| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonLayerSupport.hpp" |
| |
| #include <LayerSupportCommon.hpp> |
| #include <InternalTypes.hpp> |
| |
| #include <armnn/Descriptors.hpp> |
| #include <armnn/Types.hpp> |
| #include <armnn/Tensor.hpp> |
| |
| #include <boost/core/ignore_unused.hpp> |
| |
| #ifdef ARMCOMPUTENEON_ENABLED |
| #include "workloads/NeonAdditionFloatWorkload.hpp" |
| #include "workloads/NeonActivationFloatWorkload.hpp" |
| #include "workloads/NeonBatchNormalizationFloatWorkload.hpp" |
| #include "workloads/NeonConvolution2dBaseWorkload.hpp" |
| #include "workloads/NeonDepthwiseConvolutionBaseWorkload.hpp" |
| #include "workloads/NeonL2NormalizationFloatWorkload.hpp" |
| #include "workloads/NeonMultiplicationFloatWorkload.hpp" |
| #include "workloads/NeonNormalizationFloatWorkload.hpp" |
| #include "workloads/NeonFullyConnectedWorkload.hpp" |
| #include "workloads/NeonPermuteWorkload.hpp" |
| #include "workloads/NeonPooling2dBaseWorkload.hpp" |
| #include "workloads/NeonSoftmaxBaseWorkload.hpp" |
| #include "workloads/NeonSubtractionFloatWorkload.hpp" |
| #endif |
| |
| using namespace boost; |
| |
| namespace armnn |
| { |
| |
| bool IsNeonDirectConvolutionPreferred(const TensorInfo& weightInfo, const Convolution2dDescriptor& desc) |
| { |
| // See arm_compute::NEDirectConvolutionLayer documentation for the supported cases, |
| // and complement with NEDirectConvolutionLayerKernel::configure() implementation. |
| |
| // Only 1x1 is using direct convolution. Performance results and details are in: |
| // https://jira.arm.com/browse/IVGCVSW-1003 |
| // Measurements were taken as of clframework: f105ab972135bcd21304883eff040d7e587099bc |
| |
| const bool dataTypeSupported = (weightInfo.GetDataType() == armnn::DataType::Float32); |
| |
| // Strides: 1|2|3 |
| const bool strideSupported = (desc.m_StrideX == 1 || desc.m_StrideX == 2 || desc.m_StrideX == 3) && |
| (desc.m_StrideY == 1 || desc.m_StrideY == 2 || desc.m_StrideY == 3); |
| |
| auto paddingLargerThan = [](const Convolution2dDescriptor& conv2ddesc, unsigned int value) |
| { |
| return conv2ddesc.m_PadLeft > value || conv2ddesc.m_PadRight > value || |
| conv2ddesc.m_PadTop > value || conv2ddesc.m_PadBottom > value; |
| }; |
| |
| // Supported sizes and padding. |
| const bool sizeAndPaddingSupported = |
| // Pad > 0 not supported for 1x1 weights. |
| (weightInfo.GetShape()[2] == 1 && weightInfo.GetShape()[3] == 1 && !paddingLargerThan(desc, 0u)); |
| |
| const bool preferDirectConvolution = dataTypeSupported && |
| strideSupported && |
| sizeAndPaddingSupported && |
| // NEDirectConvolutionLayerKernel doesn't support NULL bias. |
| desc.m_BiasEnabled; |
| return preferDirectConvolution; |
| } |
| |
| bool IsNeonNormalizationDescParamsSupported(std::string* reasonIfUnsupported, const NormalizationDescriptor& parameters) |
| { |
| if (parameters.m_NormMethodType != NormalizationAlgorithmMethod::LocalBrightness) |
| { |
| if (reasonIfUnsupported) |
| { |
| *reasonIfUnsupported = "Unsupported normalisation method type, only LocalBrightness is supported"; |
| } |
| return false; |
| } |
| if (parameters.m_NormSize % 2 == 0) |
| { |
| if (reasonIfUnsupported) |
| { |
| *reasonIfUnsupported = "Normalization size must be an odd number."; |
| } |
| return false; |
| } |
| |
| return true; |
| } |
| |
| bool IsNeonBackendSupported(std::string* reasonIfUnsupported) |
| { |
| #if ARMCOMPUTENEON_ENABLED |
| return true; |
| #else |
| if (reasonIfUnsupported != nullptr) |
| { |
| *reasonIfUnsupported = "The armnn library has been built without NEON support"; |
| } |
| return false; |
| #endif |
| } |
| |
| template<typename FloatFunc, typename Uint8Func, typename ... Params> |
| bool IsSupportedForDataTypeNeon(std::string* reasonIfUnsupported, |
| DataType dataType, |
| FloatFunc floatFuncPtr, |
| Uint8Func uint8FuncPtr, |
| Params&&... params) |
| { |
| return IsNeonBackendSupported(reasonIfUnsupported) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| dataType, |
| floatFuncPtr, |
| floatFuncPtr, |
| uint8FuncPtr, |
| std::forward<Params>(params)...); |
| } |
| |
| #if ARMCOMPUTENEON_ENABLED |
| template<class FuncType, class... Args> |
| inline bool IsWorkloadSupported(FuncType& func, std::string* reasonIfUnsupported, Args&&... args) |
| { |
| arm_compute::Status aclStatus = func(std::forward<Args>(args)...); |
| const bool supported = (aclStatus.error_code() == arm_compute::ErrorCode::OK); |
| if (!supported && reasonIfUnsupported) |
| { |
| *reasonIfUnsupported = aclStatus.error_description(); |
| } |
| return supported; |
| } |
| |
| #define FORWARD_WORKLOAD_VALIDATE_FUNC(func, reasonIfUnsupported, ...) \ |
| return IsWorkloadSupported(func, reasonIfUnsupported, __VA_ARGS__); |
| #else |
| #define FORWARD_WORKLOAD_VALIDATE_FUNC(func, reasonIfUnsupported, ...) \ |
| return IsNeonBackendSupported(reasonIfUnsupported); |
| #endif |
| |
| bool IsActivationSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const ActivationDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonActivationWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool IsAdditionSupportedNeon(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonAdditionWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool IsBatchNormalizationSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& mean, |
| const TensorInfo& var, |
| const TensorInfo& beta, |
| const TensorInfo& gamma, |
| const BatchNormalizationDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonBatchNormalizationValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| mean, |
| var, |
| beta, |
| gamma, |
| descriptor); |
| } |
| |
