| return IsPadSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const PadDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Permute: |
| return IsPermuteSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const PermuteDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Pooling2d: |
| return IsPooling2dSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const Pooling2dDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Prelu: |
| return IsPreluSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::Quantize: |
| return IsQuantizeSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Reshape: |
| return IsReshapeSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ReshapeDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Resize: |
| return IsResizeSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ResizeDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::ReverseV2: |
| return IsReverseV2Supported(infos[0], |
| infos[1], |
| infos[2], |
| reasonIfUnsupported); |
| case LayerType::Reduce: |
| return IsReduceSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ReduceDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::ScatterNd: |
| return IsScatterNdSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| *(PolymorphicDowncast<const ScatterNdDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Slice: |
| return IsSliceSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const SliceDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Softmax: |
| return IsSoftmaxSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const SoftmaxDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::SpaceToBatchNd: |
| return IsSpaceToBatchNdSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const SpaceToBatchNdDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::SpaceToDepth: |
| return IsSpaceToDepthSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const SpaceToDepthDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Splitter: |
| { |
| std::vector<TensorInfo> outputInfos; |
| for (uint32_t i = 1; i < infos.size(); i++) |
| { |
| outputInfos.push_back(infos[i]); |
| } |
| return IsSplitterSupported(infos[0], |
| {outputInfos.begin(), outputInfos.end()}, |
| *(PolymorphicDowncast<const ViewsDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| } |
| case LayerType::Stack: |
| { |
| std::vector<const TensorInfo*> inputInfos; |
| for (uint32_t i = 0; i < infos.size() - 1; i++) |
| { |
| inputInfos.push_back(&infos[i]); |
| } |
| return IsStackSupported(inputInfos, |
| infos[infos.size() - 1], |
| *(PolymorphicDowncast<const StackDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| } |
| case LayerType::StridedSlice: |
| return IsStridedSliceSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const StridedSliceDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Subtraction: |
| return IsSubtractionSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::Tile: |
| return IsTileSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const TileDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Transpose: |
| return IsTransposeSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const TransposeDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::TransposeConvolution2d: |
| { |
| if (infos.size() != 4) |
| { |
| throw InvalidArgumentException("Invalid number of TransposeConvolution2d TensorInfos. " |
| "TensorInfos should be of format: {input, output, weights, biases}."); |
| } |
| |
| auto desc = *(PolymorphicDowncast<const TransposeConvolution2dDescriptor*>(&descriptor)); |
| if (infos[3] == TensorInfo()) |
| { |
| return IsTransposeConvolution2dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| EmptyOptional(), |
| reasonIfUnsupported); |
| } |
| else |
| { |
| return IsTransposeConvolution2dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| infos[3], |
| reasonIfUnsupported); |
| } |
| } |
| case LayerType::Cast: |
| return IsCastSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::ChannelShuffle: |
| return IsChannelShuffleSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const ChannelShuffleDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Convolution3d: |
| { |
| if (infos.size() != 4) |
| { |
| throw InvalidArgumentException("Invalid number of Convolution3d TensorInfos. " |
| "TensorInfos should be of format: {input, output, weights, biases}."); |
| } |
| |
| auto desc = *(PolymorphicDowncast<const Convolution3dDescriptor*>(&descriptor)); |
| if (infos[3] == TensorInfo()) |
| { |
| return IsConvolution3dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| EmptyOptional(), |
| reasonIfUnsupported); |
| } |
| else |
| { |
| return IsConvolution3dSupported(infos[0], |
| infos[1], |
| desc, |
| infos[2], |
| infos[3], |
| reasonIfUnsupported); |
| } |
| } |
| case LayerType::Debug: |
| return IsDebugSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::DetectionPostProcess: |
| return IsDetectionPostProcessSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| infos[5], |
| infos[6], |
| *(PolymorphicDowncast<const DetectionPostProcessDescriptor*> |
| (&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::FakeQuantization: |
| return IsFakeQuantizationSupported(infos[0], |
| *(PolymorphicDowncast<const FakeQuantizationDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::MemCopy: |
| return IsMemCopySupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Rank: |
| return IsRankSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Shape: |
| return IsShapeSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::UnidirectionalSequenceLstm: |
| { |
| if (infos.size() != 6) |
| { |
| throw InvalidArgumentException("Invalid number of UnidirectionalSequenceLstm TensorInfos. TensorInfos " |
| "should be of format: {input, outputStateIn, cellStateIn, " |
| "hiddenStateOutputVal, cellStateOutputVal, output}"); |
| } |
| auto desc = *(PolymorphicDowncast<const UnidirectionalSequenceLstmDescriptor*>(&descriptor)); |
| return IsUnidirectionalSequenceLstmSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| infos[5], |
| desc, |
| lstmParamsInfo.value(), |
| reasonIfUnsupported); |
| } |
| case LayerType::Pooling3d: |
| return IsPooling3dSupported(infos[0], |
| infos[1], |
| *(PolymorphicDowncast<const Pooling3dDescriptor*>(&descriptor)), |
| reasonIfUnsupported); |
| case LayerType::Map: |
| return true; |
| case LayerType::Unmap: |
| return true; |
| case LayerType::MemImport: |
| return LayerSupportBase::IsMemImportSupported(infos[0], infos[1], reasonIfUnsupported); |
| case LayerType::Merge: |
| return LayerSupportBase::IsMergeSupported(infos[0], infos[1], infos[2], reasonIfUnsupported); |
| case LayerType::QuantizedLstm: |
| return LayerSupportBase::IsQuantizedLstmSupported(infos[0], |
| infos[1], |
| infos[2], |
| infos[3], |
| infos[4], |
| quantizedLstmInputParamsInfo.value(), |
| reasonIfUnsupported); |
| default: |
| // layers not supported in reference by default: |
| // precompiled, standin, switch, fused |
| return false; |
| } |
| } |
| |
| bool RefLayerSupport::IsActivationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ActivationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| // Define supported types. |
| std::array<DataType,6> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference activation: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference activation: output type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference activation: input and output types mismatched."); |
| |
| supported &= CheckSupportRule(ShapesAreSameRank(input, output), reasonIfUnsupported, |
