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, 12 insertions, 65 deletions

diff --git a/src/backends/neon/NeonBackend.cpp b/src/backends/neon/NeonBackend.cpp
index 6d5eab0ddf..a1299fb458 100644
--- a/src/backends/neon/NeonBackend.cpp
+++ b/src/backends/neon/NeonBackend.cpp
@@ -29,7 +29,6 @@
 #include "workloads/NeonDivisionWorkload.hpp"
 #include "workloads/NeonFullyConnectedWorkload.hpp"
 #include "workloads/NeonMultiplicationWorkload.hpp"
-#include "workloads/NeonReduceWorkload.hpp"
 #include "workloads/NeonSubtractionWorkload.hpp"
 
 #include <Optimizer.hpp>
@@ -165,8 +164,7 @@ OptimizationViews NeonBackend::OptimizeSubgraphView(const SubgraphView& subgraph
         if ((base.GetType() == LayerType::DepthwiseConvolution2d || base.GetType() == LayerType::Convolution2d
              || base.GetType() == LayerType::BatchNormalization || base.GetType() == LayerType::FullyConnected
              || base.GetType() == LayerType::Addition || base.GetType() == LayerType::Multiplication
-             || base.GetType() == LayerType::Subtraction || base.GetType() == LayerType::Division
-             || base.GetType() == LayerType::Reduce)
+             || base.GetType() == LayerType::Subtraction || base.GetType() == LayerType::Division)
             && (base.GetAdditionalInformation<ActivationDescriptor>() == nullptr))
         {
             for (auto output = base.BeginOutputSlots(); output != base.EndOutputSlots(); ++output)
@@ -391,26 +389,6 @@ OptimizationViews NeonBackend::OptimizeSubgraphView(const SubgraphView& subgraph
                                 }
                             }
                         }
-
-                        // Separate check for Reduce as we aren't fusing with activation layer
-                        if (base.GetType() == LayerType::Reduce)
-                        {
-                            ReduceLayer* baseLayer = PolymorphicDowncast<ReduceLayer*>(&base);
-
-                            // Get params from base layer
-                            ReduceDescriptor reduceDescriptor = baseLayer->GetParameters();
-
-                            arm_compute::Status status = NeonReduceWorkloadValidate(
-                                    baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetTensorInfo(),
-                                    baseLayer->GetOutputSlot(0).GetTensorInfo(),
-                                    reduceDescriptor);
-
-                            if (status)
-                            {
-                                ChainReduceLayers<ReduceLayer>(optimizationViews, baseLayer, reduceDescriptor);
-                                untouched.erase(baseLayer->GetGuid());
-                            }
-                        }
                     }
                 }
             }
diff --git a/src/backends/neon/workloads/NeonReduceWorkload.cpp b/src/backends/neon/workloads/NeonReduceWorkload.cpp
index 6125f3609d..0e1b46a3a1 100644
--- a/src/backends/neon/workloads/NeonReduceWorkload.cpp
+++ b/src/backends/neon/workloads/NeonReduceWorkload.cpp
@@ -21,52 +21,22 @@ arm_compute::Status NeonReduceWorkloadValidate(const TensorInfo& input,
                                                const ReduceDescriptor& desc)
 {
     const arm_compute::TensorInfo aclInputInfo  = armcomputetensorutils::BuildArmComputeTensorInfo(input);
+    const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
+    if (!desc.m_vAxis.empty() && desc.m_vAxis.size() > 1)
+    {
+        return arm_compute::Status(arm_compute::ErrorCode::RUNTIME_ERROR,
+                                   "NeonReduceWorkload: Reduction is supported only on 1 axis.");
+    }
 
     arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(aclInputInfo.num_dimensions(),
                                                                           input.GetNumDimensions(),
                                                                           desc.m_vAxis);
 
-    // As ACL only support one axis, validate the layer for each axis if more than one is present.
-    if (!desc.m_vAxis.empty() && desc.m_vAxis.size() > 1)
-    {
-        arm_compute::Status status;
-
-        for (unsigned int i = 0; i != desc.m_vAxis.size(); ++i)
-        {
-            TensorInfo inputToModify = input;
-            std::vector<uint32_t> singleAxis(1, desc.m_vAxis[i]);
-
-            // Calculate the output shape using the input shape for a single axis.
-            // Currently the output TensorInfo inferred will be reduced upon multiple axis
-            // which will fail validation as only one axis is supported.
-            const TensorShape& reducedShape = ComputeReductionTensorShape(inputToModify, singleAxis, desc.m_KeepDims);
-            inputToModify.SetShape(reducedShape);
-
-            const arm_compute::TensorInfo aclOutputInfoModified =
-                    armcomputetensorutils::BuildArmComputeTensorInfo(inputToModify);
-
-            status = arm_compute::NEReductionOperation::validate(&aclInputInfo,
-                                                                 &aclOutputInfoModified,
-                                                                 static_cast<unsigned int>(coords[i]),
-                                                                 ConvertReductionOperationToAcl(desc),
-                                                                 desc.m_KeepDims);
-            if (!status)
-            {
-                break;
-            }
-        }
-        return status;
-    }
-    else
-    {
-        const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
-
-        return arm_compute::NEReductionOperation::validate(&aclInputInfo,
-                                                           &aclOutputInfo,
-                                                           static_cast<unsigned int>(coords[0]),
-                                                           ConvertReductionOperationToAcl(desc),
-                                                           desc.m_KeepDims);
-    }
+    return arm_compute::NEReductionOperation::validate(&aclInputInfo,
+                                                       &aclOutputInfo,
+                                                       static_cast<unsigned int>(coords[0]),
+                                                       ConvertReductionOperationToAcl(desc),
+                                                       desc.m_KeepDims);
 }
 
 NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor, const WorkloadInfo& info)
@@ -80,7 +50,6 @@ NeonReduceWorkload::NeonReduceWorkload(const ReduceQueueDescriptor& descriptor,
     arm_compute::Coordinates coords = BuildArmComputeReductionCoordinates(input.info()->num_dimensions(),
                                                                           info.m_InputTensorInfos[0].GetNumDimensions(),
                                                                           m_Data.m_Parameters.m_vAxis);
-
     m_Layer.configure(&input,
                       &output,
                       static_cast<unsigned int>(coords[0]),