diff options
Diffstat (limited to 'src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp')
| -rw-r--r-- | src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp | 41 |
1 files changed, 29 insertions, 12 deletions
diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp index 589a951825..138c237aba 100644 --- a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp +++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp @@ -33,20 +33,20 @@ arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo& i const Optional<TensorInfo>& biases, const ActivationDescriptor* activationDescriptor) { - const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); + const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout); const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout); // ArmNN's weight format is usually [ M, I, H, W ] but for depthwise its [ 1, H, W, I*M] // Permute to [ 1, I * M, H, W ] (if NCHW), as required by the compute library unsigned int aclDepthMultiplier; TensorInfo weightsPermuted; - std::tie(weightsPermuted, aclDepthMultiplier) = Convert1HWOTensorInfoToAcl(weights, input,descriptor.m_DataLayout); + std::tie(weightsPermuted, aclDepthMultiplier) = Convert1HWOTensorInfoToAcl(weights, input, descriptor.m_DataLayout); // Convert the weights into the compute library format const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weightsPermuted, descriptor.m_DataLayout); arm_compute::TensorInfo aclBiasesInfo; - arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr; + arm_compute::TensorInfo* optionalAclBiasesInfo = nullptr; if (descriptor.m_BiasEnabled) { @@ -58,10 +58,10 @@ arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo& i arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor); const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D( - descriptor.m_DilationX,descriptor.m_DilationY); + descriptor.m_DilationX, descriptor.m_DilationY); const arm_compute::ActivationLayerInfo activationInfo = ConvertActivationDescriptorToAclActivationLayerInfo( - activationDescriptor); + activationDescriptor); return arm_compute::NEDepthwiseConvolutionLayer::validate(&aclInputInfo, &aclWeightsInfo, @@ -85,9 +85,9 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( unsigned int depthMultiplier; std::unique_ptr<unsigned char[]> permuteBuffer(new unsigned char[weightInfo.GetNumBytes()]); std::tie(weightsPermuted, depthMultiplier) = Convert1HWOTensorToAcl(m_Data.m_Weight, - info.m_InputTensorInfos[0], - m_Data.m_Parameters.m_DataLayout, - permuteBuffer.get()); + info.m_InputTensorInfos[0], + m_Data.m_Parameters.m_DataLayout, + permuteBuffer.get()); // Convert the weights into the compute library format m_KernelTensor = std::make_unique<arm_compute::Tensor>(); @@ -100,14 +100,14 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( } const arm_compute::Size2D aclDilationInfo = BuildArmComputeSize2D( - m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY); + m_Data.m_Parameters.m_DilationX, m_Data.m_Parameters.m_DilationY); m_Data.ValidateInputsOutputs("NeonDepthwiseConvolutionWorkload", 1, 1); - IAclTensorHandle* inputTensorHandle = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0]); + IAclTensorHandle* inputTensorHandle = static_cast<IAclTensorHandle*>(m_Data.m_Inputs[0]); IAclTensorHandle* outputTensorHandle = static_cast<IAclTensorHandle*>(m_Data.m_Outputs[0]); - arm_compute::ITensor& input = inputTensorHandle->GetTensor(); + arm_compute::ITensor& input = inputTensorHandle->GetTensor(); arm_compute::ITensor& output = outputTensorHandle->GetTensor(); arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout); @@ -129,6 +129,23 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( activationInfo, aclDilationInfo); + // Add details for profiling output + WorkloadInfo detailsInfo; + + detailsInfo.m_InputTensorInfos = info.m_InputTensorInfos; + detailsInfo.m_OutputTensorInfos = info.m_OutputTensorInfos; + detailsInfo.m_WeightsTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Weight->GetTensorInfo()); + if (descriptor.m_Parameters.m_BiasEnabled) + { + detailsInfo.m_BiasTensorInfo = armnn::Optional<armnn::TensorInfo>(descriptor.m_Bias->GetTensorInfo()); + } + + // Report Profiling Details + ARMNN_REPORT_PROFILING_WORKLOAD_DESC("NeonDepthwiseConvolution2dWorkload_Construct", + descriptor.m_Parameters, + detailsInfo, + this->GetGuid()); + ARMNN_ASSERT(m_pDepthwiseConvolutionLayer); ScopedTensorHandle weightsPermutedHandle(weightsPermuted); @@ -145,7 +162,7 @@ NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload( void NeonDepthwiseConvolutionWorkload::Execute() const { - ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthwiseConvolutionWorkload_Execute"); + ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID("NeonDepthwiseConvolutionWorkload_Execute", this->GetGuid()); ARMNN_ASSERT(m_pDepthwiseConvolutionLayer); m_pDepthwiseConvolutionLayer->run(); |