| "Reference activation: input and output shapes are of different rank."); |
| |
| |
| struct ActivationFunctionSupported : public Rule |
| { |
| ActivationFunctionSupported(const ActivationDescriptor& desc) |
| { |
| switch(desc.m_Function) |
| { |
| case ActivationFunction::Abs: |
| case ActivationFunction::BoundedReLu: |
| case ActivationFunction::Elu: |
| case ActivationFunction::Gelu: |
| case ActivationFunction::HardSwish: |
| case ActivationFunction::LeakyReLu: |
| case ActivationFunction::Linear: |
| case ActivationFunction::ReLu: |
| case ActivationFunction::Sigmoid: |
| case ActivationFunction::SoftReLu: |
| case ActivationFunction::Sqrt: |
| case ActivationFunction::Square: |
| case ActivationFunction::TanH: |
| { |
| m_Res = true; |
| break; |
| } |
| default: |
| { |
| m_Res = false; |
| break; |
| } |
| } |
| } |
| }; |
| |
| // Function is supported |
| supported &= CheckSupportRule(ActivationFunctionSupported(descriptor), reasonIfUnsupported, |
| "Reference activation: function not supported."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsAdditionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference addition: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference addition: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference addition: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference addition: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference addition: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference addition: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsArgMinMaxSupported(const armnn::TensorInfo &input, const armnn::TensorInfo &output, |
| const armnn::ArgMinMaxDescriptor &descriptor, |
| armnn::Optional<std::string &> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 8> supportedInputTypes = |
| { |
| DataType::Float16, |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32, |
| DataType::Signed64 |
| }; |
| |
| std::array<DataType,2> supportedOutputTypes = { |
| DataType::Signed32, |
| DataType::Signed64 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedInputTypes), reasonIfUnsupported, |
| "Reference ArgMinMax: input is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedOutputTypes), reasonIfUnsupported, |
| "Reference ArgMinMax: output type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsBatchMatMulSupported(const TensorInfo& inputX, |
| const TensorInfo& inputY, |
| const TensorInfo& output, |
| const BatchMatMulDescriptor& descriptor, |
| Optional<std::string &> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::Float16, |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(inputX, supportedTypes), reasonIfUnsupported, |
| "Reference batch matrix multiplication: input X is not a supported type"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(inputY, supportedTypes), reasonIfUnsupported, |
| "Reference batch matrix multiplication: input Y is not a supported type"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference batch matrix multiplication: output is not a supported type"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(inputX, inputY), reasonIfUnsupported, |
| "Reference batch matrix multiplication: input X and input Y types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(inputX, output), reasonIfUnsupported, |
| "Reference batch matrix multiplication: inputs and output types are mismatched"); |
| |
| supported &= CheckSupportRule(TensorNumDimensionsAreGreaterOrEqualTo(inputX, 2), |
| reasonIfUnsupported, |
| "Reference batch matrix multiplication: input X is not of rank 2 or greater"); |
| |
| supported &= CheckSupportRule(TensorNumDimensionsAreGreaterOrEqualTo(inputY, 2), |
| reasonIfUnsupported, |
| "Reference batch matrix multiplication: input Y is not of rank 2 or greater"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsBatchNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& mean, |
| const TensorInfo& variance, |
| const TensorInfo& beta, |
| const TensorInfo& gamma, |
| const BatchNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference batch normalization: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(mean, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: mean is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(variance, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: variance is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(beta, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: beta is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(gamma, supportedTypes), reasonIfUnsupported, |
| "Reference batch normalization: gamma is not a supported type."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsBatchToSpaceNdSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const BatchToSpaceNdDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| |
| std::string batchToSpaceNdLayerStr = "batchToSpaceNd"; |
| std::string inputTensorStr = "input"; |
| std::string outputTensorStr = "output"; |
| |
| // Define supported types. |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference BatchToSpaceNd: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference BatchToSpaceNd: output type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference BatchToSpaceNd: input and output types mismatched."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsBroadcastToSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const BroadcastToDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| |
| std::array<DataType, 8> supportedTypes |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32, |
| DataType::Signed64 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "BroadcastTo: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "BroadcastTo: output type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsCastSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| std::array<DataType, 10> supportedInputTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QSymmS8, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32, |
| DataType::Signed64 |
| }; |
| |
| bool supported = true; |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedInputTypes), reasonIfUnsupported, |
| "Reference cast: input is not a supported type"); |
| |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedInputTypes), reasonIfUnsupported, |
| "Reference cast: output is not a supported type"); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference cast: input and output shapes have different number of total elements"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsChannelShuffleSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ChannelShuffleDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType, 7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference ChannelShuffle: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference ChannelShuffle: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference ChannelShuffle: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| |
| bool RefLayerSupport::IsComparisonSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| const ComparisonDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| std::array<DataType, 8> supportedInputTypes = |
| { |
| DataType::Boolean, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| bool supported = true; |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedInputTypes), reasonIfUnsupported, |
| "Reference comparison: input 0 is not a supported type"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference comparison: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypeIs(output, DataType::Boolean), reasonIfUnsupported, |
