IVGCVSW-1951 Remove type templating from NeonConvolution2dWorkload

Change-Id: Id3d8137d60b14e93863ad5b6db752a7f6ef9b7fb

1 files changed, 0 insertions, 127 deletions

diff --git a/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp
deleted file mode 100644
index b11d10fd2f..0000000000
--- a/src/backends/neon/workloads/NeonConvolution2dBaseWorkload.cpp
+++ /dev/null
@@ -1,127 +0,0 @@
-//
-// 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 <armnnUtils/Half.hpp>
-
-namespace armnn
-{
-
-using namespace armcomputetensorutils;
-
-arm_compute::Status NeonConvolution2dWorkloadValidate(const TensorInfo& input,
-    const TensorInfo& output,
-    const Convolution2dDescriptor& 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;
-    }
-
-    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();
-
-    arm_compute::DataLayout aclDataLayout = ConvertDataLayout(m_Data.m_Parameters.m_DataLayout);
-    input.info()->set_data_layout(aclDataLayout);
-    output.info()->set_data_layout(aclDataLayout);
-
-    m_KernelTensor = std::make_unique<arm_compute::Tensor>();
-    BuildArmComputeTensor(*m_KernelTensor, m_Data.m_Weight->GetTensorInfo(), 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);
-
-    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);
-
-    InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight);
-
-}
-
-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