// // Copyright © 2017 Arm Ltd. All rights reserved. // See LICENSE file in the project root for full license information. // #include "LayerSupportCommon.hpp" #include "ClLayerSupport.hpp" #include "InternalTypes.hpp" #include #include #include #include #ifdef ARMCOMPUTECL_ENABLED #include "ClWorkloads/ClAdditionFloat32Workload.hpp" #include "ClWorkloads/ClActivationFloat32Workload.hpp" #include "ClWorkloads/ClBatchNormalizationFloat32Workload.hpp" #include "ClWorkloads/ClConvertFp16ToFp32Workload.hpp" #include "ClWorkloads/ClConvertFp32ToFp16Workload.hpp" #include "ClWorkloads/ClConvolution2dBaseWorkload.hpp" #include "ClWorkloads/ClDepthwiseConvolutionBaseWorkload.hpp" #include "ClWorkloads/ClL2NormalizationFloat32Workload.hpp" #include "ClWorkloads/ClMultiplicationFloat32Workload.hpp" #include "ClWorkloads/ClFullyConnectedFloat32Workload.hpp" #include "ClWorkloads/ClPooling2dBaseWorkload.hpp" #include "ClWorkloads/ClPermuteWorkload.hpp" #include "ClWorkloads/ClNormalizationFloat32Workload.hpp" #include "ClWorkloads/ClSoftmaxBaseWorkload.hpp" #include "ClWorkloads/ClLstmFloat32Workload.hpp" #endif using namespace boost; namespace armnn { namespace { template bool IsMatchingSize2d(const TensorInfo& weightInfo) { // Width & Height must match. return (weightInfo.GetShape()[3] == FilterSize) && (weightInfo.GetShape()[2] == FilterSize); } template bool IsMatchingStride(uint32_t actualStride) { return ValidStride == actualStride; } template bool IsMatchingStride(uint32_t actualStride) { return IsMatchingStride(actualStride) || IsMatchingStride(actualStride); }; bool IsClBackendSupported(std::string* reasonIfUnsupported) { #if ARMCOMPUTECL_ENABLED return true; #else if (reasonIfUnsupported != nullptr) { *reasonIfUnsupported = "The armnn library has been built without CL support"; } return false; #endif } #if ARMCOMPUTECL_ENABLED #define FORWARD_CL_LAYER_SUPPORT_FUNC(expr) (expr) #else #define FORWARD_CL_LAYER_SUPPORT_FUNC(expr) IsClBackendSupported(reasonIfUnsupported) #endif #if ARMCOMPUTECL_ENABLED template inline bool IsWorkloadSupported(FuncType&& func, std::string* reasonIfUnsupported, Args&&... args) { arm_compute::Status aclStatus = func(std::forward(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 IsClBackendSupported(reasonIfUnsupported); #endif } //namespace template bool IsSupportedForDataTypeCl(std::string* reasonIfUnsupported, DataType dataType, FloatFunc floatFuncPtr, Uint8Func uint8FuncPtr, Params&&... params) { return IsClBackendSupported(reasonIfUnsupported) && IsSupportedForDataTypeGeneric(reasonIfUnsupported, dataType, floatFuncPtr, floatFuncPtr, uint8FuncPtr, std::forward(params)...); } bool IsActivationSupportedCl(const TensorInfo& input, const TensorInfo& output, const ActivationDescriptor& descriptor, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClActivationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool IsAdditionSupportedCl(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, std::string* reasonIfUnsupported) { return FORWARD_CL_LAYER_SUPPORT_FUNC(ClAdditionValidate(input0, input1, output, reasonIfUnsupported)); } bool IsBatchNormalizationSupportedCl(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(ClBatchNormalizationValidate, reasonIfUnsupported, input, output, mean, var, beta, gamma, descriptor); } bool IsConstantSupportedCl(const TensorInfo& output, std::string* reasonIfUnsupported) { return IsSupportedForDataTypeCl(reasonIfUnsupported, output.GetDataType(), &TrueFunc<>, &FalseFuncU8<>); } bool IsClDirectConvolution2dSupported(const TensorInfo& weightInfo, const Convolution2dDescriptor& desc) { bool isSupported = false; bool strideXIsOneOrTwo = IsMatchingStride<1, 2>(desc.m_StrideX); bool strideXIsThree = IsMatchingStride<3>(desc.m_StrideX); bool strideYIsOneOrTwo = IsMatchingStride<1, 2>(desc.m_StrideY); bool strideYIsThree = IsMatchingStride<3>(desc.m_StrideY); bool strideIsOneOrTwo = strideXIsOneOrTwo && strideYIsOneOrTwo; bool strideIsOneOrTwoOrThree = ( strideXIsOneOrTwo || strideXIsThree ) && ( strideYIsOneOrTwo || strideYIsThree ); // 1x1 convolution with strides of 1,2,3. isSupported |= IsMatchingSize2d<1>(weightInfo) && ( strideIsOneOrTwoOrThree ); // 3x3 convolution with strides of 1,2. isSupported |= IsMatchingSize2d<3>(weightInfo) && ( strideIsOneOrTwo ); // 5x5 convolution with strides of 1,2 isSupported |= IsMatchingSize2d<5>(weightInfo) && ( strideIsOneOrTwo ); //Fall back to normal convolution for the asymmetric padding case. if (desc.m_PadLeft != desc.m_PadRight || desc.m_PadTop != desc.m_PadBottom) { //Direct convolution does not support asymmetric padding yet. isSupported = false; } return isSupported; } bool IsDirectConvolution2dParamsSupportedCl(std::string* reasonIfUnsupported, const Convolution2dDescriptor& parameters, const TensorInfo& weightInfo) { return IsClDirectConvolution2dSupported(weightInfo, parameters); } bool IsConvolution2dSupportedCl(const TensorInfo& input, const TensorInfo& output, const