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| author | Matteo Martincigh <matteo.martincigh@arm.com> | 2019-06-03 16:54:25 +0100 |
|---|---|---|
| committer | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2019-06-04 15:13:51 +0000 |
| commit | 3122bd574a3d29774c535ca2136de361da626e88 (patch) | |
| tree | c2fcc19be67f5a35c30d042b80ba3157ef87bd21 /src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp | |
| parent | 550fe36f687e73c78b57ebfeee9f98fd35f40f24 (diff) | |
| download | armnn-3122bd574a3d29774c535ca2136de361da626e88.tar.gz | |
IVGCVSW-3212 Refactor the Reference BatchNormalization workloads to
handle Float32 and QAsymm8 types
* Removed the type-specific workload implementations
* Added type-independent RefBatchNormalizationWorkload implementation
* Reworked BachNormImpl to use decoders/encoders
* Improved the validation of the BatchNorm queue descriptor
* Fixed unit tests where necessary
Change-Id: Icf3fa1332292d38ec2fa0b1cb984cab78426034b
Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>
Diffstat (limited to 'src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp')
| -rw-r--r-- | src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp | 38 |
1 files changed, 0 insertions, 38 deletions
diff --git a/src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp b/src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp deleted file mode 100644 index 313af9c438..0000000000 --- a/src/backends/reference/workloads/RefBatchNormalizationFloat32Workload.cpp +++ /dev/null @@ -1,38 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// - -#include "RefBatchNormalizationFloat32Workload.hpp" - -#include "BatchNormImpl.hpp" -#include "RefWorkloadUtils.hpp" - -#include "Profiling.hpp" - -namespace armnn -{ -RefBatchNormalizationFloat32Workload::RefBatchNormalizationFloat32Workload( - const BatchNormalizationQueueDescriptor& descriptor, const WorkloadInfo& info) - : Float32Workload<BatchNormalizationQueueDescriptor>(descriptor, info), - m_Mean(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Mean))), - m_Variance(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Variance))), - m_Beta(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Beta))), - m_Gamma(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Gamma))) {} - -void RefBatchNormalizationFloat32Workload::Execute() const -{ - ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefBatchNormalizationFloat32Workload_Execute"); - - const float* var = m_Variance->GetConstTensor<float>(); - const float* mean = m_Mean->GetConstTensor<float>(); - const float* gamma = m_Gamma->GetConstTensor<float>(); - const float* beta = m_Beta->GetConstTensor<float>(); - - auto inputData = GetInputTensorDataFloat(0, m_Data); - auto outputData = GetOutputTensorDataFloat(0, m_Data); - - BatchNormImpl(m_Data, var, mean, gamma, beta, outputData, inputData); -} - -} //namespace armnn |