IVGCVSW-2681 Serialize/de-serialize the BatchNormalization layer

Change-Id: I418c4465366742262fb6e6c1eeba76c634beaeb5
Signed-off-by: ruoyan01 <ruomei.yan@arm.com>

4 files changed, 214 insertions, 0 deletions

diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index 77bd7498ee..e8cda2e3d3 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -188,6 +188,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
     m_ParserFunctions[Layer_ActivationLayer]             = &Deserializer::ParseActivation;
     m_ParserFunctions[Layer_AdditionLayer]               = &Deserializer::ParseAdd;
     m_ParserFunctions[Layer_BatchToSpaceNdLayer]         = &Deserializer::ParseBatchToSpaceNd;
+    m_ParserFunctions[Layer_BatchNormalizationLayer]     = &Deserializer::ParseBatchNormalization;
     m_ParserFunctions[Layer_ConstantLayer]               = &Deserializer::ParseConstant;
     m_ParserFunctions[Layer_Convolution2dLayer]          = &Deserializer::ParseConvolution2d;
     m_ParserFunctions[Layer_DepthwiseConvolution2dLayer] = &Deserializer::ParseDepthwiseConvolution2d;
@@ -220,6 +221,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
             return graphPtr->layers()->Get(layerIndex)->layer_as_AdditionLayer()->base();
         case Layer::Layer_BatchToSpaceNdLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_BatchToSpaceNdLayer()->base();
+        case Layer::Layer_BatchNormalizationLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer()->base();
         case Layer::Layer_ConstantLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_ConstantLayer()->base();
         case Layer::Layer_Convolution2dLayer:
@@ -848,6 +851,43 @@ void Deserializer::ParseBatchToSpaceNd(GraphPtr graph, unsigned int layerIndex)
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void Deserializer::ParseBatchNormalization(GraphPtr graph, unsigned int layerIndex)
+{
+    CHECK_LAYERS(graph, 0, layerIndex);
+
+    auto inputs = GetInputs(graph, layerIndex);
+    CHECK_VALID_SIZE(inputs.size(), 1);
+
+    auto outputs = GetOutputs(graph, layerIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+    auto outputInfo = ToTensorInfo(outputs[0]);
+
+    auto layerName = boost::str(boost::format("BatchNormalization:%1%") % layerIndex);
+
+    auto serializerLayer = graph->layers()->Get(layerIndex)->layer_as_BatchNormalizationLayer();
+    auto serializerDescriptor = serializerLayer->descriptor();
+
+    armnn::BatchNormalizationDescriptor descriptor;
+    descriptor.m_Eps = serializerDescriptor->eps();
+    descriptor.m_DataLayout = ToDataLayout(serializerDescriptor->dataLayout());
+
+    armnn::ConstTensor mean     = ToConstTensor(serializerLayer->mean());
+    armnn::ConstTensor variance = ToConstTensor(serializerLayer->variance());
+    armnn::ConstTensor beta     = ToConstTensor(serializerLayer->beta());
+    armnn::ConstTensor gamma    = ToConstTensor(serializerLayer->gamma());
+
+    IConnectableLayer* layer = m_Network->AddBatchNormalizationLayer(descriptor,
+                                                                     mean,
+                                                                     variance,
+                                                                     beta,
+                                                                     gamma,
+                                                                     layerName.c_str());
+    layer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+    RegisterInputSlots(graph, layerIndex, layer);
+    RegisterOutputSlots(graph, layerIndex, layer);
+}
+
 void Deserializer::ParseConstant(GraphPtr graph, unsigned int layerIndex)
 {
     CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index aa5035ed31..237cb9f975 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -74,6 +74,7 @@ private:
     void ParseActivation(GraphPtr graph, unsigned int layerIndex);
     void ParseAdd(GraphPtr graph, unsigned int layerIndex);
     void ParseBatchToSpaceNd(GraphPtr graph, unsigned int layerIndex);
+    void ParseBatchNormalization(GraphPtr graph, unsigned int layerIndex);
     void ParseConstant(GraphPtr graph, unsigned int layerIndex);
     void ParseConvolution2d(GraphPtr graph, unsigned int layerIndex);
     void ParseDepthwiseConvolution2d(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 765432b8e4..b5e9b6b0a2 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -9,6 +9,7 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
 * Activation
 * Addition
 * BatchToSpaceNd
+* BatchNormalization
 * Constant
 * Convolution2d
 * DepthwiseConvolution2d
diff --git a/src/armnnDeserializer/test/DeserializeBatchNormalization.cpp b/src/armnnDeserializer/test/DeserializeBatchNormalization.cpp
