| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "NeonLayerSupport.hpp" |
| #include "NeonBackendId.hpp" |
| |
| #include <armnn/Descriptors.hpp> |
| #include <armnn/Tensor.hpp> |
| #include <armnn/Types.hpp> |
| #include <armnn/BackendRegistry.hpp> |
| |
| #include <InternalTypes.hpp> |
| #include <LayerSupportCommon.hpp> |
| |
| #include <boost/core/ignore_unused.hpp> |
| |
| #if defined(ARMCOMPUTENEON_ENABLED) |
| #include <aclCommon/ArmComputeUtils.hpp> |
| #include <aclCommon/ArmComputeTensorUtils.hpp> |
| #include "workloads/NeonAbsWorkload.hpp" |
| #include "workloads/NeonAdditionWorkload.hpp" |
| #include "workloads/NeonActivationWorkload.hpp" |
| #include "workloads/NeonArgMinMaxWorkload.hpp" |
| #include "workloads/NeonBatchNormalizationWorkload.hpp" |
| #include "workloads/NeonBatchToSpaceNdWorkload.hpp" |
| #include "workloads/NeonConvolution2dWorkload.hpp" |
| #include "workloads/NeonDepthToSpaceWorkload.hpp" |
| #include "workloads/NeonDepthwiseConvolutionWorkload.hpp" |
| #include "workloads/NeonDequantizeWorkload.hpp" |
| #include "workloads/NeonGreaterWorkload.hpp" |
| #include "workloads/NeonInstanceNormalizationWorkload.hpp" |
| #include "workloads/NeonL2NormalizationFloatWorkload.hpp" |
| #include "workloads/NeonLstmFloatWorkload.hpp" |
| #include "workloads/NeonMaximumWorkload.hpp" |
| #include "workloads/NeonMeanWorkload.hpp" |
| #include "workloads/NeonConcatWorkload.hpp" |
| #include "workloads/NeonMinimumWorkload.hpp" |
| #include "workloads/NeonMultiplicationWorkload.hpp" |
| #include "workloads/NeonDivisionWorkload.hpp" |
| #include "workloads/NeonNormalizationFloatWorkload.hpp" |
| #include "workloads/NeonFullyConnectedWorkload.hpp" |
| #include "workloads/NeonPadWorkload.hpp" |
| #include "workloads/NeonPermuteWorkload.hpp" |
| #include "workloads/NeonPooling2dWorkload.hpp" |
| #include "workloads/NeonPreluWorkload.hpp" |
| #include "workloads/NeonQuantizeWorkload.hpp" |
| #include "workloads/NeonQuantizedLstmWorkload.hpp" |
| #include "workloads/NeonReshapeWorkload.hpp" |
| #include "workloads/NeonResizeWorkload.hpp" |
| #include "workloads/NeonRsqrtWorkload.hpp" |
| #include "workloads/NeonSliceWorkload.hpp" |
| #include "workloads/NeonSoftmaxBaseWorkload.hpp" |
| #include "workloads/NeonSpaceToBatchNdWorkload.hpp" |
| #include "workloads/NeonSpaceToDepthWorkload.hpp" |
| #include "workloads/NeonSplitterWorkload.hpp" |
| #include "workloads/NeonStackWorkload.hpp" |
| #include "workloads/NeonStridedSliceWorkload.hpp" |
| #include "workloads/NeonSubtractionWorkload.hpp" |
| #include "workloads/NeonTransposeConvolution2dWorkload.hpp" |
| #endif |
| |
| using namespace boost; |
| |
| namespace armnn |
| { |
| |
| namespace |
| { |
| |
| template< typename ... Args> |
| bool IsNeonBackendSupported(Optional<std::string&> reasonIfUnsupported, Args... args) |
| { |
| boost::ignore_unused(reasonIfUnsupported, (args)...); |
| #if defined(ARMCOMPUTENEON_ENABLED) |
| return true; |
| #else |
| SetValueChecked(reasonIfUnsupported, "The armnn library has been built without NEON support"); |
| return false; |
| #endif |
| } |
| |
| template<typename FloatFunc, typename Uint8Func, typename ... Params> |
| bool IsSupportedForDataTypeNeon(Optional<std::string&> reasonIfUnsupported, |
| DataType dataType, |
| FloatFunc floatFuncPtr, |
| Uint8Func uint8FuncPtr, |
| Params&&... params) |
| { |
| return IsNeonBackendSupported(reasonIfUnsupported) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| dataType, |
| floatFuncPtr, |
| floatFuncPtr, |
| uint8FuncPtr, |
| &FalseFunc<>, |
| &FalseFunc<>, |
| std::forward<Params>(params)...); |
| } |
| |
| #if defined(ARMCOMPUTENEON_ENABLED) |
| template<class FuncType, class... Args> |
| inline bool IsWorkloadSupported(FuncType& func, Optional<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.value() = 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, __VA_ARGS__); |
| #endif |
| } // anonymous namespace |
| |
| bool NeonLayerSupport::IsAbsSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ElementwiseUnaryDescriptor descriptor(UnaryOperation::Abs); |
| return IsElementwiseUnarySupported(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool NeonLayerSupport::IsActivationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ActivationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(descriptor); |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonActivationWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsAdditionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonAdditionWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsArgMinMaxSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ArgMinMaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonArgMinMaxWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsBatchNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& mean, |
