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author | arovir01 <Aron.Virginas-Tar@arm.com> | 2018-08-31 15:26:35 +0100 |
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committer | Matthew Bentham <matthew.bentham@arm.com> | 2018-09-17 17:21:25 +0100 |
commit | 9e53a35b66b1ec7ceee7c712380a13596175b83b (patch) | |
tree | d40bf9f27c799184324b6ab91cbb1a546fc4012e /src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp | |
parent | 5540d2f379b15503269d1b9b5fbe8fbafd160d2e (diff) | |
download | armnn-9e53a35b66b1ec7ceee7c712380a13596175b83b.tar.gz |
IVGCVSW-1784: Rename float32 workloads for ACL
Change-Id: I98bdfe9cb12c663d1d5cfa456e2cc967d70ab22b
Diffstat (limited to 'src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp')
-rw-r--r-- | src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp | 94 |
1 files changed, 0 insertions, 94 deletions
diff --git a/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp b/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp deleted file mode 100644 index f94cd903b6..0000000000 --- a/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp +++ /dev/null @@ -1,94 +0,0 @@ -// -// 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) - : FloatWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info) -{ - const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); - - m_KernelTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_KernelTensor, weightInfo); - - if (m_Data.m_Parameters.m_BiasEnabled) - { - m_BiasTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo()); - } - - 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.get(), - m_BiasTensor.get(), - &output, - padStrideInfo); - } - else - { - m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer>(); - static_cast<arm_compute::NEDepthwiseConvolutionLayer*>( - m_pDepthwiseConvolutionLayer.get())->configure(&input, - m_KernelTensor.get(), - m_BiasTensor.get(), - &output, - padStrideInfo); - } - - BOOST_ASSERT(m_pDepthwiseConvolutionLayer); - - InitializeArmComputeTensorDataForFloatTypes(*m_KernelTensor, m_Data.m_Weight); - - if (m_BiasTensor) - { - InitializeArmComputeTensorDataForFloatTypes(*m_BiasTensor, m_Data.m_Bias); - } - - m_pDepthwiseConvolutionLayer->prepare(); - FreeUnusedTensors(); -} - -void NeonDepthwiseConvolutionFloat32Workload::Execute() const -{ - ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthwiseConvolutionFloat32Workload_Execute"); - BOOST_ASSERT(m_pDepthwiseConvolutionLayer); - - m_pDepthwiseConvolutionLayer->run(); -} - -void NeonDepthwiseConvolutionFloat32Workload::FreeUnusedTensors() -{ - FreeTensorIfUnused(m_KernelTensor); - FreeTensorIfUnused(m_BiasTensor); -} - -} //namespace armnn |