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Diffstat (limited to 'src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp')
-rw-r--r-- | src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp | 91 |
1 files changed, 91 insertions, 0 deletions
diff --git a/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp b/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp new file mode 100644 index 0000000000..11e31c727a --- /dev/null +++ b/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp @@ -0,0 +1,91 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// + +#include "NeonDepthwiseConvolutionFloat32Workload.hpp" +#include "backends/NeonLayerSupport.hpp" +#include "backends/CpuTensorHandle.hpp" +#include "backends/ArmComputeTensorUtils.hpp" + + +namespace armnn +{ +using namespace armcomputetensorutils; + +NeonDepthwiseConvolutionFloat32Workload::NeonDepthwiseConvolutionFloat32Workload( + const DepthwiseConvolution2dQueueDescriptor& descriptor, + const WorkloadInfo& info) + : Float32Workload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info) +{ + const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); + + std::string reasonIfUnsupported; + if (!IsNeonDepthwiseConvolution2dDescParamsSupported(&reasonIfUnsupported, m_Data.m_Parameters, weightInfo)) + { + throw UnimplementedException(reasonIfUnsupported); + } + + BuildArmComputeTensor(m_KernelTensor, weightInfo); + + arm_compute::Tensor* optionalBias = nullptr; + if (m_Data.m_Parameters.m_BiasEnabled) + { + BuildArmComputeTensor(m_BiasTensor, m_Data.m_Bias->GetTensorInfo()); + optionalBias = &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); + + m_Data.ValidateInputsOutputs("NeonDepthwiseConvolutionFloat32Workload", 1, 1); + + arm_compute::ITensor& input = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); + arm_compute::ITensor& output = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + + bool use3x3Optimisation = weightInfo.GetShape()[3] == 3 && weightInfo.GetShape()[2] == 3; + if (use3x3Optimisation) + { + m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer3x3>(); + static_cast<arm_compute::NEDepthwiseConvolutionLayer3x3*>( + m_pDepthwiseConvolutionLayer.get())->configure(&input, + &m_KernelTensor, + optionalBias, + &output, + padStrideInfo); + } + else + { + m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer>(); + static_cast<arm_compute::NEDepthwiseConvolutionLayer*>( + m_pDepthwiseConvolutionLayer.get())->configure(&input, + &m_KernelTensor, + optionalBias, + &output, + padStrideInfo); + } + + BOOST_ASSERT(m_pDepthwiseConvolutionLayer); + + InitialiseArmComputeTensorData(m_KernelTensor, m_Data.m_Weight->GetConstTensor<float>()); + + if (optionalBias) + { + InitialiseArmComputeTensorData(*optionalBias, m_Data.m_Bias->GetConstTensor<float>()); + } +} + +void NeonDepthwiseConvolutionFloat32Workload::Execute() const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::GpuAcc, "NeonDepthwiseConvolutionFloat32Workload_Execute"); + BOOST_ASSERT(m_pDepthwiseConvolutionLayer); + + m_pDepthwiseConvolutionLayer->run(); +} + +} //namespace armnn |