| "Reference comparison: output is not of type Boolean"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference comparison: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsConcatSupported(const std::vector<const TensorInfo*> inputs, |
| const TensorInfo& output, |
| const OriginsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference concatenation: output type not supported"); |
| for (const TensorInfo* input : inputs) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(*input, supportedTypes), reasonIfUnsupported, |
| "Reference concatenation: input type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(*input, output), reasonIfUnsupported, |
| "Reference concatenation: input and output types mismatched."); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsConstantSupported(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| std::array<DataType,8> supportedTypes = |
| { |
| DataType::Float16, |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| return CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference constant: output is not a supported type."); |
| } |
| |
| bool RefLayerSupport::IsConvertFp16ToFp32Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return (IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &FalseInputFuncF32<>, |
| &FalseFuncU8<>, |
| &FalseFuncI32<>, |
| &FalseFuncU8<>) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| output.GetDataType(), |
| &FalseOutputFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>, |
| &FalseFuncI32<>, |
| &FalseFuncU8<>)); |
| } |
| |
| bool RefLayerSupport::IsConvertFp32ToFp16Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return (IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &FalseInputFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>, |
| &FalseFuncI32<>, |
| &FalseFuncU8<>) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &FalseOutputFuncF32<>, |
| &FalseFuncU8<>, |
| &FalseFuncI32<>, |
| &FalseFuncU8<>)); |
| } |
| |
| bool RefLayerSupport::IsConvolution2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| // Define supported types. |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution2d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution2d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Convolution2d: input and output types mismatched."); |
| |
| |
| const DataType inputType = input.GetDataType(); |
| if (IsQuantized8BitType(inputType)) |
| { |
| std::array<DataType, 3> supportedWeightTypes = |
| { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedWeightTypes), reasonIfUnsupported, |
| "Reference Convolution2d: weights type not supported for quantized input."); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution2d: weights is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, weights), reasonIfUnsupported, |
| "Reference Convolution2d: input and weights types mismatched."); |
| } |
| |
| if (biases.has_value()) |
| { |
| std::array<DataType,4> biasesSupportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(biases.value(), biasesSupportedTypes), reasonIfUnsupported, |
| "Reference Convolution2d: biases is not a supported type."); |
| } |
| IgnoreUnused(descriptor); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsConvolution3dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution3dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| // Define supported types. |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution3d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution3d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Convolution3d: input and output types mismatched."); |
| |
| const DataType inputType = input.GetDataType(); |
| if (IsQuantized8BitType(inputType)) |
| { |
| std::array<DataType, 3> supportedWeightTypes = |
| { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedWeightTypes), reasonIfUnsupported, |
| "Reference Convolution3d: weights type not supported for quantized input."); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference Convolution3d: weights is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, weights), reasonIfUnsupported, |
| "Reference Convolution3d: input and weights types mismatched."); |
| } |
| |
| if (biases.has_value()) |
| { |
| std::array<DataType,4> biasesSupportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(biases.value(), biasesSupportedTypes), reasonIfUnsupported, |
| "Reference Convolution3d: biases is not a supported type."); |
| } |
| IgnoreUnused(descriptor); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsDebugSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType, 8> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float16, |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference for Debug layer: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference for Debug layer: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference for Debug layer: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsDepthToSpaceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthToSpaceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference DepthToSpace: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference DepthToSpace: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference DepthToSpace: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsDepthwiseConvolutionSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported types. |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: input and output types mismatched."); |
| |
| const DataType inputType = input.GetDataType(); |
| if (IsQuantized8BitType(inputType)) |
| { |
| std::array<DataType, 3> supportedWeightTypes = |
| { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedWeightTypes), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: weights type not supported for " |
| "quantized input."); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: weights is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, weights), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: input and weights types mismatched."); |
| } |
| |
| if (biases.has_value()) |
| { |
| std::array<DataType,4> biasesSupportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32 |
| }; |
| supported &= CheckSupportRule(TypeAnyOf(biases.value(), biasesSupportedTypes), reasonIfUnsupported, |
| "Reference DepthwiseConvolution2d: biases is not a supported type."); |
| } |
| |
| return supported; |
| |
| } |
| |
| bool RefLayerSupport::IsDequantizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,5> supportedInputTypes = { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Float16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedInputTypes), reasonIfUnsupported, |
| "Reference for Dequantize layer: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeNotPerAxisQuantized(input), reasonIfUnsupported, |
| "Reference for Dequantize layer: per-axis quantized input not supported."); |
| |
| std::array<DataType,3> supportedOutputTypes = { |
| DataType::Float32, |
| DataType::Float16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedOutputTypes), reasonIfUnsupported, |
| "Reference for Dequantize layer: output type not supported."); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference for Dequantize layer: input/output shapes have different num total " |
| "elements."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsDetectionPostProcessSupported(const TensorInfo& boxEncodings, |
| const TensorInfo& scores, |