| const TensorInfo& var, |
| const TensorInfo& beta, |
| const TensorInfo& gamma, |
| const BatchNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonBatchNormalizationValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| mean, |
| var, |
| beta, |
| gamma, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsBatchToSpaceNdSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const BatchToSpaceNdDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonBatchToSpaceNdWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsComparisonSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| const ComparisonDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| if (descriptor.m_Operation == ComparisonOperation::Greater) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonGreaterWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| return false; |
| } |
| |
| bool NeonLayerSupport::IsConcatSupported(const std::vector<const TensorInfo*> inputs, |
| const TensorInfo& output, |
| const ConcatDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| if (descriptor.GetNumDimensions() <= descriptor.GetConcatAxis()) |
| { |
| SetValueChecked(reasonIfUnsupported, "Neon Concat: Concat axis > Number of dimensions."); |
| return false; |
| } |
| |
| unsigned int concatInnerAxis = (descriptor.GetNumDimensions() - descriptor.GetConcatAxis()) - 1; |
| if(concatInnerAxis < 3) // Width, height, or channels |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonConcatWorkloadValidate, |
| reasonIfUnsupported, |
| inputs, |
| output, |
| descriptor); |
| } |
| else if (concatInnerAxis == 3) |
| { |
| for (auto& input : inputs) |
| { |
| if (input && !output.IsTypeSpaceMatch(*input)) // Cannot use sub-tensors if the types are not same space |
| { |
| SetValueChecked(reasonIfUnsupported, "Neon Concat: Types and quantization parameters must match."); |
| return false; |
| } |
| } |
| return true; // Sub-tensors support concat along batch |
| } |
| else // > 4 dimensions not supported. |
| { |
| SetValueChecked(reasonIfUnsupported, "Neon Concat: Maximum of 4 dimensions supported."); |
| return false; |
| } |
| } |
| |
| bool NeonLayerSupport::IsConstantSupported(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| output.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool NeonLayerSupport::IsConvertFp16ToFp32Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(input); |
| ignore_unused(output); |
| ignore_unused(reasonIfUnsupported); |
| return true; |
| } |
| |
| bool NeonLayerSupport::IsConvertFp32ToFp16Supported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(input); |
| ignore_unused(output); |
| ignore_unused(reasonIfUnsupported); |
| return true; |
| } |
| |
| bool NeonLayerSupport::IsConvolution2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Convolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonConvolution2dWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| bool NeonLayerSupport::IsDepthToSpaceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthToSpaceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDepthToSpaceWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsDepthwiseConvolutionSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDepthwiseConvolutionWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| bool NeonLayerSupport::IsDequantizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDequantizeWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsDilatedDepthwiseConvolutionSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const DepthwiseConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDepthwiseConvolutionWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| bool NeonLayerSupport::IsElementwiseUnarySupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ElementwiseUnaryDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| if (descriptor.m_Operation == UnaryOperation::Abs) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonAbsWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output); |
| } |
| else if (descriptor.m_Operation == UnaryOperation::Rsqrt) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonRsqrtWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output); |
| } |
| |
| return false; |
| } |
| |
| bool NeonLayerSupport::IsFloorSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(output); |
| return IsNeonBackendSupported(reasonIfUnsupported) && |
| IsSupportedForDataTypeGeneric(reasonIfUnsupported, |
| input.GetDataType(), |
| &FalseFuncF16<>, |
| &TrueFunc<>, |
| &FalseFuncU8<>, |
| &FalseFuncI32<>, |
