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Diffstat (limited to 'src/armnn/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp')
-rw-r--r-- | src/armnn/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp | 88 |
1 files changed, 88 insertions, 0 deletions
diff --git a/src/armnn/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp b/src/armnn/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp new file mode 100644 index 0000000000..5099965a24 --- /dev/null +++ b/src/armnn/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp @@ -0,0 +1,88 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// + +#include "backends/CpuTensorHandle.hpp" +#include "backends/ArmComputeTensorUtils.hpp" +#include "backends/NeonLayerSupport.hpp" + +#include "NeonConvolution2dBaseWorkload.hpp" + +namespace armnn +{ + +template<armnn::DataType dataType> +NeonConvolution2dBaseWorkload<dataType>::NeonConvolution2dBaseWorkload(const Convolution2dQueueDescriptor& descriptor, + const WorkloadInfo& info) + : TypedWorkload<Convolution2dQueueDescriptor, dataType>(descriptor, info) +{ + using arm_compute::NEDirectConvolutionLayer; + using namespace armcomputetensorutils; + + ValidateData(); + + // todo: check tensor shapes match + + arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + + BuildArmComputeTensor(m_KernelTensor, m_Data.m_Weight->GetTensorInfo()); + + arm_compute::Tensor* optionalBiasTensor = nullptr; + if (m_Data.m_Parameters.m_BiasEnabled) + { + BuildArmComputeTensor(m_BiasTensor, m_Data.m_Bias->GetTensorInfo()); + optionalBiasTensor = &m_BiasTensor; + } + + arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, + m_Data.m_Parameters.m_StrideY, + m_Data.m_Parameters.m_PadLeft, + m_Data.m_Parameters.m_PadRight, + m_Data.m_Parameters.m_PadTop, + m_Data.m_Parameters.m_PadBottom, + arm_compute::DimensionRoundingType::FLOOR); + + const bool preferDirectConvolution = + IsNeonDirectConvolutionPreferred(m_Data.m_Weight->GetTensorInfo(), + m_Data.m_Parameters); + + if (preferDirectConvolution) + { + auto directConvolutionLayer = std::make_unique<arm_compute::NEDirectConvolutionLayer>(); + directConvolutionLayer->configure(&input, + &m_KernelTensor, + optionalBiasTensor, + &output, + padStrideInfo); + m_ConvolutionLayer.reset(directConvolutionLayer.release()); + } + else + { + auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(); + convolutionLayer->configure(&input, + &m_KernelTensor, + optionalBiasTensor, + &output, + padStrideInfo); + m_ConvolutionLayer.reset(convolutionLayer.release()); + } + BOOST_ASSERT(m_ConvolutionLayer); + + using Type = ResolveType<dataType>; + + InitialiseArmComputeTensorData(m_KernelTensor, m_Data.m_Weight->template GetConstTensor<Type>()); + if (m_Data.m_Parameters.m_BiasEnabled) + { + InitialiseArmComputeTensorData(m_BiasTensor, m_Data.m_Bias->template GetConstTensor<Type>()); + } +} + +// Generate known implementations for linker +template class NeonConvolution2dBaseWorkload<DataType::Float32>; +template class NeonConvolution2dBaseWorkload<DataType::QuantisedAsymm8>; + +} //namespace armnn + + |