| const TensorInfo& anchors, |
| const TensorInfo& detectionBoxes, |
| const TensorInfo& detectionClasses, |
| const TensorInfo& detectionScores, |
| const TensorInfo& numDetections, |
| const DetectionPostProcessDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(anchors, detectionBoxes, detectionClasses, detectionScores, numDetections, descriptor); |
| |
| bool supported = true; |
| |
| std::array<DataType,6> supportedInputTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(boxEncodings, supportedInputTypes), reasonIfUnsupported, |
| "Reference DetectionPostProcess: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(scores, supportedInputTypes), reasonIfUnsupported, |
| "Reference DetectionPostProcess: input 1 is not a supported type."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsDilatedDepthwiseConvolutionSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return IsDepthwiseConvolutionSupported(input, output, descriptor, weights, biases, reasonIfUnsupported); |
| } |
| |
| bool RefLayerSupport::IsDivisionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference division: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference division: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference division: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference division: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference division: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference division: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsElementwiseUnarySupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ElementwiseUnaryDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| std::array<DataType, 1> logicalSupportedTypes = |
| { |
| DataType::Boolean |
| }; |
| |
| bool supported = true; |
| |
| if (descriptor.m_Operation == UnaryOperation::LogicalNot) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(input, logicalSupportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, logicalSupportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: output type not supported"); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference elementwise unary: output type not supported"); |
| } |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference elementwise unary: input and output types not matching"); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference elementwise unary: input and output shapes" |
| "have different number of total elements"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsFakeQuantizationSupported(const TensorInfo& input, |
| const FakeQuantizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType,1> supportedTypes = |
| { |
| DataType::Float32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference fake quantization: input type not supported."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsFillSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const FillDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| IgnoreUnused(output); |
| |
| bool supported = true; |
| |
| std::array<DataType,3> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeIs(input, DataType::Signed32), reasonIfUnsupported, |
| "Reference Fill: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Fill: output type not supported."); |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsFloorSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(output); |
| bool supported = true; |
| |
| std::array<DataType,3> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Floor: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Floor: output type not supported."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsFullyConnectedSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& weights, |
| const TensorInfo& biases, |
| const FullyConnectedDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| // Define supported types. |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Fully Connected: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Fully Connected: output type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference Fully Connected: weights type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Fully Connected: input and output types mismatched."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference Fully Connected: weights is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, weights), reasonIfUnsupported, |
| "Reference Fully Connected: input and weights types mismatched."); |
| |
| if (descriptor.m_BiasEnabled) |
| { |
| // Defined supported types for bias |
| std::array<DataType, 5> |
| supportedBiasTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32, |
| DataType::QAsymmS8 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(biases, supportedBiasTypes), reasonIfUnsupported, |
| "Reference Fully Connected: bias type not supported."); |
| |
| supported &= CheckSupportRule(BiasAndWeightsTypesMatch(biases, weights), reasonIfUnsupported, |
| "Reference Fully Connected: bias and weight types mismatch."); |
| |
| supported &= CheckSupportRule(BiasAndWeightsTypesCompatible(weights, supportedBiasTypes), reasonIfUnsupported, |
| "Reference Fully Connected: bias type inferred from weights is incompatible."); |
| |
| supported &= CheckSupportRule(TensorNumDimensionsAreCorrect(biases, 1U), reasonIfUnsupported, |
| "Reference Fully Connected: bias must have 1 dimension."); |
| |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsGatherNdSupported(const armnn::TensorInfo& input0, |
| const armnn::TensorInfo& input1, |
| const armnn::TensorInfo& output, |
| armnn::Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference GatherNd: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference GatherNd: output type not supported"); |
| |
| supported &= CheckSupportRule(TypeIs(input1, DataType::Signed32), reasonIfUnsupported, |
| "Reference GatherNd: indices (input1) type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference GatherNd: input and output types not matching"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsGatherSupported(const armnn::TensorInfo& input0, |
| const armnn::TensorInfo& input1, |
| const armnn::TensorInfo& output, |
| const GatherDescriptor& descriptor, |
| armnn::Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| IgnoreUnused(descriptor); |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference Gather: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Gather: output type not supported"); |
| |
| supported &= CheckSupportRule(TypeIs(input1, DataType::Signed32), reasonIfUnsupported, |
| "Reference Gather: indices (input1) type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference Gather: input and output types not matching"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsInputSupported(const TensorInfo& /*input*/, |
| Optional<std::string&> /*reasonIfUnsupported*/) const |
| { |
| return true; |
| } |
| |
| bool RefLayerSupport::IsInstanceNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const InstanceNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| // Define supported types |
| std::array<DataType, 3> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Instance Normalization: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Instance Normalization: output type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Instance Normalization: input and output types mismatched."); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference Instance Normalization: input and output shapes have different " |