| &FalseFuncU8<>); |
| } |
| |
| bool NeonLayerSupport::IsFullyConnectedSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TensorInfo& weights, |
| const TensorInfo& biases, |
| const FullyConnectedDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonFullyConnectedWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| weights, |
| biases, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsGreaterSupported(const armnn::TensorInfo& input0, |
| const armnn::TensorInfo& input1, |
| const armnn::TensorInfo& output, |
| armnn::Optional<std::string&> reasonIfUnsupported) const |
| { |
| ComparisonDescriptor descriptor(ComparisonOperation::Greater); |
| return IsComparisonSupported(input0, input1, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool NeonLayerSupport::IsInputSupported(const TensorInfo& input, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return IsNeonBackendSupported(reasonIfUnsupported, input); |
| } |
| |
| bool NeonLayerSupport::IsInstanceNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const InstanceNormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonInstanceNormalizationWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsL2NormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const L2NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonL2NormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool NeonLayerSupport::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 |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonLstmFloatWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| outputStateIn, |
| cellStateIn, |
| scratchBuffer, |
| outputStateOut, |
| cellStateOut, |
| output, |
| descriptor, |
| paramsInfo); |
| } |
| |
| bool NeonLayerSupport::IsMaximumSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonMaximumWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsMeanSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const MeanDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonMeanWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsMergerSupported(const std::vector<const TensorInfo*> inputs, |
| const TensorInfo& output, |
| const MergerDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return IsConcatSupported(inputs, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool NeonLayerSupport::IsMinimumSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonMinimumWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsMultiplicationSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonMultiplicationWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsDivisionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonDivisionWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsNormalizationSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const NormalizationDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonNormalizationWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsOutputSupported(const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| return IsNeonBackendSupported(reasonIfUnsupported, output); |
| } |
| |
| bool NeonLayerSupport::IsPadSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PadDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPadWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsPermuteSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const PermuteDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPermuteWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool NeonLayerSupport::IsPooling2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const Pooling2dDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPooling2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool NeonLayerSupport::IsPreluSupported(const armnn::TensorInfo &input, |
| const armnn::TensorInfo &alpha, |
| const armnn::TensorInfo &output, |
| armnn::Optional<std::string &> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonPreluWorkloadValidate, reasonIfUnsupported, input, alpha, output); |
| } |
| |
| bool NeonLayerSupport::IsQuantizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonQuantizeWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsQuantizedLstmSupported(const TensorInfo& input, |
| const TensorInfo& cellStateIn, |
| const TensorInfo& outputStateIn, |
| const TensorInfo& cellStateOut, |
| const TensorInfo& outputStateOut, |
| const QuantizedLstmInputParamsInfo& paramsInfo, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonQuantizedLstmWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| cellStateIn, |
| outputStateIn, |
| cellStateOut, |
| outputStateOut, |
| paramsInfo); |
| } |
| |
