backends/reference: Add ReduceSum operation support

This patch addes ReduceSum operation support for reference backend,
which computes the sum of elements across dimensions of a tensor.

Changelog v1:
- Fix file header descriptions.

Chagelog v2:
- Fix line limit issue.
- Fix type conversion issue.

Changelog v3:
- Remove tabs.
- Modify newly added file headers.

Changelog v4:
- Symbol on header isn't allowed so drop it from newly added file headers.

Changelog v5:
- Remove tabs, fix the use of brackets and align lines correctly.

Changelog v6:
- Add serializer and deserializer support.

Changelog v7:
- Fix build error add missed code.

Changelog v8:
- Rename ReduceSumDecriptor to ReduceDescriptor
    - Update m_KeepDims field data type to bool on ReduceDescriptor
    - Add ReduceOperation field to ReduceDescriptor

- Rename ReduceSumLayer to ReduceLayer
    - Update ReduceLayer to use ReduceDescriptor
    - Update ReduceLayer::ValidateTensorShapesFromInputs() function

- Rename RefReduceSumWokload to RefReduceWorkload
    - Update workload to use ReduceDescriptor
    - Update workload to use Decoders and Encoders

- Remove ReduceSum.hpp and ReduceSum.cpp
- Added Reduce.hpp and Reduce.cpp
     - Move Mean.cpp (which is implementing REDUCE_MEAN) functionality to Reduce.cpp
     - Update RefMeanWorkload to call Reduce function with ReduceOperation::Mean argument

- Remove Mean.hpp and Mean.cpp
- Update the Serializer/Deserializer ArmnnSchema.fbs for ReduceLayer, ReduceDescriptor, and ReduceOperation
- Update Serializer and Deserializer for serializing/parsing ReduceLayer
- Added TfLiter parser Sum test for REDUCE_SUM operator
- Make corresponding changes on front-end and Ref backend to support REDUCE_SUM operator

Changelog v9:
- Fixed build errors.

Change-Id: I8c8e034f3df73f9565b3c18eff51ecca6c542195
Signed-off-by: Inki Dae <inki.dae@samsung.com>
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>

3 files changed, 179 insertions, 0 deletions

diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index 14c2af4fe1..e98ff15aa9 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -251,6 +251,7 @@ m_ParserFunctions(Layer_MAX+1, &IDeserializer::DeserializerImpl::ParseUnsupporte
     m_ParserFunctions[Layer_QuantizeLayer]               = &DeserializerImpl::ParseQuantize;
     m_ParserFunctions[Layer_QuantizedLstmLayer]          = &DeserializerImpl::ParseQuantizedLstm;
     m_ParserFunctions[Layer_RankLayer]                   = &DeserializerImpl::ParseRank;
+    m_ParserFunctions[Layer_ReduceLayer]                 = &DeserializerImpl::ParseReduce;
     m_ParserFunctions[Layer_ReshapeLayer]                = &DeserializerImpl::ParseReshape;
     m_ParserFunctions[Layer_ResizeBilinearLayer]         = &DeserializerImpl::ParseResizeBilinear;
     m_ParserFunctions[Layer_ResizeLayer]                 = &DeserializerImpl::ParseResize;
@@ -363,6 +364,8 @@ LayerBaseRawPtr IDeserializer::DeserializerImpl::GetBaseLayer(const GraphPtr& gr
             return graphPtr->layers()->Get(layerIndex)->layer_as_QuantizedLstmLayer()->base();
         case Layer::Layer_RankLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_RankLayer()->base();
+        case Layer::Layer_ReduceLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_ReduceLayer()->base();
         case Layer::Layer_ReshapeLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();
         case Layer::Layer_ResizeBilinearLayer:
@@ -498,6 +501,23 @@ armnn::ComparisonOperation ToComparisonOperation(armnnSerializer::ComparisonOper
     }
 }
 
