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authorMatteo Martincigh <matteo.martincigh@arm.com>2019-06-20 12:46:43 +0100
committerMatteo Martincigh <matteo.martincigh@arm.com>2019-06-20 12:51:17 +0100
commit65263959a797e3d93189fc798a6545e79d84106f (patch)
tree82c742a0a349c29b8fcd65f10aceaafc0a68d17e
parent47ea3c0e8d8d10906d04a0e7c537ffee68b0f819 (diff)
downloadarmnn-65263959a797e3d93189fc798a6545e79d84106f.tar.gz
IVGCVSW-3212 Refactor RefBatchNormalizationWorkload
* Refactor the reference batch normalization workload to avoid unnecessary function calls and to improve readibility Change-Id: I49d78dcac7bad36f57bd1eb196c12dbad01cc893 Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>
-rw-r--r--src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp26
1 files changed, 13 insertions, 13 deletions
diff --git a/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp
index b43b104459..54e7d0d38b 100644
--- a/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp
+++ b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp
@@ -26,20 +26,20 @@ 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());
+ std::unique_ptr<Decoder<float>> meanDecoder = MakeDecoder<float>(m_Mean->GetTensorInfo(),
+ m_Mean->Map(true));
+ std::unique_ptr<Decoder<float>> varianceDecoder = MakeDecoder<float>(m_Variance->GetTensorInfo(),
+ m_Variance->Map(true));
+ std::unique_ptr<Decoder<float>> gammaDecoder = MakeDecoder<float>(m_Gamma->GetTensorInfo(),
+ m_Gamma->Map(true));
+ std::unique_ptr<Decoder<float>> betaDecoder = MakeDecoder<float>(m_Beta->GetTensorInfo(),
+ m_Beta->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
+} // namespace armnn