IVGCVSW-2696 Serialize / de-serialize the Mean layer

Change-Id: Iee4bab5a6d6b992cf4bba8697a2918f854c906a3
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>

4 files changed, 160 insertions, 2 deletions

diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index 79713d4dbe..96879bb65a 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -198,8 +198,9 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
     m_ParserFunctions[Layer_FloorLayer]                  = &Deserializer::ParseFloor;
     m_ParserFunctions[Layer_GatherLayer]                 = &Deserializer::ParseGather;
     m_ParserFunctions[Layer_GreaterLayer]                = &Deserializer::ParseGreater;
-    m_ParserFunctions[Layer_MinimumLayer]                = &Deserializer::ParseMinimum;
     m_ParserFunctions[Layer_MaximumLayer]                = &Deserializer::ParseMaximum;
+    m_ParserFunctions[Layer_MeanLayer]                   = &Deserializer::ParseMean;
+    m_ParserFunctions[Layer_MinimumLayer]                = &Deserializer::ParseMinimum;
     m_ParserFunctions[Layer_MultiplicationLayer]         = &Deserializer::ParseMultiplication;
     m_ParserFunctions[Layer_NormalizationLayer]          = &Deserializer::ParseNormalization;
     m_ParserFunctions[Layer_PadLayer]                    = &Deserializer::ParsePad;
@@ -248,6 +249,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
             return graphPtr->layers()->Get(layerIndex)->layer_as_GreaterLayer()->base();
         case Layer::Layer_InputLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_InputLayer()->base()->base();
+        case Layer::Layer_MeanLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_MeanLayer()->base();
         case Layer::Layer_MinimumLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_MinimumLayer()->base();
         case Layer::Layer_MaximumLayer:
@@ -1733,4 +1736,32 @@ void Deserializer::ParseGather(GraphPtr graph, unsigned int layerIndex)
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void Deserializer::ParseMean(GraphPtr graph, unsigned int layerIndex)
+{
+    CHECK_LAYERS(graph, 0, layerIndex);
+
+    Deserializer::TensorRawPtrVector inputs = GetInputs(graph, layerIndex);
+    CHECK_VALID_SIZE(inputs.size(), 1);
+
+    Deserializer::TensorRawPtrVector outputs = GetOutputs(graph, layerIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto flatBufferDescriptor = graph->layers()->Get(layerIndex)->layer_as_MeanLayer()->descriptor();
+    auto flatBufferAxis = flatBufferDescriptor->axis();
+    auto flatBufferKeepDims = flatBufferDescriptor->keepDims();
+
+    armnn::MeanDescriptor descriptor;
+    descriptor.m_Axis = std::vector<unsigned int>(flatBufferAxis->begin(), flatBufferAxis->end());
+    descriptor.m_KeepDims = flatBufferKeepDims;
+
+    auto layerName = GetLayerName(graph, layerIndex);
+    IConnectableLayer* layer = m_Network->AddMeanLayer(descriptor, layerName.c_str());
+
+    armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    RegisterInputSlots(graph, layerIndex, layer);
+    RegisterOutputSlots(graph, layerIndex, layer);
+}
+
 } // namespace armnnDeserializer
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index 058002548a..4d9c13818b 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -84,8 +84,9 @@ private:
     void ParseFullyConnected(GraphPtr graph, unsigned int layerIndex);
     void ParseGather(GraphPtr graph, unsigned int layerIndex);
     void ParseGreater(GraphPtr graph, unsigned int layerIndex);
-    void ParseMinimum(GraphPtr graph, unsigned int layerIndex);
     void ParseMaximum(GraphPtr graph, unsigned int layerIndex);
+    void ParseMean(GraphPtr graph, unsigned int layerIndex);
+    void ParseMinimum(GraphPtr graph, unsigned int layerIndex);
     void ParseMultiplication(GraphPtr graph, unsigned int layerIndex);
     void ParseNormalization(GraphPtr graph, unsigned int layerIndex);
     void ParsePad(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index cc7c62662a..0f3d91d1e7 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -20,6 +20,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
 * Gather
 * Greater
 * Maximum
+* Mean
 * Minimum
 * Multiplication
 * Normalization
diff --git a/src/armnnDeserializer/test/DeserializeMean.cpp b/src/armnnDeserializer/test/DeserializeMean.cpp
new file mode 100644
index 0000000000..4ea745628c
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeMean.cpp
@@ -0,0 +1,125 @@
+//
+// Copyright © 2017 Arm Ltd. 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 MeanFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit MeanFixture(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: "MeanLayer",
+                        layer: {
+                            base: {
+                                index: 1,
+                                layerName: "MeanLayer",
+                                layerType: "Mean",
+                                inputSlots: [{
+                                    index: 0,
+                                    connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                }],
+                                outputSlots: [{
+                                    index: 0,
+                                    tensorInfo: {
+                                        dimensions: )" + outputShape + R"(,
+                                        dataType: )" + dataType + R"(
+                                    }
+                                }]
+                            },
+                            descriptor: {
+                                axis: )" + axis + R"(,
+                                keepDims: true
+                            }
+                        }
+                    },
+                    {
+                        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 SimpleMeanFixture : MeanFixture
+{
+    SimpleMeanFixture()
+        : MeanFixture("[ 1, 1, 3, 2 ]",     // inputShape
+                      "[ 1, 1, 1, 2 ]",     // outputShape
+                      "[ 2 ]",              // axis
+                      "Float32")            // dataType
+    {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleMean, SimpleMeanFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(
+         0,
+         {{"InputLayer",  { 1.0f, 1.0f, 2.0f, 2.0f, 3.0f, 3.0f }}},
+         {{"OutputLayer", { 2.0f, 2.0f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file