Revert "MLCE-418 Reduce layer does not support multiple axes"

This reverts commit d905decd256558bbee165e636ce4242ac3b9c917.

Reason for revert: LargeGraph_TENSOR_FLOAT32/FLOAT16 CTS tests failures

Change-Id: Ie69826549e73775825f45134375b5b2c41aebd01

2 files changed, 0 insertions, 140 deletions

diff --git a/src/backends/aclCommon/ArmComputeSubgraphUtils.hpp b/src/backends/aclCommon/ArmComputeSubgraphUtils.hpp
index 9439ddb61e..a0fca46330 100644
--- a/src/backends/aclCommon/ArmComputeSubgraphUtils.hpp
+++ b/src/backends/aclCommon/ArmComputeSubgraphUtils.hpp
@@ -6,9 +6,6 @@
 #pragma once
 
 #include <armnn/backends/OptimizationViews.hpp>
-#include <armnn/utility/Assert.hpp>
-
-#include <aclCommon/ArmComputeUtils.hpp>
 
 namespace armnn
 {
@@ -150,86 +147,4 @@ LayerType* FuseLayerWithWeightsAndBiases(OptimizationViews& optimizationViews,
     return replacementLayer;
 }
 
-//
-// If reduce layer has multiple axes, add new layer for each axis to simulate the same behaviour
-// as currently only one axis is supported.
-//
-template<typename LayerType>
-void ChainReduceLayers(OptimizationViews& optimizationViews,
-                       LayerType* baseLayer,
-                       ReduceDescriptor& reduceDescriptor)
-{
-    // If layer has single axis don't chain layers.
-    if (!reduceDescriptor.m_vAxis.empty() && reduceDescriptor.m_vAxis.size() > 1)
-    {
-        // Save base layer output shape to compare against the output of the final layer added.
-        const TensorInfo baseLayerInfo = baseLayer->GetOutputSlot(0).GetTensorInfo();
-
-        // Vector of new chained layers, used for substitution.
-        std::vector<Layer*> layers;
-
-        // Vector of axes so each layer is reshaped correctly.
-        std::vector<uint32_t> reduceAxis;
-        unsigned int recalulateAxis = 0;
-
-        for (unsigned int i = 0; i != reduceDescriptor.m_vAxis.size(); ++i)
-        {
-            // Get TensorInfo to populate subsequent layers with.
-            TensorInfo layerInfoToModify = baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo();
-
-            reduceAxis.emplace_back(reduceDescriptor.m_vAxis[i]);
-
-            // Calculate new shape based on the axes.
-            const TensorShape& reducedShape = ComputeReductionTensorShape(layerInfoToModify,
-                                                                          reduceAxis,
-                                                                          reduceDescriptor.m_KeepDims);
-            layerInfoToModify.SetShape(reducedShape);
-
-            // Create a vector for the single axis to be assigned to the descriptor.
-            // Update axis if keepDims is set reduce layers correctly.
-            std::vector<uint32_t> singleAxis(1, reduceDescriptor.m_vAxis[i] - recalulateAxis);
-
-            // Create a descriptor and assign single axis.
-            ReduceDescriptor newReduceDescriptor = baseLayer->GetParameters();
-            newReduceDescriptor.m_vAxis.assign(singleAxis.begin(), singleAxis.end());
-
-            // Add new layer to graph.
-            std::string layerName = "reduce_layer_" + std::to_string(i);
-            Layer* replacementLayer = optimizationViews.GetGraph().AddLayer<LayerType>(newReduceDescriptor,
-                                                                                       layerName.c_str());
-
-            // Connect previous layer with new layer.
-            // The first and last layer will be connected when the subgraph is replaced.
-            if (!layers.empty())
-            {
-                layers[i - 1]->GetOutputSlot(0).Connect(replacementLayer->GetInputSlot(0));
-            }
-
-            // Set updated tensorInfo for new layer.
-            replacementLayer->GetOutputSlot(0).SetTensorInfo(layerInfoToModify);
-
-            if (!reduceDescriptor.m_KeepDims)
-            {
-                recalulateAxis++;
-            }
-
-            layers.emplace_back(replacementLayer);
-        }
-
-        // Check if the TensorInfo from the last layer equals the inferred output from the original layer.
-        ARMNN_ASSERT(baseLayerInfo == layers.back()->GetOutputSlot().GetTensorInfo());
-
-        std::list<Layer*> replacementLayers(layers.begin(), layers.end());
-
-        // Substitute new chained subgraph for original reduce layer.
-        SubgraphView substitutionSubgraph(baseLayer);
-        SubgraphView replacementSubgraph(CreateInputsFrom({replacementLayers.front()}),
-                                         CreateOutputsFrom({replacementLayers.back()}),
-                                         std::move(replacementLayers));
-
-        optimizationViews.AddSubstitution({substitutionSubgraph, replacementSubgraph});
-
-    }
-}
-
 } // namespace armnn
diff --git a/src/backends/aclCommon/ArmComputeUtils.hpp b/src/backends/aclCommon/ArmComputeUtils.hpp
index 5bc5abcb05..d9efab288f 100644
--- a/src/backends/aclCommon/ArmComputeUtils.hpp
+++ b/src/backends/aclCommon/ArmComputeUtils.hpp
@@ -7,7 +7,6 @@
 #include <armnn/Descriptors.hpp>
 #include <armnn/Tensor.hpp>
 #include <armnn/utility/Assert.hpp>
-#include <armnn/utility/NumericCast.hpp>
 #include <backendsCommon/WorkloadData.hpp>
 
 #include <arm_compute/core/Types.h>
@@ -268,58 +267,4 @@ inline arm_compute::ReductionOperation ConvertReductionOperationToAcl(const Redu
     }
 }
 
-/// Function to compute the output tensor shape based on the axes and if keepDims is set.
-inline const TensorShape ComputeReductionTensorShape(const armnn::TensorInfo& input,
-                                                     const std::vector<uint32_t>& vAxis,
-                                                     const bool keepDims)
-{
-    unsigned int rank = input.GetNumDimensions();
-    unsigned int outputRank = 0;
-
-    // Calculate output dimension
-    if (keepDims)
-    {
-        outputRank = rank;
-    }
-    else if (vAxis.empty())
-    {
-        outputRank = 1;
-    }
-    else if (vAxis.size() > input.GetNumDimensions())
-    {
-        throw LayerValidationException("ReduceLayer: Dimensions to reduce can not be bigger than input dimensions");
-    }
-    else
-    {
-        outputRank = input.GetNumDimensions() - armnn::numeric_cast<unsigned int>(vAxis.size());
-        if (outputRank == 0)
-        {
-            outputRank = 1;
-        }
-    }
-
-    std::vector<unsigned int> dimSizes(outputRank, 1);
-    if (!vAxis.empty())
-    {
-        // Skip the dimension that has been reduced unless keepDims is true.
-        unsigned int outputIndex = 0;
-        for (unsigned int i = 0; i < input.GetNumDimensions(); ++i)
-        {
-            if (std::find(vAxis.begin(), vAxis.end(), i) == vAxis.end())
-            {
-                dimSizes[outputIndex] = armnn::numeric_cast<unsigned int>(input.GetShape()[i]);
-                ++outputIndex;
-            }
-            else if (keepDims)
-            {
-                dimSizes[outputIndex] = 1;
-                ++outputIndex;
-            }
-        }
-    }
-
-    const TensorShape inferredShape = TensorShape(outputRank, dimSizes.data());
-    return inferredShape;
-}
-
 } // namespace armnn