{
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