IVGCVSW-1899 : Neon backend folder structure
armnn:149855
Change-Id: I26e8cf83422a65049386a5ebdb6d0001627aefaa
diff --git a/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp
new file mode 100644
index 0000000..547f563
--- /dev/null
+++ b/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp
@@ -0,0 +1,146 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <backends/CpuTensorHandle.hpp>
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/neon/NeonLayerSupport.hpp>
+
+#include "NeonConvolution2dBaseWorkload.hpp"
+
+#include <armnn/Types.hpp>
+#include <Half.hpp>
+
+namespace armnn
+{
+
+using namespace armcomputetensorutils;
+
+arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo& input,
+ const TensorInfo& output,
+ const Convolution2dDescriptor& descriptor,
+ const TensorInfo& weights,
+ const boost::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.is_initialized());
+
+ aclBiasesInfo = BuildArmComputeTensorInfo(biases.get(), descriptor.m_DataLayout);
+ optionalAclBiasesInfo = &aclBiasesInfo;
+ }
+
+ arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
+
+ return arm_compute::NEConvolutionLayer::validate(&aclInputInfo,
+ &aclWeightsInfo,
+ optionalAclBiasesInfo,
+ &aclOutputInfo,
+ layerInfo);
+}
+
+template<armnn::DataType... dataTypes>
+NeonConvolution2dBaseWorkload<dataTypes...>::NeonConvolution2dBaseWorkload(
+ const Convolution2dQueueDescriptor& descriptor, const WorkloadInfo& info,
+ std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
+ : TypedWorkload<Convolution2dQueueDescriptor, dataTypes...>(descriptor, info)
+{
+ using arm_compute::NEDirectConvolutionLayer;
+
+ ValidateData();
+
+ // todo: check tensor shapes match.
+
+ arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+ arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+ m_KernelTensor = std::make_unique<arm_compute::Tensor>();
+ BuildArmComputeTensor(*m_KernelTensor, m_Data.m_Weight->GetTensorInfo(), descriptor.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);
+ }
+
+ 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);
+
+ const bool preferDirectConvolution =
+ IsNeonDirectConvolutionPreferred(m_Data.m_Weight->GetTensorInfo(),
+ m_Data.m_Parameters);
+
+ if (preferDirectConvolution)
+ {
+ auto directConvolutionLayer = std::make_unique<arm_compute::NEDirectConvolutionLayer>(memoryManager);
+ directConvolutionLayer->configure(&input,
+ m_KernelTensor.get(),
+ m_BiasTensor.get(),
+ &output,
+ padStrideInfo);
+ m_ConvolutionLayer.reset(directConvolutionLayer.release());
+ }
+ else
+ {
+ auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
+ convolutionLayer->configure(&input,
+ m_KernelTensor.get(),
+ m_BiasTensor.get(),
+ &output,
+ padStrideInfo);
+ m_ConvolutionLayer.reset(convolutionLayer.release());
+ }
+ BOOST_ASSERT(m_ConvolutionLayer);
+
+ armnn::DataType dataType = m_Data.m_Weight->GetTensorInfo().GetDataType();
+
+ switch (dataType)
+ {
+ case DataType::Float16:
+ {
+ InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<Half>());
+ break;
+ }
+ case DataType::Float32:
+ {
+ InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<float>());
+ break;
+ }
+ case DataType::QuantisedAsymm8:
+ {
+ InitialiseArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight->template GetConstTensor<uint8_t>());
+ break;
+ }
+ default:
+ {
+ BOOST_ASSERT_MSG(false, "Unknown DataType.");
+ }
+ }
+}
+
+template<armnn::DataType... dataTypes>
+void NeonConvolution2dBaseWorkload<dataTypes...>::FreeUnusedTensors()
+{
+ FreeTensorIfUnused(m_KernelTensor);
+ FreeTensorIfUnused(m_BiasTensor);
+}
+
+// Generates known implementations for linker.
+template class NeonConvolution2dBaseWorkload<armnn::DataType::Float16, armnn::DataType::Float32>;
+template class NeonConvolution2dBaseWorkload<armnn::DataType::QuantisedAsymm8>;
+
+} //namespace armnn
+