diff options
| -rw-r--r-- | src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp | 30 |
1 files changed, 26 insertions, 4 deletions
diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp index 1b4887e0e0..d294705eaa 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp @@ -8,6 +8,7 @@ #include <aclCommon/ArmComputeTensorUtils.hpp> #include <neon/NeonLayerSupport.hpp> #include <backendsCommon/CpuTensorHandle.hpp> +#include <backendsCommon/DataLayoutIndexed.hpp> namespace armnn { @@ -60,11 +61,26 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( m_KernelTensor = std::make_unique<arm_compute::Tensor>(); BuildArmComputeTensor(*m_KernelTensor, weightInfo, m_Data.m_Parameters.m_DataLayout); + INeonTensorHandle* inputTensorHandle = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0]); + INeonTensorHandle* outputTensorHandle = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0]); + DataLayoutIndexed dataLayoutIndex(m_Data.m_Parameters.m_DataLayout); + if (m_Data.m_Parameters.m_BiasEnabled) { m_BiasTensor = std::make_unique<arm_compute::Tensor>(); BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } + else + { + // Workaround for COMPMID-1813 + m_BiasTensor = std::make_unique<arm_compute::Tensor>(); + TensorInfo biasTensorInfo({weightInfo.GetShape()[dataLayoutIndex.GetChannelsIndex()]}, + weightInfo.GetDataType() == DataType::QuantisedAsymm8 ? DataType::Signed32 : + weightInfo.GetDataType(), + weightInfo.GetQuantizationScale() * + info.m_InputTensorInfos[0].GetQuantizationScale()); + BuildArmComputeTensor(*m_BiasTensor, biasTensorInfo, m_Data.m_Parameters.m_DataLayout); + } arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, m_Data.m_Parameters.m_StrideY, @@ -76,14 +92,16 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( m_Data.ValidateInputsOutputs("NeonDepthwiseConvolutionWorkload", 1, 1); - arm_compute::ITensor& input = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); - arm_compute::ITensor& output = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + arm_compute::ITensor& input = inputTensorHandle->GetTensor(); + arm_compute::ITensor& output = outputTensorHandle->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); input.info()->set_data_layout(aclDataLayout); output.info()->set_data_layout(aclDataLayout); - bool use3x3Optimisation = weightInfo.GetShape()[3] == 3 && weightInfo.GetShape()[2] == 3; + bool use3x3Optimisation = weightInfo.GetShape()[dataLayoutIndex.GetWidthIndex()] == 3 && + weightInfo.GetShape()[dataLayoutIndex.GetHeightIndex()] == 3; + if (use3x3Optimisation) { m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer3x3>(); @@ -109,10 +127,14 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight); - if (m_BiasTensor) + if (m_Data.m_Parameters.m_BiasEnabled) { InitializeArmComputeTensorData(*m_BiasTensor, m_Data.m_Bias); } + else + { + InitialiseArmComputeTensorEmpty(*m_BiasTensor); + } m_pDepthwiseConvolutionLayer->prepare(); FreeUnusedTensors(); |