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, 61 insertions, 0 deletions

diff --git a/src/backends/reference/workloads/RefL2NormalizationFloat32Workload.cpp b/src/backends/reference/workloads/RefL2NormalizationFloat32Workload.cpp
new file mode 100644
index 0000000000..973c87b009
--- /dev/null
+++ b/src/backends/reference/workloads/RefL2NormalizationFloat32Workload.cpp
@@ -0,0 +1,61 @@
+//
+// 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