new file mode 100644
index 0000000000..3e1be6cf72
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeBatchNormalization.cpp
@@ -0,0 +1,172 @@
+//
+// 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 BatchNormalizationFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit BatchNormalizationFixture(const std::string &inputShape,
+                                       const std::string &outputShape,
+                                       const std::string &meanShape,
+                                       const std::string &varianceShape,
+                                       const std::string &offsetShape,
+                                       const std::string &scaleShape,
+                                       const std::string &dataType,
+                                       const std::string &dataLayout)
+    {
+        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"(",
+                                quantizationScale: 0.5,
+                                quantizationOffset: 0
+                                },
+                            }]
+                        },
+                    }
+                },
+            },
+        {
+        layer_type: "BatchNormalizationLayer",
+        layer : {
+            base: {
+                index:1,
+                layerName: "BatchNormalizationLayer",
+                layerType: "BatchNormalization",
+                inputSlots: [{
+                        index: 0,
+                        connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                   }],
+                outputSlots: [{
+                    index: 0,
+                    tensorInfo: {
+                        dimensions: )" + outputShape + R"(,
+                        dataType: ")" + dataType + R"("
+                    },
+                    }],
+                },
+            descriptor: {
+                eps: 0.0010000000475,
+                dataLayout: ")" + dataLayout + R"("
+                },
+            mean: {
+                info: {
+                         dimensions: )" + meanShape + R"(,
+                         dataType: ")" + dataType + R"("
+                     },
+                data_type: IntData,
+                data: {
+                    data: [1084227584],
+                    }
+                },
+            variance: {
+                info: {
+                         dimensions: )" + varianceShape + R"(,
+                         dataType: ")" + dataType + R"("
+                     },
+               data_type: IntData,
+                data: {
+                    data: [1073741824],
+                    }
+                },
+            beta: {
+                info: {
+                         dimensions: )" + offsetShape + R"(,
+                         dataType: ")" + dataType + R"("
+                     },
+                data_type: IntData,
+                data: {
+                    data: [0],
+                    }
+                },
+            gamma: {
+                info: {
+                         dimensions: )" + scaleShape + R"(,
+                         dataType: ")" + dataType + R"("
+                     },
+                data_type: IntData,
+                data: {
+                    data: [1065353216],
+                    }
+                },
+            },
+        },
+        {
+        layer_type: "OutputLayer",
+        layer: {
+            base:{
+                layerBindingId: 0,
+                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 BatchNormFixture : BatchNormalizationFixture
+{
+    BatchNormFixture():BatchNormalizationFixture("[ 1, 3, 3, 1 ]",
+                                                 "[ 1, 3, 3, 1 ]",
+                                                 "[ 1 ]",
+                                                 "[ 1 ]",
+                                                 "[ 1 ]",
+                                                 "[ 1 ]",
+                                                 "Float32",
+                                                 "NHWC"){}
+};
+
+BOOST_FIXTURE_TEST_CASE(BatchNormalizationFloat32, BatchNormFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(0,
+                                         {{"InputLayer", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f }}},
+                                         {{"OutputLayer",{ -2.8277204f, -2.12079024f, -1.4138602f,
+                                           -0.7069301f,  0.0f,         0.7069301f,
+                                           1.4138602f,  2.12079024f,  2.8277204f }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()