IVGCVSW-1812 Adding Ref implementation and tests of MeanWorkloads
Change-Id: I6fb15c407024e3b91d5abf4513f8090be5821760
diff --git a/src/backends/reference/workloads/Mean.cpp b/src/backends/reference/workloads/Mean.cpp
new file mode 100644
index 0000000..0db67a0
--- /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