// // Copyright © 2017 Arm Ltd. All rights reserved. // SPDX-License-Identifier: MIT // #include "ClLayerSupport.hpp" #include "ClBackendId.hpp" #include #include #include #include #include #if defined(ARMCOMPUTECL_ENABLED) #include #include "workloads/ClAdditionWorkload.hpp" #include "workloads/ClActivationWorkload.hpp" #include "workloads/ClBatchNormalizationFloatWorkload.hpp" #include "workloads/ClBatchToSpaceNdWorkload.hpp" #include "workloads/ClConvertFp16ToFp32Workload.hpp" #include "workloads/ClConvertFp32ToFp16Workload.hpp" #include "workloads/ClConvolution2dWorkload.hpp" #include "workloads/ClDequantizeWorkload.hpp" #include "workloads/ClDepthwiseConvolutionWorkload.hpp" #include "workloads/ClDivisionFloatWorkload.hpp" #include "workloads/ClFullyConnectedWorkload.hpp" #include "workloads/ClGreaterWorkload.hpp" #include "workloads/ClL2NormalizationFloatWorkload.hpp" #include "workloads/ClLstmFloatWorkload.hpp" #include "workloads/ClMaximumWorkload.hpp" #include "workloads/ClMeanWorkload.hpp" #include "workloads/ClConcatWorkload.hpp" #include "workloads/ClMinimumWorkload.hpp" #include "workloads/ClMultiplicationWorkload.hpp" #include "workloads/ClNormalizationFloatWorkload.hpp" #include "workloads/ClPadWorkload.hpp" #include "workloads/ClPermuteWorkload.hpp" #include "workloads/ClPooling2dWorkload.hpp" #include "workloads/ClPreluWorkload.hpp" #include "workloads/ClReshapeWorkload.hpp" #include "workloads/ClResizeWorkload.hpp" #include "workloads/ClQuantizedLstmWorkload.hpp" #include "workloads/ClQuantizeWorkload.hpp" #include "workloads/ClSoftmaxBaseWorkload.hpp" #include "workloads/ClSpaceToBatchNdWorkload.hpp" #include "workloads/ClSpaceToDepthWorkload.hpp" #include "workloads/ClSplitterWorkload.hpp" #include "workloads/ClStackWorkload.hpp" #include "workloads/ClStridedSliceWorkload.hpp" #include "workloads/ClSubtractionWorkload.hpp" #include "workloads/ClTransposeConvolution2dWorkload.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(Optional reasonIfUnsupported) { #if defined(ARMCOMPUTECL_ENABLED) return true; #else if (reasonIfUnsupported) { reasonIfUnsupported.value() = "The armnn library has been built without CL support"; } return false; #endif } #if defined(ARMCOMPUTECL_ENABLED) #define FORWARD_CL_LAYER_SUPPORT_FUNC(expr) (expr) #else #define FORWARD_CL_LAYER_SUPPORT_FUNC(expr) IsClBackendSupported(reasonIfUnsupported) #endif #if defined(ARMCOMPUTECL_ENABLED) template inline bool IsWorkloadSupported(FuncType&& func, Optional 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.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 IsClBackendSupported(reasonIfUnsupported); #endif template bool IsSupportedForDataTypeCl(Optional reasonIfUnsupported, DataType dataType, FloatFunc floatFuncPtr, Uint8Func uint8FuncPtr, Params&&... params) { return IsClBackendSupported(reasonIfUnsupported) && IsSupportedForDataTypeGeneric(reasonIfUnsupported, dataType, floatFuncPtr, floatFuncPtr, uint8FuncPtr, &FalseFunc<>, &FalseFunc<>, std::forward(params)...); } } // anonymous namespace bool ClLayerSupport::IsActivationSupported(const TensorInfo& input, const TensorInfo& output, const ActivationDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClActivationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsAdditionSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClAdditionValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsBatchNormalizationSupported(const TensorInfo& input, const TensorInfo& output, const TensorInfo& mean, const TensorInfo& var, const TensorInfo& beta, const TensorInfo& gamma, const BatchNormalizationDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClBatchNormalizationValidate, reasonIfUnsupported, input, output, mean, var, beta, gamma, descriptor); } bool ClLayerSupport::IsBatchToSpaceNdSupported(const TensorInfo& input, const TensorInfo& output, const BatchToSpaceNdDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClBatchToSpaceNdWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsConcatSupported(const std::vector inputs, const TensorInfo& output, const ConcatDescriptor& descriptor, Optional reasonIfUnsupported) const { if (descriptor.GetNumDimensions() <= descriptor.GetConcatAxis()) { SetValueChecked(reasonIfUnsupported, "Cl 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(ClConcatWorkloadValidate, reasonIfUnsupported, inputs, output, descriptor); } else if (concatInnerAxis == 3) { // We rely on the sub-tensor optimization to handle the batch dimension for 4D tensors. If we can't use // sub-tensors for this then we can't support it. Here is where we check that the sub-tensors will work. for (auto& input : inputs) { if (input && !output.IsTypeSpaceMatch(*input)) // Cannot use sub-tensors if the types are not same space { SetValueChecked(reasonIfUnsupported, "Cl Concat: Types and quantization parameters must match."); return false; } } return