+armnn::ReduceOperation ToReduceOperation(armnnSerializer::ReduceOperation operation)
+{
+    switch (operation)
+    {
+        case armnnSerializer::ReduceOperation::ReduceOperation_Sum:
+            return armnn::ReduceOperation::Sum;
+        case armnnSerializer::ReduceOperation::ReduceOperation_Max:
+            return armnn::ReduceOperation::Max;
+        case armnnSerializer::ReduceOperation::ReduceOperation_Mean:
+            return armnn::ReduceOperation::Mean;
+        case armnnSerializer::ReduceOperation::ReduceOperation_Min:
+            return armnn::ReduceOperation::Min;
+        default:
+            return armnn::ReduceOperation::Sum;
+    }
+}
+
 armnn::LogicalBinaryOperation ToLogicalBinaryOperation(armnnSerializer::LogicalBinaryOperation operation)
 {
     switch (operation)
@@ -2082,6 +2102,38 @@ void IDeserializer::DeserializerImpl::ParseRank(GraphPtr graph, unsigned int lay
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void IDeserializer::DeserializerImpl::ParseReduce(GraphPtr graph, unsigned int layerIndex)
+{
+    CHECK_LAYERS(graph, 0, layerIndex);
+    CHECK_LOCATION();
+
+    auto inputs = GetInputs(graph, layerIndex);
+    CHECK_VALID_SIZE(inputs.size(), 1);
+
+    auto outputs = GetOutputs(graph, layerIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto fbLayer      = graph->layers()->Get(layerIndex)->layer_as_ReduceLayer();
+    auto fbDescriptor = fbLayer->descriptor();
+    auto flatBufferAxis = fbDescriptor->axis();
+
+    armnn::ReduceDescriptor descriptor;
+    descriptor.m_TargetHeight = fbDescriptor->targetHeight();
+    descriptor.m_TargetWidth  = fbDescriptor->targetWidth();
+    descriptor.m_KeepDims     = fbDescriptor->keepDims();
+    descriptor.m_vAxis = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());
+    descriptor.m_ReduceOperation = ToReduceOperation(fbDescriptor->reduceOperation());
+
+    const std::string& layerName = GetLayerName(graph, layerIndex);
+    IConnectableLayer* layer     = m_Network->AddReduceLayer(descriptor, layerName.c_str());
+
+    armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    RegisterInputSlots(graph, layerIndex, layer);
+    RegisterOutputSlots(graph, layerIndex, layer);
+}
+
 void IDeserializer::DeserializerImpl::ParseReshape(GraphPtr graph, unsigned int layerIndex)
 {
     CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index e232feed9b..f4f64240a0 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -119,6 +119,7 @@ private:
     void ParseQLstm(GraphPtr graph, unsigned int layerIndex);
     void ParseQuantize(GraphPtr graph, unsigned int layerIndex);
     void ParseRank(GraphPtr graph, unsigned int layerIndex);
+    void ParseReduce(GraphPtr graph, unsigned int layerIndex);
     void ParseReshape(GraphPtr graph, unsigned int layerIndex);
     void ParseResize(GraphPtr graph, unsigned int layerIndex);
     void ParseResizeBilinear(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/test/DeserializeReduceSum.cpp b/src/armnnDeserializer/test/DeserializeReduceSum.cpp
new file mode 100644
index 0000000000..d88613e593
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeReduceSum.cpp
@@ -0,0 +1,126 @@
+//
+// Copyright © 2020 Samsung Electronics Co Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <boost/test/unit_test.hpp>
+#include "ParserFlatbuffersSerializeFixture.hpp"
+#include "../Deserializer.hpp"
+
+#include <string>
+#include <iostream>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct ReduceSumFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit ReduceSumFixture(const std::string& inputShape,
+                              const std::string& outputShape,
+                              const std::string& axis,
+                              const std::string& dataType)
+    {
+        m_JsonString = R"(
+            {
+                inputIds: [0],
+                outputIds: [2],
+                layers: [
+                    {
+                        layer_type: "InputLayer",
+                        layer: {
+                            base: {
+                                layerBindingId: 0,
+                                base: {
+                                    index: 0,
+                                    layerName: "InputLayer",
+                                    layerType: "Input",
+                                    inputSlots: [{
+                                        index: 0,
+                                        connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                    }],
+                                    outputSlots: [{
+                                        index: 0,
+                                        tensorInfo: {
+                                            dimensions: )" + inputShape + R"(,
+                                            dataType: )" + dataType + R"(
+                                        }
+                                    }]
+                                }
+                            }
+                        }
+                    },
+                    {
+                        layer_type: "ReduceLayer",
+                        layer: {
+                            base: {
+                                index: 1,
+                                layerName: "ReduceSumLayer",
+                                layerType: "Reduce",
+                                inputSlots: [{
+                                    index: 0,
+                                    connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                }],
+                                outputSlots: [{
+                                    index: 0,
+                                    tensorInfo: {
+                                        dimensions: )" + outputShape + R"(,
+                                        dataType: )" + dataType + R"(
+                                    }
+                                }]
+                            },
+                            descriptor: {
+                                axis: )" + axis + R"(,
+                                keepDims: true,
+                                reduceOperation: Sum
+                            }
+                        }
+                    },
+                    {
+                        layer_type: "OutputLayer",
+                        layer: {
+                            base:{
+                                layerBindingId: 2,
+                                base: {
+                                    index: 2,
+                                    layerName: "OutputLayer",
+                                    layerType: "Output",
+                                    inputSlots: [{
+                                        index: 0,
+                                        connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+                                    }],
+                                    outputSlots: [{
+                                        index: 0,
+                                        tensorInfo: {
+                                            dimensions: )" + outputShape + R"(,
+                                            dataType: )" + dataType + R"(
+                                        },
+                                    }],
+                                }
+                            }
+                        },
+                    }
+                ]
+            }
+        )";
+        Setup();
+    }
+};
+
+struct SimpleReduceSumFixture : ReduceSumFixture
+{
+    SimpleReduceSumFixture()
+        : ReduceSumFixture("[ 1, 1, 3, 2 ]",     // inputShape
+                           "[ 1, 1, 1, 2 ]",     // outputShape
+                           "[ 2 ]",              // axis
+                           "Float32")            // dataType
+    {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleReduceSum, SimpleReduceSumFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(
+         0,
+         {{"InputLayer",  { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }}},
+         {{"OutputLayer", { 6.0f, 6.0f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()