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Diffstat (limited to 'src/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp')
| -rw-r--r-- | src/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp | 146 |
1 files changed, 0 insertions, 146 deletions
diff --git a/src/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp b/src/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp deleted file mode 100644 index ee69088691..0000000000 --- a/src/backends/NeonWorkloads/NeonConvolution2dBaseWorkload.cpp +++ /dev/null @@ -1,146 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include <backends/CpuTensorHandle.hpp> -#include <backends/aclCommon/ArmComputeTensorUtils.hpp> -#include <backends/NeonLayerSupport.hpp> - -#include "NeonConvolution2dBaseWorkload.hpp" - -#include <armnn/Types.hpp> -#include <Half.hpp> - -namespace armnn -{ - -using namespace armcomputetensorutils; - -arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo& input, - const TensorInfo& output, - const Convolution2dDescriptor& descriptor, - const TensorInfo& weights, - const boost::optional<TensorInfo>& biases) -{ - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); - const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); - const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout); - - arm_compute::TensorInfo aclBiasesInfo; - arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr; - - if (descriptor.m_BiasEnabled) - { - BOOST_ASSERT(biases.is_initialized()); - - aclBiasesInfo = BuildArmComputeTensorInfo(biases.get(), descriptor.m_DataLayout); - optionalAclBiasesInfo = &aclBiasesInfo; - } - - arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor); - - return arm_compute::NEConvolutionLayer::validate(&aclInputInfo, - &aclWeightsInfo, - optionalAclBiasesInfo, - &aclOutputInfo, - layerInfo); -} - -template<armnn::DataType... dataTypes> -NeonConvolution2dBaseWorkload<dataTypes...>::NeonConvolution2dBaseWorkload( - const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info, - std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager) - : TypedWorkload<Convolution2dQueueDescriptor, dataTypes...>(descriptor, info) -{ - using arm_compute::NEDirectConvolutionLayer; - - 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(); - - m_KernelTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_KernelTensor, m_Data.m_Weight->GetTensorInfo(), descriptor.m_DataLayout); - - if (m_Data.m_Parameters.m_BiasEnabled) - { - m_BiasTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), descriptor.m_DataLayout); - } - - 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>(memoryManager); - directConvolutionLayer->configure(&input, - m_KernelTensor.get(), - m_BiasTensor.get(), - &output, - padStrideInfo); - m_ConvolutionLayer.reset(directConvolutionLayer.release()); - } - else - { - auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager); - convolutionLayer->configure(&input, - m_KernelTensor.get(), - m_BiasTensor.get(), - &output, - padStrideInfo); - m_ConvolutionLayer.reset(convolutionLayer.release()); - } - BOOST_ASSERT(m_ConvolutionLayer); - - armnn::DataType dataType = m_Data.m_Weight->GetTensorInfo().GetDataType(); - - switch (dataType) - { - case DataType::Float16: - { - InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<Half>()); - break; - } - case DataType::Float32: - { - InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<float>()); - break; - } - case DataType::QuantisedAsymm8: - { - InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<uint8_t>()); - break; - } - default: - { - BOOST_ASSERT_MSG(false, "Unknown DataType."); - } - } -} - -template<armnn::DataType... dataTypes> -void NeonConvolution2dBaseWorkload<dataTypes...>::FreeUnusedTensors() -{ - FreeTensorIfUnused(m_KernelTensor); - FreeTensorIfUnused(m_BiasTensor); -} - -// Generates known implementations for linker. -template class NeonConvolution2dBaseWorkload<armnn::DataType::Float16, armnn::DataType::Float32>; -template class NeonConvolution2dBaseWorkload<armnn::DataType::QuantisedAsymm8>; - -} //namespace armnn - |