true; // Sub-tensors support concat along batch } else // > 4 dimensions not supported. { SetValueChecked(reasonIfUnsupported, "Cl Concat: Maximum of 4 dimensions supported."); return false; } } bool ClLayerSupport::IsConstantSupported(const TensorInfo& output, Optional reasonIfUnsupported) const { return IsSupportedForDataTypeCl(reasonIfUnsupported, output.GetDataType(), &TrueFunc<>, &TrueFunc<>); } bool ClLayerSupport::IsConvertFp16ToFp32Supported(const TensorInfo& input, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvertFp16ToFp32WorkloadValidate, reasonIfUnsupported, input, output); } bool ClLayerSupport::IsConvertFp32ToFp16Supported(const TensorInfo& input, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvertFp32ToFp16WorkloadValidate, reasonIfUnsupported, input, output); } bool ClLayerSupport::IsConvolution2dSupported(const TensorInfo& input, const TensorInfo& output, const Convolution2dDescriptor& descriptor, const TensorInfo& weights, const Optional& biases, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClConvolution2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } bool ClLayerSupport::IsDequantizeSupported(const TensorInfo& input, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClDequantizeWorkloadValidate, reasonIfUnsupported, input, output); } bool ClLayerSupport::IsDepthwiseConvolutionSupported(const TensorInfo& input, const TensorInfo& output, const DepthwiseConvolution2dDescriptor& descriptor, const TensorInfo& weights, const Optional& biases, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClDepthwiseConvolutionWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } bool ClLayerSupport::IsDilatedDepthwiseConvolutionSupported(const TensorInfo& input, const TensorInfo& output, const DepthwiseConvolution2dDescriptor& descriptor, const TensorInfo& weights, const Optional& biases, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClDepthwiseConvolutionWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } bool ClLayerSupport::IsDivisionSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClDivisionWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsFloorSupported(const TensorInfo& input, const TensorInfo& output, Optional reasonIfUnsupported) const { ignore_unused(output); return IsClBackendSupported(reasonIfUnsupported) && IsSupportedForDataTypeGeneric(reasonIfUnsupported, input.GetDataType(), &FalseFuncF16<>, &TrueFunc<>, &FalseFuncU8<>, &FalseFuncI32<>, &FalseFuncU8<>); } bool ClLayerSupport::IsFullyConnectedSupported(const TensorInfo& input, const TensorInfo& output, const TensorInfo& weights, const TensorInfo& biases, const FullyConnectedDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClFullyConnectedWorkloadValidate, reasonIfUnsupported, input, output, weights, biases, descriptor); } bool ClLayerSupport::IsGreaterSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClGreaterWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsInputSupported(const TensorInfo& input, Optional reasonIfUnsupported) const { return IsClBackendSupported(reasonIfUnsupported); } bool ClLayerSupport::IsL2NormalizationSupported(const TensorInfo& input, const TensorInfo& output, const L2NormalizationDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClL2NormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::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 reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClLstmFloatWorkloadValidate, reasonIfUnsupported, input, outputStateIn, cellStateIn, scratchBuffer, outputStateOut, cellStateOut, output, descriptor, paramsInfo); } bool ClLayerSupport::IsMaximumSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClMaximumWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsMeanSupported(const TensorInfo& input, const TensorInfo& output, const MeanDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClMeanValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsMergerSupported(const std::vector inputs, const TensorInfo& output, const MergerDescriptor& descriptor, Optional reasonIfUnsupported) const { return IsConcatSupported(inputs, output, descriptor, reasonIfUnsupported); } bool ClLayerSupport::IsMinimumSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClMinimumWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsMultiplicationSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClMultiplicationWorkloadValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsNormalizationSupported(const TensorInfo& input, const TensorInfo& output, const NormalizationDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClNormalizationWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsOutputSupported(const TensorInfo& output, Optional reasonIfUnsupported) const { return IsClBackendSupported(reasonIfUnsupported); } bool ClLayerSupport::IsPadSupported(const TensorInfo& input, const TensorInfo& output, const PadDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClPadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsPermuteSupported(const TensorInfo& input, const TensorInfo& output, const PermuteDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClPermuteWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsPooling2dSupported(const TensorInfo& input, const TensorInfo& output, const Pooling2dDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClPooling2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsPreluSupported(const armnn::TensorInfo &input, const armnn::TensorInfo &alpha, const armnn::TensorInfo &output, armnn::Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClPreluWorkloadValidate, reasonIfUnsupported, input, alpha, output); } bool ClLayerSupport::IsQuantizedLstmSupported(const TensorInfo& input, const TensorInfo& previousCellStateIn, const TensorInfo& previousOutputIn, const TensorInfo& cellStateOut, const TensorInfo& output, const QuantizedLstmInputParamsInfo& paramsInfo, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClQuantizedLstmWorkloadValidate, reasonIfUnsupported, input, previousCellStateIn, previousOutputIn, cellStateOut, output, paramsInfo); } bool ClLayerSupport::IsQuantizeSupported(const TensorInfo& input, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClQuantizeWorkloadValidate, reasonIfUnsupported, input, output); } bool ClLayerSupport::IsReshapeSupported(const TensorInfo& input, const TensorInfo& output, const ReshapeDescriptor& descriptor, Optional reasonIfUnsupported) const { ignore_unused(descriptor); FORWARD_WORKLOAD_VALIDATE_FUNC(ClReshapeWorkloadValidate, reasonIfUnsupported, input, output); } bool ClLayerSupport::IsResizeSupported(const TensorInfo& input, const TensorInfo& output, const ResizeDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClResizeWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsResizeBilinearSupported(const TensorInfo& input, const TensorInfo& output, Optional 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 ClLayerSupport::IsSoftmaxSupported(const TensorInfo& input, const TensorInfo& output, const SoftmaxDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClSoftmaxWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsSpaceToBatchNdSupported(const TensorInfo& input, const TensorInfo& output, const SpaceToBatchNdDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClSpaceToBatchNdWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsSpaceToDepthSupported(const TensorInfo& input, const TensorInfo& output, const SpaceToDepthDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClSpaceToDepthWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsSplitterSupported(const TensorInfo& input, const ViewsDescriptor& descriptor, Optional reasonIfUnsupported) const { ignore_unused(descriptor); return IsSupportedForDataTypeCl(reasonIfUnsupported, input.GetDataType(), &TrueFunc<>, &TrueFunc<>); } bool ClLayerSupport::IsSplitterSupported(const TensorInfo& input, const std::vector>& outputs, const ViewsDescriptor& descriptor, Optional reasonIfUnsupported) const { #if defined(ARMCOMPUTECL_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 splitAxis = ComputeSplitAxis(descriptor, input.GetShape()); if (descriptor.GetNumDimensions() > 2 && splitAxis.size() == 1 && *splitAxis.begin() == descriptor.GetNumDimensions() - 1 ) { FORWARD_WORKLOAD_VALIDATE_FUNC(ClSplitterWorkloadValidate, reasonIfUnsupported, input, outputs, *splitAxis.begin()); } #endif for (auto output : outputs) { if (!input.IsTypeSpaceMatch(output)) // Cannot use sub-tensors if the types are not same space { SetValueChecked(reasonIfUnsupported, "Cl Splitter: Types and quantization parameters must match."); return false; } } return true; } bool ClLayerSupport::IsStackSupported(const std::vector& inputs, const TensorInfo& output, const StackDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClStackWorkloadValidate, reasonIfUnsupported, inputs, output, descriptor); } bool ClLayerSupport::IsStridedSliceSupported(const TensorInfo& input, const TensorInfo& output, const StridedSliceDescriptor& descriptor, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClStridedSliceWorkloadValidate, reasonIfUnsupported, input, output, descriptor); } bool ClLayerSupport::IsSubtractionSupported(const TensorInfo& input0, const TensorInfo& input1, const TensorInfo& output, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClSubtractionValidate, reasonIfUnsupported, input0, input1, output); } bool ClLayerSupport::IsTransposeConvolution2dSupported(const TensorInfo& input, const TensorInfo& output, const TransposeConvolution2dDescriptor& descriptor, const TensorInfo& weights, const Optional& biases, Optional reasonIfUnsupported) const { FORWARD_WORKLOAD_VALIDATE_FUNC(ClTransposeConvolution2dWorkloadValidate, reasonIfUnsupported, input, output, descriptor, weights, biases); } } // namespace armnn