IVGCVSW-1951 Remove type templating from NeonDepthwiseConvolutionWorkload
Change-Id: I411d02949524eb802672d83ee281300c34b007c8
diff --git a/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp
new file mode 100644
index 0000000..8b1feaa
--- /dev/null
+++ b/src/backends/neon/workloads/NeonDepthwiseConvolutionWorkload.cpp
@@ -0,0 +1,135 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonDepthwiseConvolutionWorkload.hpp"
+
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/neon/NeonLayerSupport.hpp>
+#include <backends/CpuTensorHandle.hpp>
+
+namespace armnn
+{
+
+using namespace armcomputetensorutils;
+
+arm_compute::Status NeonDepthwiseConvolutionWorkloadValidate(const TensorInfo& input,
+ const TensorInfo& output,
+ const DepthwiseConvolution2dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const Optional<TensorInfo>& biases)
+{
+ const arm_compute::TensorInfo aclInputInfo =
+ BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
+ const arm_compute::TensorInfo aclOutputInfo =
+ BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
+ const arm_compute::TensorInfo aclWeightsInfo =
+ BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
+
+ arm_compute::TensorInfo aclBiasesInfo;
+ arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
+
+ if (descriptor.m_BiasEnabled)
+ {
+ BOOST_ASSERT(biases.has_value());
+
+ aclBiasesInfo = BuildArmComputeTensorInfo(biases.value(), descriptor.m_DataLayout);
+ optionalAclBiasesInfo = &aclBiasesInfo;
+ }
+
+ const arm_compute::PadStrideInfo aclPadStrideInfo =
+ BuildArmComputePadStrideInfo(descriptor);
+ const unsigned int aclDepthMultiplier = weights.GetShape()[0];
+
+ return arm_compute::NEDepthwiseConvolutionLayer::validate(&aclInputInfo,
+ &aclWeightsInfo,
+ optionalAclBiasesInfo,
+ &aclOutputInfo,
+ aclPadStrideInfo,
+ aclDepthMultiplier);
+}
+
+NeonDepthwiseConvolutionWorkload::NeonDepthwiseConvolutionWorkload(
+ const DepthwiseConvolution2dQueueDescriptor& descriptor,
+ const WorkloadInfo& info)
+ : BaseWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info)
+{
+ const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+ m_KernelTensor = std::make_unique<arm_compute::Tensor>();
+ 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(), m_Data.m_Parameters.m_DataLayout);
+ }
+
+ arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
+ m_Data.m_Parameters.m_StrideY,
+ m_Data.m_Parameters.m_PadLeft,
+ m_Data.m_Parameters.m_PadRight,
+ m_Data.m_Parameters.m_PadTop,
+ m_Data.m_Parameters.m_PadBottom,
+ arm_compute::DimensionRoundingType::FLOOR);
+
+ 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::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)
+ {
+ m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer3x3>();
+ static_cast<arm_compute::NEDepthwiseConvolutionLayer3x3*>(
+ m_pDepthwiseConvolutionLayer.get())->configure(&input,
+ m_KernelTensor.get(),
+ m_BiasTensor.get(),
+ &output,
+ padStrideInfo);
+ }
+ else
+ {
+ m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer>();
+ static_cast<arm_compute::NEDepthwiseConvolutionLayer*>(
+ m_pDepthwiseConvolutionLayer.get())->configure(&input,
+ m_KernelTensor.get(),
+ m_BiasTensor.get(),
+ &output,
+ padStrideInfo);
+ }
+
+ BOOST_ASSERT(m_pDepthwiseConvolutionLayer);
+
+ InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight);
+
+ if (m_BiasTensor)
+ {
+ InitializeArmComputeTensorData(*m_BiasTensor, m_Data.m_Bias);
+ }
+
+ m_pDepthwiseConvolutionLayer->prepare();
+ FreeUnusedTensors();
+}
+
+void NeonDepthwiseConvolutionWorkload::Execute() const
+{
+ ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthwiseConvolutionWorkload_Execute");
+ BOOST_ASSERT(m_pDepthwiseConvolutionLayer);
+
+ m_pDepthwiseConvolutionLayer->run();
+}
+
+void NeonDepthwiseConvolutionWorkload::FreeUnusedTensors()
+{
+ FreeTensorIfUnused(m_KernelTensor);
+ FreeTensorIfUnused(m_BiasTensor);
+}
+
+} //namespace armnn