| bool IsConstantSupportedNeon(const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsConvolution2dSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const boost::optional<TensorInfo>& biases, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonConvolution2dWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| bool IsDepthwiseConvolutionSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const boost::optional<TensorInfo>& biases, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDepthwiseConvolutionWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| bool IsDivisionSupportedNeon(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| // At the moment division is not supported |
| return false; |
| } |
| |
| bool IsSubtractionSupportedNeon(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSubtractionWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool IsFullyConnectedSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& weights, |
| const TensorInfo& biases, |
| const FullyConnectedDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| // At the moment U8 is unsupported |
| if (input.GetDataType() == DataType::QuantisedAsymm8) |
| { |
| return false; |
| } |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonFullyConnectedWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| weights, |
| biases, |
| descriptor); |
| } |
| |
| bool IsInputSupportedNeon(const TensorInfo& input, |
| std::string* reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsL2NormalizationSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const L2NormalizationDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonL2NormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool IsMergerSupportedNeon(const std::vector<const TensorInfo*> inputs, |
| const OriginsDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| inputs[0]->GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsMultiplicationSupportedNeon(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonMultiplicationWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool IsNormalizationSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const NormalizationDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonNormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool IsOutputSupportedNeon(const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsPermuteSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const PermuteDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPermuteWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool IsPooling2dSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling2dDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPooling2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool IsResizeBilinearSupportedNeon(const TensorInfo& input, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| return false; |
| } |
| |
| bool IsSoftmaxSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const SoftmaxDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSoftmaxWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool IsSplitterSupportedNeon(const TensorInfo& input, |
| const ViewsDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsFakeQuantizationSupportedNeon(const TensorInfo& input, |
| const FakeQuantizationDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| ignore_unused(descriptor); |
| return false; |
| } |
| |
| bool IsReshapeSupportedNeon(const TensorInfo& input, |
| std::string* reasonIfUnsupported) |
| { |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool IsFloorSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(output); |
| return IsNeonBackendSupported(reasonIfUnsupported) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &FalseFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool IsLstmSupportedNeon(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 TensorInfo& inputToForgetWeights, const TensorInfo& inputToCellWeights, |
| const TensorInfo& inputToOutputWeights, const TensorInfo& recurrentToForgetWeights, |
| const TensorInfo& recurrentToCellWeights, const TensorInfo& recurrentToOutputWeights, |
| const TensorInfo& forgetGateBias, const TensorInfo& cellBias, |
| const TensorInfo& outputGateBias, const TensorInfo* inputToInputWeights, |
| const TensorInfo* recurrentToInputWeights, const TensorInfo* cellToInputWeights, |
| const TensorInfo* inputGateBias, const TensorInfo* projectionWeights, |
| const TensorInfo* projectionBias, const TensorInfo* cellToForgetWeights, |
| const TensorInfo* cellToOutputWeights, std::string* reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| ignore_unused(outputStateIn); |
| ignore_unused(cellStateIn); |
| ignore_unused(scratchBuffer); |
| ignore_unused(outputStateOut); |
| ignore_unused(cellStateOut); |
| ignore_unused(output); |
| ignore_unused(descriptor); |
| ignore_unused(inputToForgetWeights); |
| ignore_unused(inputToCellWeights); |
| ignore_unused(inputToOutputWeights); |
| ignore_unused(recurrentToForgetWeights); |
| ignore_unused(recurrentToCellWeights); |
| ignore_unused(recurrentToOutputWeights); |
| ignore_unused(forgetGateBias); |
| ignore_unused(cellBias); |
| ignore_unused(outputGateBias); |
| ignore_unused(inputToInputWeights); |
| ignore_unused(recurrentToInputWeights); |
| ignore_unused(cellToInputWeights); |
| ignore_unused(inputGateBias); |
| ignore_unused(projectionWeights); |
| ignore_unused(projectionBias); |
| ignore_unused(cellToForgetWeights); |
| ignore_unused(cellToOutputWeights); |
| return false; |
| } |
| |
| bool IsConvertFp16ToFp32SupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| ignore_unused(output); |
| return true; |
| } |
| |
| bool IsConvertFp32ToFp16SupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| std::string* reasonIfUnsupported) |
| { |
| ignore_unused(input); |
| ignore_unused(output); |
| return true; |
| } |
| |
| bool IsMeanSupportedNeon(const TensorInfo& input, |
| const TensorInfo& output, |
| const MeanDescriptor& descriptor, |
| std::string* reasonIfUnsupported) |
| { |
| return false; |
| } |
| |
| } |