| "num total elements."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsL2NormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const L2NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| // Define supported types |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference L2normalization: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference L2normalization: output type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference L2normalization: input and output types mismatched."); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference L2normalization: input and output shapes have different " |
| "num total elements."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsLogicalBinarySupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| const LogicalBinaryDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 1> supportedTypes = |
| { |
| DataType::Boolean |
| }; |
| |
| bool supported = true; |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference LogicalBinary: input 0 type not supported"); |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference LogicalBinary: input 1 type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference LogicalBinary: input and output types do not match"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference LogicalBinary: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsLogSoftmaxSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const LogSoftmaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| std::array<DataType, 3> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16 |
| }; |
| |
| bool supported = true; |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference LogSoftmax: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference LogSoftmax: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference LogSoftmax: input and output types do not match"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsLstmSupported(const TensorInfo& input, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& scratchBuffer, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& output, |
| const LstmDescriptor& descriptor, |
| const LstmInputParamsInfo& paramsInfo, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| IgnoreUnused(paramsInfo); |
| |
| bool supported = true; |
| |
| std::array<DataType,3> supportedTypes = { |
| DataType::Float32, |
| DataType::QSymmS16 |
| }; |
| |
| // check inputs and outputs |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Lstm: input is not a supported type."); |
| supported &= CheckSupportRule(TypesAreEqual(input, outputStateIn), reasonIfUnsupported, |
| "Reference Lstm: input and outputStateIn types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, cellStateIn), reasonIfUnsupported, |
| "Reference Lstm: input and cellStateIn types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, scratchBuffer), reasonIfUnsupported, |
| "Reference Lstm: input and scratchBuffer types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, outputStateOut), reasonIfUnsupported, |
| "Reference Lstm: input and outputStateOut types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, cellStateOut), reasonIfUnsupported, |
| "Reference Lstm: input and cellStateOut types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Lstm: input and output types are mismatched"); |
| // check layer parameters |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToForgetWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and InputToForgetWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToCellWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and InputToCellWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToOutputWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and InputToOutputWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToForgetWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and RecurrentToForgetWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToCellWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and RecurrentToCellWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToOutputWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and RecurrentToOutputWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetForgetGateBias()), reasonIfUnsupported, |
| "Reference Lstm: input and ForgetGateBias types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellBias()), reasonIfUnsupported, |
| "Reference Lstm: input and CellBias types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetOutputGateBias()), reasonIfUnsupported, |
| "Reference Lstm: input and OutputGateBias types are mismatched"); |
| if (!descriptor.m_CifgEnabled) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToInputWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and InputToInputWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToInputWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and RecurrentToInputWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputGateBias()), reasonIfUnsupported, |
| "Reference Lstm: input and InputGateBias types are mismatched"); |
| if (descriptor.m_PeepholeEnabled) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToInputWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and CellToInputWeights types are mismatched"); |
| } |
| } |
| if (descriptor.m_PeepholeEnabled) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToForgetWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and CellToForgetWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToOutputWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and CellToOutputWeights types are mismatched"); |
| } |
| if (descriptor.m_ProjectionEnabled) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetProjectionWeights()), reasonIfUnsupported, |
| "Reference Lstm: input and mProjectionWeights types are mismatched"); |
| if (paramsInfo.m_ProjectionBias != nullptr) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetProjectionBias()), reasonIfUnsupported, |
| "Reference Lstm: input and ProjectionBias types are mismatched"); |
| } |
| } |
| if (descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputLayerNormWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and InputLayerNormWeights types are mismatched"); |
| } |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetForgetLayerNormWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and ForgetLayerNormWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellLayerNormWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and CellLayerNormWeights types are mismatched"); |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetOutputLayerNormWeights()), |
| reasonIfUnsupported, |
| "Reference Lstm: input and OutputLayerNormWeights types are mismatched"); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsMaximumSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference maximum: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference maximum: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference maximum: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference maximum: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference maximum: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference maximum: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsMeanSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const MeanDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| std::string meanLayerStr = "Mean"; |
| std::string outputTensorStr = "output"; |
| |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Mean: input type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Mean: input and output types are mismatched"); |
