diff options
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/RefBatchNormalizationWorkload.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/RefBatchNormalizationWorkload.cpp')
-rw-r--r-- | src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp | 45 |
1 files changed, 45 insertions, 0 deletions
diff --git a/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp new file mode 100644 index 0000000000..b43b104459 --- /dev/null +++ b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp @@ -0,0 +1,45 @@ +// +// Copyright © 2017 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "RefBatchNormalizationWorkload.hpp" + +#include "BatchNormImpl.hpp" +#include "RefWorkloadUtils.hpp" + +#include "Profiling.hpp" + +namespace armnn +{ + +RefBatchNormalizationWorkload::RefBatchNormalizationWorkload(const BatchNormalizationQueueDescriptor& descriptor, + const WorkloadInfo& info) + : BaseWorkload(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 RefBatchNormalizationWorkload::Execute() const +{ + ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefBatchNormalizationWorkload_Execute"); + + std::unique_ptr<Decoder<float>> meanDecoder = MakeDecoder<float>(GetTensorInfo(m_Mean.get()), + m_Mean.get()->Map(true)); + std::unique_ptr<Decoder<float>> varianceDecoder = MakeDecoder<float>(GetTensorInfo(m_Variance.get()), + m_Variance.get()->Map(true)); + std::unique_ptr<Decoder<float>> gammaDecoder = MakeDecoder<float>(GetTensorInfo(m_Gamma.get()), + m_Gamma.get()->Map(true)); + std::unique_ptr<Decoder<float>> betaDecoder = MakeDecoder<float>(GetTensorInfo(m_Beta.get()), + m_Beta.get()->Map(true)); + std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[0]), + m_Data.m_Inputs[0]->Map()); + std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]), + m_Data.m_Outputs[0]->Map()); + + BatchNormImpl(m_Data, *meanDecoder, *varianceDecoder, *betaDecoder, *gammaDecoder, *inputDecoder, *outputEncoder); +} + +} //namespace armnn |