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Diffstat (limited to 'src/armnn/backends/NeonWorkloads/NeonBatchNormalizationFloat32Workload.cpp')
-rw-r--r-- | src/armnn/backends/NeonWorkloads/NeonBatchNormalizationFloat32Workload.cpp | 45 |
1 files changed, 45 insertions, 0 deletions
diff --git a/src/armnn/backends/NeonWorkloads/NeonBatchNormalizationFloat32Workload.cpp b/src/armnn/backends/NeonWorkloads/NeonBatchNormalizationFloat32Workload.cpp new file mode 100644 index 0000000000..f107c8137f --- /dev/null +++ b/src/armnn/backends/NeonWorkloads/NeonBatchNormalizationFloat32Workload.cpp @@ -0,0 +1,45 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// See LICENSE file in the project root for full license information. +// + +#include "NeonBatchNormalizationFloat32Workload.hpp" +#include "backends/CpuTensorHandle.hpp" +#include "backends/ArmComputeTensorUtils.hpp" + +namespace armnn +{ +using namespace armcomputetensorutils; + +NeonBatchNormalizationFloat32Workload::NeonBatchNormalizationFloat32Workload( + const BatchNormalizationQueueDescriptor& descriptor, const WorkloadInfo& info) + : Float32Workload<BatchNormalizationQueueDescriptor>(descriptor, info) +{ + m_Data.ValidateInputsOutputs("NeonBatchNormalizationFloat32Workload", 1, 1); + + 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_Mean, m_Data.m_Mean->GetTensorInfo()); + BuildArmComputeTensor(m_Variance, m_Data.m_Variance->GetTensorInfo()); + BuildArmComputeTensor(m_Gamma, m_Data.m_Gamma->GetTensorInfo()); + BuildArmComputeTensor(m_Beta, m_Data.m_Beta->GetTensorInfo()); + + m_Layer.configure( + &input, &output, &m_Mean, &m_Variance, &m_Beta, &m_Gamma, m_Data.m_Parameters.m_Eps); + + InitialiseArmComputeTensorData(m_Mean, m_Data.m_Mean->GetConstTensor<float>()); + InitialiseArmComputeTensorData(m_Variance, m_Data.m_Variance->GetConstTensor<float>()); + InitialiseArmComputeTensorData(m_Gamma, m_Data.m_Gamma->GetConstTensor<float>()); + InitialiseArmComputeTensorData(m_Beta, m_Data.m_Beta->GetConstTensor<float>()); +} + +void NeonBatchNormalizationFloat32Workload::Execute() const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuAcc, "NeonBatchNormalizationFloat32Workload_Execute"); + m_Layer.run(); +} + +} //namespace armnn + + |