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| author | Nikhil Raj <nikhil.raj@arm.com> | 2018-10-12 13:51:57 +0100 |
|---|---|---|
| committer | Matthew Bentham <matthew.bentham@arm.com> | 2018-10-22 16:57:53 +0100 |
| commit | cec6b655d9f6ddb73c721ca47a7d67eeaad5c043 (patch) | |
| tree | 898dbc90785f77f9c724bb8de61d7fb1b1ce3c0b /src/backends/neon/workloads | |
| parent | f3eb46d23c6001150d36d80acac7ad1247174630 (diff) | |
| download | armnn-cec6b655d9f6ddb73c721ca47a7d67eeaad5c043.tar.gz | |
IVGCVSW-1922 Unit test for DepthwiseConvolution with NHWC
Change-Id: I3e6e5b9a62f30d03c05bd7178adea8f4c8275da8
Diffstat (limited to 'src/backends/neon/workloads')
| -rw-r--r-- | src/backends/neon/workloads/NeonDepthwiseConvolutionFloatWorkload.cpp | 8 | ||||
| -rw-r--r-- | src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp | 8 |
2 files changed, 12 insertions, 4 deletions
diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionFloatWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionFloatWorkload.cpp index 742a768b94..4b266f3288 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionFloatWorkload.cpp @@ -20,12 +20,12 @@ NeonDepthwiseConvolutionFloatWorkload::NeonDepthwiseConvolutionFloatWorkload( const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); m_KernelTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_KernelTensor, weightInfo, descriptor.m_DataLayout); + BuildArmComputeTensor(*m_KernelTensor, weightInfo, 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(), descriptor.m_DataLayout); + BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, @@ -41,6 +41,10 @@ NeonDepthwiseConvolutionFloatWorkload::NeonDepthwiseConvolutionFloatWorkload( 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::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; if (use3x3Optimisation) { diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp index 722b778eba..6c6c2dfb6c 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionUint8Workload.cpp @@ -20,12 +20,12 @@ NeonDepthwiseConvolutionUint8Workload::NeonDepthwiseConvolutionUint8Workload( const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo(); m_KernelTensor = std::make_unique<arm_compute::Tensor>(); - BuildArmComputeTensor(*m_KernelTensor, weightInfo, descriptor.m_DataLayout); + BuildArmComputeTensor(*m_KernelTensor, weightInfo, 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(), descriptor.m_DataLayout); + BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo(), m_Data.m_Parameters.m_DataLayout); } arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX, @@ -41,6 +41,10 @@ NeonDepthwiseConvolutionUint8Workload::NeonDepthwiseConvolutionUint8Workload( 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::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; if (use3x3Optimisation) { |