Convolution2dDescriptor& descriptor, const TensorInfo& weights, const boost::optional& biases, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvolution2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } bool IsDepthwiseConvolutionSupportedCl(const TensorInfo& input, const TensorInfo& output, const DepthwiseConvolution2dDescriptor& descriptor, const TensorInfo& weights, const boost::optional& biases, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClDepthwiseConvolutionWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } bool IsFullyConnectedSupportedCl(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(ClFullyConnectedWorkloadValidate, reasonIfUnsupported, input, output, weights, biases, descriptor); } bool IsInputSupportedCl(const TensorInfo& input, std::string* reasonIfUnsupported) { return IsSupportedForDataTypeCl(reasonIfUnsupported, input.GetDataType(), &TrueFunc<>, &TrueFunc<>); } bool IsL2NormalizationSupportedCl(const TensorInfo& input, const TensorInfo& output, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClL2NormalizationWorkloadValidate, reasonIfUnsupported, input, output); } bool IsMergerSupportedCl(const std::vector inputs, const OriginsDescriptor& descriptor, std::string* reasonIfUnsupported) { ignore_unused(descriptor); return IsSupportedForDataTypeCl(reasonIfUnsupported, inputs[0]->GetDataType(), &TrueFunc<>, &FalseFuncU8<>); } bool IsMultiplicationSupportedCl(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClMultiplicationWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool IsNormalizationSupportedCl(const TensorInfo& input, const TensorInfo& output, const NormalizationDescriptor& descriptor, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClNormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool IsOutputSupportedCl(const TensorInfo& output, std::string* reasonIfUnsupported) { return IsSupportedForDataTypeCl(reasonIfUnsupported, output.GetDataType(), &TrueFunc<>, &TrueFunc<>); } bool IsPermuteSupportedCl(const TensorInfo& input, const TensorInfo& output, const PermuteDescriptor& descriptor, std::string* reasonIfUnsupported) { ignore_unused(input); ignore_unused(output); FORWARD_WORKLOAD_VALIDATE_FUNC(ClPermuteWorkloadValidate, reasonIfUnsupported, descriptor); } bool IsPooling2dSupportedCl(const TensorInfo& input, const TensorInfo& output, const Pooling2dDescriptor& descriptor, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClPooling2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool IsResizeBilinearSupportedCl(const TensorInfo& input, std::string* reasonIfUnsupported) { return IsSupportedForDataTypeCl(reasonIfUnsupported, input.GetDataType(), &TrueFunc<>, &FalseFuncU8<>); } bool IsSoftmaxSupportedCl(const TensorInfo& input, const TensorInfo& output, const SoftmaxDescriptor& descriptor, std::string* reasonIfUnsupported) { ignore_unused(descriptor); FORWARD_WORKLOAD_VALIDATE_FUNC(ClSoftmaxWorkloadValidate, reasonIfUnsupported, input, output); } bool IsSplitterSupportedCl(const TensorInfo& input, const ViewsDescriptor& descriptor, std::string* reasonIfUnsupported) { ignore_unused(descriptor); return IsSupportedForDataTypeCl(reasonIfUnsupported, input.GetDataType(), &TrueFunc<>, &TrueFunc<>); } bool IsFakeQuantizationSupportedCl(const TensorInfo& input, const FakeQuantizationDescriptor& descriptor, std::string* reasonIfUnsupported) { ignore_unused(input); ignore_unused(descriptor); return false; } bool IsReshapeSupportedCl(const TensorInfo& input, std::string* reasonIfUnsupported) { ignore_unused(input); return true; } bool IsFloorSupportedCl(const TensorInfo& input, const TensorInfo& output, std::string* reasonIfUnsupported) { ignore_unused(output); return IsClBackendSupported(reasonIfUnsupported) && IsSupportedForDataTypeGeneric(reasonIfUnsupported, input.GetDataType(), &FalseFuncF16<>, &TrueFunc<>, &FalseFuncU8<>); } bool IsLstmSupportedCl(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) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClLstmFloat32WorkloadValidate, reasonIfUnsupported, input, outputStateIn, cellStateIn, scratchBuffer, outputStateOut, cellStateOut, output, descriptor, inputToForgetWeights, inputToCellWeights, inputToOutputWeights, recurrentToForgetWeights, recurrentToCellWeights, recurrentToOutputWeights, forgetGateBias, cellBias, outputGateBias, inputToInputWeights, recurrentToInputWeights, cellToInputWeights, inputGateBias, projectionWeights, projectionBias, cellToForgetWeights, cellToOutputWeights); } bool IsConvertFp16ToFp32SupportedCl(const TensorInfo& input, const TensorInfo& output, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvertFp16ToFp32WorkloadValidate, reasonIfUnsupported, input, output, reasonIfUnsupported); } bool IsConvertFp32ToFp16SupportedCl(const TensorInfo& input, const TensorInfo& output, std::string* reasonIfUnsupported) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvertFp32ToFp16WorkloadValidate, reasonIfUnsupported, input, output, reasonIfUnsupported); } }