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Diffstat (limited to 'src/armnn/backends/NeonLayerSupport.cpp')
| -rw-r--r-- | src/armnn/backends/NeonLayerSupport.cpp | 468 |
1 files changed, 0 insertions, 468 deletions
diff --git a/src/armnn/backends/NeonLayerSupport.cpp b/src/armnn/backends/NeonLayerSupport.cpp deleted file mode 100644 index 30956dfba0..0000000000 --- a/src/armnn/backends/NeonLayerSupport.cpp +++ /dev/null @@ -1,468 +0,0 @@ -// -// 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 "NeonWorkloads/NeonAdditionFloatWorkload.hpp" -#include "NeonWorkloads/NeonActivationFloatWorkload.hpp" -#include "NeonWorkloads/NeonBatchNormalizationFloatWorkload.hpp" -#include "NeonWorkloads/NeonConvolution2dBaseWorkload.hpp" -#include "NeonWorkloads/NeonDepthwiseConvolutionBaseWorkload.hpp" -#include "NeonWorkloads/NeonL2NormalizationFloatWorkload.hpp" -#include "NeonWorkloads/NeonMultiplicationFloatWorkload.hpp" -#include "NeonWorkloads/NeonNormalizationFloatWorkload.hpp" -#include "NeonWorkloads/NeonFullyConnectedFloatWorkload.hpp" -#include "NeonWorkloads/NeonPermuteWorkload.hpp" -#include "NeonWorkloads/NeonPooling2dBaseWorkload.hpp" -#include "NeonWorkloads/NeonSoftmaxBaseWorkload.hpp" -#include "NeonWorkloads/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, - std::string* reasonIfUnsupported) -{ - FORWARD_WORKLOAD_VALIDATE_FUNC(NeonL2NormalizationWorkloadValidate, reasonIfUnsupported, input, output); -} - -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; -} - -} |