IVGCVSW-1897 : build infrastructure for the src/backends folder

Change-Id: I7ebafb675ccc77ad54d1deb01412a8379a5356bb

1 files changed, 0 insertions, 70 deletions

diff --git a/src/armnn/backends/NeonWorkloads/NeonNormalizationFloatWorkload.cpp b/src/armnn/backends/NeonWorkloads/NeonNormalizationFloatWorkload.cpp
deleted file mode 100644
index 4534c376d8..0000000000
--- a/src/armnn/backends/NeonWorkloads/NeonNormalizationFloatWorkload.cpp
+++ /dev/null
@@ -1,70 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "NeonNormalizationFloatWorkload.hpp"
-#include "backends/NeonLayerSupport.hpp"
-#include "backends/ArmComputeUtils.hpp"
-#include "backends/ArmComputeTensorUtils.hpp"
-
-namespace armnn
-{
-
-arm_compute::Status NeonNormalizationWorkloadValidate(const TensorInfo& input,
-                                                      const TensorInfo& output,
-                                                      const NormalizationDescriptor& descriptor)
-{
-    const arm_compute::TensorInfo aclInput = armcomputetensorutils::BuildArmComputeTensorInfo(input);
-    const arm_compute::TensorInfo aclOutput = armcomputetensorutils::BuildArmComputeTensorInfo(output);
-
-    arm_compute::NormalizationLayerInfo normalizationInfo =
-            armcomputetensorutils::BuildArmComputeNormalizationLayerInfo(descriptor);
-
-    return arm_compute::NENormalizationLayer::validate(&aclInput, &aclOutput, normalizationInfo);
-}
-
-NeonNormalizationFloatWorkload::NeonNormalizationFloatWorkload(const NormalizationQueueDescriptor& descriptor,
-                                                   const WorkloadInfo& info,
-                                                   std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
-    : FloatWorkload<NormalizationQueueDescriptor>(descriptor, info)
-    , m_NormalizationLayer(memoryManager)
-{
-    m_Data.ValidateInputsOutputs("NeonNormalizationFloatWorkload", 1, 1);
-    std::string reasonIfUnsupported;
-    if (!IsNeonNormalizationDescParamsSupported(&reasonIfUnsupported, m_Data.m_Parameters))
-    {
-        throw UnimplementedException(reasonIfUnsupported);
-    }
-
-    // Input and output tensors have to have the same dimensionality.
-    if (info.m_InputTensorInfos[0].GetShape()[1] != info.m_OutputTensorInfos[0].GetShape()[1]
-        || info.m_InputTensorInfos[0].GetShape()[0] != info.m_OutputTensorInfos[0].GetShape()[0]
-        || info.m_InputTensorInfos[0].GetShape()[3] != info.m_OutputTensorInfos[0].GetShape()[3]
-        || info.m_InputTensorInfos[0].GetShape()[2] != info.m_OutputTensorInfos[0].GetShape()[2])
-    {
-        throw InvalidArgumentException("Normalization requires input and output tensors to have equal dimensionality.");
-    }
-
-    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();
-
-    const arm_compute::NormType normType =
-        ConvertNormalizationAlgorithmChannelToAclNormType(m_Data.m_Parameters.m_NormChannelType);
-    arm_compute::NormalizationLayerInfo normalizationInfo(normType,
-                                                          m_Data.m_Parameters.m_NormSize,
-                                                          m_Data.m_Parameters.m_Alpha,
-                                                          m_Data.m_Parameters.m_Beta,
-                                                          m_Data.m_Parameters.m_K,
-                                                          false);
-
-    m_NormalizationLayer.configure(&input, &output, normalizationInfo);
-}
-
-void NeonNormalizationFloatWorkload::Execute() const
-{
-    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonNormalizationFloatWorkload_Execute");
-    m_NormalizationLayer.run();
-}
-
-} //namespace armnn