| |
| if (descriptor.m_KeepDims) |
| { |
| supported &= CheckSupportRule(TensorNumDimensionsAreCorrect(output, input.GetNumDimensions()), |
| reasonIfUnsupported, |
| CreateIncorrectDimensionsErrorMsg(input.GetNumDimensions(), |
| output.GetNumDimensions(), |
| meanLayerStr, outputTensorStr).data()); |
| } |
| else if (descriptor.m_Axis.empty()) |
| { |
| supported &= CheckSupportRule(TensorNumDimensionsAreCorrect(output, 1), |
| reasonIfUnsupported, |
| CreateIncorrectDimensionsErrorMsg(1, output.GetNumDimensions(), |
| meanLayerStr, outputTensorStr).data()); |
| } |
| else |
| { |
| auto outputDim = input.GetNumDimensions() - armnn::numeric_cast<unsigned int>(descriptor.m_Axis.size()); |
| |
| if (outputDim > 0) |
| { |
| supported &= CheckSupportRule(TensorNumDimensionsAreCorrect(output, outputDim), |
| reasonIfUnsupported, |
| CreateIncorrectDimensionsErrorMsg(outputDim, output.GetNumDimensions(), |
| meanLayerStr, outputTensorStr).data()); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TensorNumDimensionsAreCorrect(output, 1), |
| reasonIfUnsupported, |
| CreateIncorrectDimensionsErrorMsg(1, output.GetNumDimensions(), |
| meanLayerStr, outputTensorStr).data()); |
| } |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsMemCopySupported(const TensorInfo &input, |
| const TensorInfo &output, |
| Optional<std::string &> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Boolean |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference MemCopy: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference MemCopy: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference MemCopy: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsMinimumSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference minimum: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference minimum: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference minimum: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference minimum: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference minimum: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference minimum: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsMultiplicationSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference multiplication: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference multiplication: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference multiplication: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference multiplication: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference multiplication: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference multiplication: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| // Define supported types |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::Float16, |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| bool supported = true; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference normalization: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference normalization: output type not supported."); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference normalization: input and output shapes have different " |
| "num total elements."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsOutputSupported(const TensorInfo& /*output*/, |
| Optional<std::string&> /*reasonIfUnsupported*/) const |
| { |
| return true; |
| } |
| |
| bool RefLayerSupport::IsPadSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PadDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference pad: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference pad: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference pad: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsPermuteSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PermuteDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference permute: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference permute: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference permute: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsPooling2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling2dDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference poolind2d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference poolind2d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference poolind2d: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsPooling3dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling3dDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference poolind3d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference poolind3d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference poolind3d: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| |
| bool RefLayerSupport::IsQLstmSupported(const TensorInfo& input, |
| const TensorInfo& previousOutputIn, |
| const TensorInfo& previousCellStateIn, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& output, |
| const QLstmDescriptor& descriptor, |
| const LstmInputParamsInfo& paramsInfo, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(input); |
| IgnoreUnused(previousOutputIn); |
| IgnoreUnused(previousCellStateIn); |
| IgnoreUnused(outputStateOut); |
| IgnoreUnused(cellStateOut); |
| IgnoreUnused(output); |
| IgnoreUnused(descriptor); |
| IgnoreUnused(paramsInfo); |
| |
| IgnoreUnused(reasonIfUnsupported); |
| |
| return true; |
| } |
| |
| bool RefLayerSupport::IsQuantizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| // Define supported input types. |
| std::array<DataType,7> supportedInputTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedInputTypes), reasonIfUnsupported, |
| "Reference quantize: input type not supported."); |
| |
| // Define supported output types. |
| std::array<DataType,4> supportedOutputTypes = { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedOutputTypes), reasonIfUnsupported, |
| "Reference quantize: output type not supported."); |
| |
| supported &= CheckSupportRule(ShapesAreSameTotalSize(input, output), reasonIfUnsupported, |
| "Reference quantize: input and output shapes have different num total elements."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsRankSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(input); |
| // Define supported output types. |
| std::array<DataType,1> supportedOutputTypes = |
| { |
| DataType::Signed32, |
| }; |
| |
| return CheckSupportRule(TypeAnyOf(output, supportedOutputTypes), reasonIfUnsupported, |
| "Reference rank: input type not supported."); |
| } |
| |
| bool RefLayerSupport::IsReduceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ReduceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Reduce: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Reduce: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Reduce: input and output types not matching"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsReshapeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ReshapeDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(output); |
| IgnoreUnused(descriptor); |
| // Define supported output types. |
| std::array<DataType,8> supportedOutputTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Boolean |
| }; |
| |
| return CheckSupportRule(TypeAnyOf(input, supportedOutputTypes), reasonIfUnsupported, |
| "Reference reshape: input type not supported."); |
| } |
| |