| bool NeonLayerSupport::IsReshapeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ReshapeDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(descriptor); |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonReshapeWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsResizeSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const ResizeDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonResizeWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsResizeBilinearSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ResizeDescriptor descriptor; |
| descriptor.m_Method = ResizeMethod::Bilinear; |
| descriptor.m_DataLayout = DataLayout::NCHW; |
| |
| const TensorShape& outputShape = output.GetShape(); |
| descriptor.m_TargetHeight = outputShape[2]; |
| descriptor.m_TargetWidth = outputShape[3]; |
| |
| return IsResizeSupported(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool NeonLayerSupport::IsRsqrtSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ElementwiseUnaryDescriptor descriptor(UnaryOperation::Rsqrt); |
| return IsElementwiseUnarySupported(input, output, descriptor, reasonIfUnsupported); |
| } |
| |
| bool NeonLayerSupport::IsSliceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SliceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSliceWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsSoftmaxSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SoftmaxDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSoftmaxWorkloadValidate, reasonIfUnsupported, input, output, descriptor); |
| } |
| |
| bool NeonLayerSupport::IsSpaceToBatchNdSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SpaceToBatchNdDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSpaceToBatchNdWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsSpaceToDepthSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const SpaceToDepthDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSpaceToDepthWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsSplitterSupported(const TensorInfo& input, |
| const ViewsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| ignore_unused(descriptor); |
| return IsSupportedForDataTypeNeon(reasonIfUnsupported, |
| input.GetDataType(), |
| &TrueFunc<>, |
| &TrueFunc<>); |
| } |
| |
| bool NeonLayerSupport::IsSplitterSupported(const TensorInfo& input, |
| const std::vector<std::reference_wrapper<TensorInfo>>& outputs, |
| const ViewsDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| #if defined(ARMCOMPUTENEON_ENABLED) |
| // Split along the last dimension, cannot use sub-tensors |
| // as width and height of the sub-tensors do not match |
| // the width and height of the parent tensor |
| // in case of input with more than 2D. |
| std::set<unsigned int> splitAxis = ComputeSplitAxis(descriptor, input.GetShape()); |
| if (descriptor.GetNumDimensions() > 2 && splitAxis.size() == 1 && |
| *splitAxis.begin() == descriptor.GetNumDimensions() - 1 ) |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSplitterWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| outputs, |
| *splitAxis.begin()); |
| } |
| #endif |
| boost::ignore_unused(descriptor); |
| for (auto output : outputs) |
| { |
| if (!input.IsTypeSpaceMatch(output)) // Cannot use sub-tensors if the types are not same space |
| { |
| SetValueChecked(reasonIfUnsupported, "Neon Splitter: Types and quantization parameters must match."); |
| return false; |
| } |
| } |
| return true; |
| } |
| |
| bool NeonLayerSupport::IsStackSupported(const std::vector<const TensorInfo*>& inputs, |
| const TensorInfo& output, |
| const StackDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonStackWorkloadValidate, |
| reasonIfUnsupported, |
| inputs, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsStridedSliceSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const StridedSliceDescriptor& descriptor, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonStridedSliceWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor); |
| } |
| |
| bool NeonLayerSupport::IsSubtractionSupported(const TensorInfo& input0, |
| const TensorInfo& input1, |
| const TensorInfo& output, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonSubtractionWorkloadValidate, |
| reasonIfUnsupported, |
| input0, |
| input1, |
| output); |
| } |
| |
| bool NeonLayerSupport::IsTransposeConvolution2dSupported(const TensorInfo& input, |
| const TensorInfo& output, |
| const TransposeConvolution2dDescriptor& descriptor, |
| const TensorInfo& weights, |
| const Optional<TensorInfo>& biases, |
| Optional<std::string&> reasonIfUnsupported) const |
| { |
| FORWARD_WORKLOAD_VALIDATE_FUNC(NeonTransposeConvolution2dWorkloadValidate, |
| reasonIfUnsupported, |
| input, |
| output, |
| descriptor, |
| weights, |
| biases); |
| } |
| |
| } // namespace armnn |
