From 1e4c31dafb1c8984a126fa1d211ed8f9eedaf7cc Mon Sep 17 00:00:00 2001
From: narpra01 <narumol.prangnawarat@arm.com>
Date: Fri, 28 Sep 2018 11:07:51 +0100
Subject: IVGCVSW-1812 Adding Ref implementation and tests of MeanWorkloads

Change-Id: I6fb15c407024e3b91d5abf4513f8090be5821760
---
 src/backends/reference/workloads/Mean.cpp | 136 ++++++++++++++++++++++++++++++
 1 file changed, 136 insertions(+)
 create mode 100644 src/backends/reference/workloads/Mean.cpp

(limited to 'src/backends/reference/workloads/Mean.cpp')

diff --git a/src/backends/reference/workloads/Mean.cpp b/src/backends/reference/workloads/Mean.cpp
new file mode 100644
index 0000000000..0db67a0eed
--- /dev/null
+++ b/src/backends/reference/workloads/Mean.cpp
@@ -0,0 +1,136 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "Mean.hpp"
+#include "backends/WorkloadData.hpp"
+
+#include <boost/numeric/conversion/cast.hpp>
+
+#include <cmath>
+#include <cstddef>
+#include <functional>
+#include <limits>
+
+namespace armnn
+{
+bool NextIndex(const unsigned int numDims, const armnn::TensorShape& dims, std::vector<unsigned int>& current)
+{
+    unsigned int carry = 1;
+
+    for (unsigned int idx = numDims; idx-- > 0; )
+    {
+        unsigned int current_val = current[idx] + carry;
+        if (dims[idx] == current_val)
+        {
+            current[idx] = 0;
+        }
+        else
+        {
+            current[idx] = current_val;
+            carry = 0;
+            break;
+        }
+    }
+    return (carry == 0);
+}
+
+std::size_t ReducedOutputOffset(const unsigned int numDims, const armnn::TensorShape& dims,
+                                std::vector<unsigned int>& index, const unsigned int numAxis,
+                                const std::vector<unsigned int>& axis) {
+    std::size_t offset = 0;
+    for (unsigned int idx = 0; idx < numDims; ++idx)
+    {
+        bool isAxis = false;
+        if (!axis.empty())
+        {
+            for (unsigned int axisIdx = 0; axisIdx < numAxis; ++axisIdx)
+            {
+                if (idx == axis[axisIdx])
+                {
+                    isAxis = true;
+                    break;
+                }
+            }
+        }
+        if (!isAxis)
+        {
+            offset = offset * boost::numeric_cast<size_t>(dims[idx]) + boost::numeric_cast<size_t>(index[idx]);
+        }
+    }
+    return offset;
+}
+} // namespace
+
+namespace armnn
+{
+void Mean(const armnn::TensorInfo& inputInfo,
+          const armnn::TensorInfo& outputInfo,
+          const std::vector<unsigned int>& axis,
+          const float* inputData,
+          float* outputData) {
+
+    unsigned int inputNumDims = inputInfo.GetNumDimensions();
+    unsigned int outputNumDims = outputInfo.GetNumDimensions();
+
+    armnn::TensorShape outputDims = outputInfo.GetShape();
+    armnn::TensorShape inputDims = inputInfo.GetShape();
+
+    // Initialise output data.
+    size_t numOutputs = 1;
+    for (unsigned int idx = 0; idx < outputNumDims; ++idx)
+    {
+        numOutputs *= boost::numeric_cast<size_t>(outputDims[idx]);
+    }
+
+    std::vector<float> tempSum(numOutputs);
+    for (size_t idx = 0; idx < numOutputs; ++idx)
+    {
+        outputData[idx] = 0.0f;
+        tempSum[idx] = 0.0f;
+    }
+
+    // Initialise temp index.
+    std::vector<unsigned int> tempIndex(inputNumDims);
+    for (unsigned int idx = 0; idx < inputNumDims; ++idx)
+    {
+        tempIndex[idx] = 0;
+    }
+
+    std::vector<unsigned int> resolvedAxis = axis;
+    if (resolvedAxis.empty())
+    {
+      for (unsigned int idx = 0; idx < inputNumDims; ++idx)
+      {
+          resolvedAxis.push_back(idx);
+      }
+    }
+    unsigned int numResolvedAxis = boost::numeric_cast<unsigned int>(resolvedAxis.size());
+
+    // Iterates through input_data and sum up the reduced axis.
+    for (bool hasNext = true; hasNext; hasNext = NextIndex(inputNumDims, inputDims, tempIndex))
+    {
+        size_t inputOffset = ReducedOutputOffset(inputNumDims, inputDims, tempIndex, 0, {});
+        size_t outputOffset = ReducedOutputOffset(inputNumDims, inputDims, tempIndex,
+                                                  numResolvedAxis, resolvedAxis);
+        tempSum[outputOffset] += inputData[inputOffset];
+    }
+
+    // Takes average by num of elements added to get mean.
+    size_t numElementsInAxis = 1;
+    for (unsigned int idx = 0; idx < numResolvedAxis; ++idx)
+    {
+        size_t current = boost::numeric_cast<size_t>(inputDims[resolvedAxis[idx]]);
+        BOOST_ASSERT(boost::numeric_cast<float>(current) <
+              (std::numeric_limits<float>::max() / boost::numeric_cast<float>(numElementsInAxis)));
+        numElementsInAxis *= current;
+    }
+    if (numElementsInAxis > 0) {
+        for (size_t idx = 0; idx < numOutputs; ++idx)
+        {
+            outputData[idx] = tempSum[idx] / boost::numeric_cast<float>(numElementsInAxis);
+        }
+    }
+}
+} //namespace armnn
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