| bool RefLayerSupport::IsResizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ResizeDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Resize: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Resize: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Resize: input and output types not matching"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsReverseV2Supported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| // ReverseV2 is data type agnostic so it can support all the types in the Reference backend |
| std::array<DataType,8> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference ReverseV2: input0 type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference ReverseV2: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference ReverseV2: input0 and output types not matching"); |
| |
| std::array<DataType,6> input2SupportedTypes = |
| { |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, input2SupportedTypes), reasonIfUnsupported, |
| "Reference ReverseV2: input1 type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsScatterNdSupported(const TensorInfo& input, |
| const TensorInfo& indices, |
| const TensorInfo& updates, |
| const TensorInfo& output, |
| const ScatterNdDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| |
| std::array<DataType, 7> supportedTypes |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| std::array<DataType, 1> indicesSupportedTypes = |
| { |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(indices, indicesSupportedTypes), reasonIfUnsupported, |
| "ScatterNd: indices type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(updates, supportedTypes), reasonIfUnsupported, |
| "ScatterNd: updates type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "ScatterNd: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(updates, output), reasonIfUnsupported, |
| "ScatterNd: input and updates types are mismatched"); |
| |
| if (descriptor.m_InputEnabled) |
| { |
| // If the input slot is enabled, we have the input tensor in this slot |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "ScatterNd: input type not supported."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "ScatterNd: input and output types are mismatched"); |
| } |
| else |
| { |
| // If the input slot is not enabled, we have the shape tensor in this slot |
| supported &= CheckSupportRule(TypeAnyOf(input, indicesSupportedTypes), reasonIfUnsupported, |
| "ScatterNd: shape type not supported."); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsShapeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(input); |
| bool supported = true; |
| |
| std::array<DataType, 1> supportedTypes = |
| { |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Shape: output type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSliceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SliceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType, 5> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Slice: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Slice: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Slice: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSoftmaxSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SoftmaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QSymmS8, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference Softmax: output type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference Softmax: input type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference Softmax: input type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSpaceToBatchNdSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SpaceToBatchNdDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference SpaceToBatchNd: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference SpaceToBatchNd: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference SpaceToBatchNd: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSpaceToDepthSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SpaceToDepthDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference SpaceToDepth: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference SpaceToDepth: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference SpaceToDepth: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSplitterSupported(const TensorInfo& input, |
| const std::vector<std::reference_wrapper<TensorInfo>>& outputs, |
| const ViewsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| std::array<DataType,6> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference splitter: output type not supported"); |
| for (const TensorInfo& output : outputs) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference splitter: input type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference splitter: input and output types mismatched."); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsStackSupported(const std::vector<const TensorInfo*>& inputs, |
| const TensorInfo& output, |
| const StackDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference stack: output type not supported"); |
| for (const TensorInfo* input : inputs) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(*input, supportedTypes), reasonIfUnsupported, |
| "Reference stack: input type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(*input, output), reasonIfUnsupported, |
| "Reference stack: input and output types mismatched."); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsStridedSliceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const StridedSliceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType,5> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference StridedSlice: input type not supported"); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference StridedSlice: output type not supported"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference StridedSlice: input and output types are mismatched"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsSubtractionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input0, supportedTypes), reasonIfUnsupported, |
| "Reference subtraction: input 0 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(input1, supportedTypes), reasonIfUnsupported, |
| "Reference subtraction: input 1 is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference subtraction: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, input1), reasonIfUnsupported, |
| "Reference subtraction: input 0 and Input 1 types are mismatched"); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input0, output), reasonIfUnsupported, |
| "Reference subtraction: input and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input0, input1, output), reasonIfUnsupported, |
| "Reference subtraction: shapes are not suitable for implicit broadcast."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsPreluSupported(const TensorInfo& input, |
| const TensorInfo& alpha, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| bool supported = true; |
| |
| std::array<DataType, 6> supportedTypes |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "PReLU: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(alpha, supportedTypes), reasonIfUnsupported, |
| "PReLU: alpha is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "PReLU: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, alpha, output), reasonIfUnsupported, |
| "PReLU: input, alpha and output types are mismatched"); |
| |
| supported &= CheckSupportRule(ShapesAreBroadcastCompatible(input, alpha, output), reasonIfUnsupported, |
| "PReLU: shapes are not suitable for implicit broadcast"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsTileSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TileDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| |
