IVGCVSW-1898 : Ref backend folder structure

* Reference backend is renamed to backends/reference as per
  https://confluence.arm.com/display/MLENG/Pluggable+backends

Change-Id: I27a13c274eb60995dfb459e3c49c0e2f60bcd32c

1 files changed, 0 insertions, 61 deletions

diff --git a/src/backends/RefWorkloads/RefL2NormalizationFloat32Workload.cpp b/src/backends/RefWorkloads/RefL2NormalizationFloat32Workload.cpp
deleted file mode 100644
index 973c87b009..0000000000
--- a/src/backends/RefWorkloads/RefL2NormalizationFloat32Workload.cpp
+++ /dev/null
@@ -1,61 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-
-#include "RefL2NormalizationFloat32Workload.hpp"
-
-#include "RefWorkloadUtils.hpp"
-#include "TensorBufferArrayView.hpp"
-
-#include "Profiling.hpp"
-
-#include <cmath>
-
-namespace armnn
-{
-
-void RefL2NormalizationFloat32Workload::Execute() const
-{
-    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefL2NormalizationFloat32Workload_Execute");
-
-    const TensorInfo& inputInfo = GetTensorInfo(m_Data.m_Inputs[0]);
-    const TensorInfo& outputInfo = GetTensorInfo(m_Data.m_Outputs[0]);
-
-    TensorBufferArrayView<const float> input(inputInfo.GetShape(), GetInputTensorDataFloat(0, m_Data));
-    TensorBufferArrayView<float> output(outputInfo.GetShape(), GetOutputTensorDataFloat(0, m_Data));
-
-    const unsigned int batchSize = inputInfo.GetShape()[0];
-    const unsigned int depth = inputInfo.GetShape()[1];
-    const unsigned int rows = inputInfo.GetShape()[2];
-    const unsigned int cols = inputInfo.GetShape()[3];
-
-    for (unsigned int n = 0; n < batchSize; ++n)
-    {
-        for (unsigned int d = 0; d < depth; ++d)
-        {
-            for (unsigned int h = 0; h < rows; ++h)
-            {
-                for (unsigned int w = 0; w < cols; ++w)
-                {
-                    float reduction = 0.0;
-                    for (unsigned int c = 0; c < depth; ++c)
-                    {
-                        const float value = input.Get(n, c, h, w);
-                        reduction += value * value;
-                    }
-
-                    // Using std::max(reduction, epsilon) below would prevent against division by 0.
-                    // However, at the time of writing:
-                    // - This is not supported by the ACL functions used to implement L2Normalization in the CL
-                    //   backend.
-                    // - The reference semantics for this operator do not include this parameter.
-                    const float scale = 1.0f / sqrtf(reduction);
-                    output.Get(n, d, h, w) = input.Get(n, d, h, w) * scale;
-                }
-            }
-        }
-    }
-}
-
-} //namespace armnn