| bool supported = true; |
| |
| std::array<DataType, 7> supportedTypes |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16, |
| DataType::Signed32 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Tile: input type not supported."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Tile: output type not supported"); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsTransposeConvolution2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TransposeConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| std::array<DataType,7> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: input and output types mismatched."); |
| |
| |
| const DataType inputType = input.GetDataType(); |
| if (IsQuantized8BitType(inputType)) |
| { |
| std::array<DataType, 3> supportedWeightTypes = |
| { |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS8 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedWeightTypes), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: weights type not supported for " |
| "quantized input."); |
| } |
| else |
| { |
| supported &= CheckSupportRule(TypeAnyOf(weights, supportedTypes), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: weights is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, weights), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: input and weights types mismatched."); |
| } |
| |
| if (biases.has_value()) |
| { |
| std::array<DataType,4> biasesSupportedTypes = |
| { |
| DataType::Float32, |
| DataType::Float16, |
| DataType::Signed32 |
| }; |
| supported &= CheckSupportRule(TypeAnyOf(biases.value(), biasesSupportedTypes), reasonIfUnsupported, |
| "Reference TransposeConvolution2d: biases is not a supported type."); |
| } |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsTransposeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TransposeDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| bool supported = true; |
| |
| // Define supported output and inputs types. |
| std::array<DataType, 6> supportedTypes = |
| { |
| DataType::BFloat16, |
| DataType::Float32, |
| DataType::Float16, |
| DataType::QAsymmS8, |
| DataType::QAsymmU8, |
| DataType::QSymmS16 |
| }; |
| |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference transpose: input is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference transpose: output is not a supported type."); |
| |
| supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, |
| "Reference transpose: input and output types are mismatched."); |
| |
| return supported; |
| } |
| |
| bool RefLayerSupport::IsUnidirectionalSequenceLstmSupported( |
| const TensorInfo& input, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& outputStateOut, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& output, |
| const UnidirectionalSequenceLstmDescriptor& descriptor, |
| const LstmInputParamsInfo& paramsInfo, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| IgnoreUnused(descriptor); |
| IgnoreUnused(paramsInfo); |
| IgnoreUnused(outputStateIn); |
| IgnoreUnused(cellStateIn); |
| IgnoreUnused(outputStateOut); |
| IgnoreUnused(cellStateOut); |
| bool supported = true; |
| |
| std::array<DataType, 2> supportedTypes = |
| { |
| DataType::Float32, |
| DataType::QAsymmS8 |
| }; |
| |
| std::array<DataType, 2> supportedWeightTypes = |
| { |
| DataType::Float32, |
| DataType::QAsymmS8 |
| }; |
| |
| std::array<DataType, 3> supportedBiasTypes = |
| { |
| DataType::Float32, |
| DataType::QAsymmS8, |
| DataType::Signed32 |
| }; |
| |
| // check inputs and outputs |
| supported &= CheckSupportRule(TypeAnyOf(input, supportedTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: input is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: output is not a supported type."); |
| |
| // check layer parameters |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputToForgetWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputToForgetWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputToCellWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputToCellWeights is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputToOutputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputToOutputWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetRecurrentToForgetWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: RecurrentToForgetWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetRecurrentToCellWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: RecurrentToCellWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetRecurrentToOutputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: RecurrentToOutputWeights " |
| "is not a supported type."); |
| |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetForgetGateBias(), supportedBiasTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: ForgetGateBias is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetCellBias(), supportedBiasTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: CellBias is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetOutputGateBias(), supportedBiasTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: OutputGateBias is not a supported type."); |
| if (!descriptor.m_CifgEnabled) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputToInputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputToInputWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetRecurrentToInputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: RecurrentToInputWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputGateBias(), supportedBiasTypes), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputGateBias is not a supported type."); |
| if (descriptor.m_PeepholeEnabled) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetCellToInputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: CellToInputWeights " |
| "is not a supported type."); |
| } |
| } |
| if (descriptor.m_PeepholeEnabled) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetCellToForgetWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: CellToForgetWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetCellToOutputWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: CellToOutputWeights " |
| "is not a supported type."); |
| } |
| if (descriptor.m_ProjectionEnabled) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetProjectionWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: ProjectionWeights " |
| "is not a supported type."); |
| if (paramsInfo.m_ProjectionBias != nullptr) |
| { |
| supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetProjectionBias()), reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: input and ProjectionBias types " |
| "are mismatched"); |
| } |
| } |
| if (descriptor.m_LayerNormEnabled) |
| { |
| if (!descriptor.m_CifgEnabled) |
| { |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetInputLayerNormWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: InputLayerNormWeights " |
| "is not a supported type."); |
| } |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetForgetLayerNormWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: ForgetLayerNormWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetCellLayerNormWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: CellLayerNormWeights " |
| "is not a supported type."); |
| supported &= CheckSupportRule(TypeAnyOf(paramsInfo.GetOutputLayerNormWeights(), supportedWeightTypes), |
| reasonIfUnsupported, |
| "Reference UnidirectionalSequenceLstm: OutputLayerNormWeights " |
| "is not a supported type."); |
| } |
| |
| return supported; |
| } |
| |
| } // namespace armnn |