IVGCVSW-2708 Add Serializer and Deserializer SpaceToBatchNd

Change-Id: I14f2a660654dc87939fe413fafa9384f09594f68
Signed-off-by: Nattapat Chaimanowong <nattapat.chaimanowong@arm.com>

10 files changed, 284 insertions, 2 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index a40077680f..0823f0878f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -604,6 +604,7 @@ if(BUILD_UNIT_TESTS)
                 src/armnnDeserializer/test/DeserializePermute.cpp
                 src/armnnDeserializer/test/DeserializePooling2d.cpp
                 src/armnnDeserializer/test/DeserializeReshape.cpp
+                src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
                 src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
                 src/armnnDeserializer/test/SchemaSerialize.s
                 )
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index b263c3a769..64f8e44429 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -196,6 +196,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
     m_ParserFunctions[Layer_Pooling2dLayer]              = &Deserializer::ParsePooling2d;
     m_ParserFunctions[Layer_ReshapeLayer]                = &Deserializer::ParseReshape;
     m_ParserFunctions[Layer_SoftmaxLayer]                = &Deserializer::ParseSoftmax;
+    m_ParserFunctions[Layer_SpaceToBatchNdLayer]         = &Deserializer::ParseSpaceToBatchNd;
 }
 
 Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -230,6 +231,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
             return graphPtr->layers()->Get(layerIndex)->layer_as_ReshapeLayer()->base();
         case Layer::Layer_SoftmaxLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_SoftmaxLayer()->base();
+        case Layer::Layer_SpaceToBatchNdLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_SpaceToBatchNdLayer()->base();
         case Layer::Layer_NONE:
         default:
             throw ParseException(boost::str(
@@ -1176,4 +1179,47 @@ void Deserializer::ParseSoftmax(GraphPtr graph, unsigned int layerIndex)
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void Deserializer::ParseSpaceToBatchNd(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_SpaceToBatchNdLayer()->descriptor();
+    auto flatBufferPadList = flatBufferDescriptor->padList();
+    auto flatBufferBlockShape = flatBufferDescriptor->blockShape();
+
+    if (flatBufferPadList->Length() % 2 != 0)
+    {
+        throw ParseException(boost::str(
+            boost::format("The size of the pad list must be divisible by 2 %1%") % CHECK_LOCATION().AsString()));
+    }
+
+    std::vector<std::pair<unsigned int, unsigned int>> padList;
+    padList.reserve(flatBufferPadList->Length() / 2);
+    for (unsigned int i = 0; i < flatBufferPadList->Length() - 1; i += 2)
+    {
+        padList.emplace_back(flatBufferPadList->Get(i), flatBufferPadList->Get(i+1));
+    }
+
+    armnn::SpaceToBatchNdDescriptor descriptor;
+    descriptor.m_DataLayout = ToDataLayout(flatBufferDescriptor->dataLayout());
+    descriptor.m_BlockShape =
+        std::vector<unsigned int>(flatBufferBlockShape->begin(), flatBufferBlockShape->end());
+    descriptor.m_PadList = padList;
+
+    auto layerName = GetLayerName(graph, layerIndex);
+    IConnectableLayer* layer = m_Network->AddSpaceToBatchNdLayer(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 9159ff2f36..c88459d97a 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -79,6 +79,7 @@ private:
     void ParsePooling2d(GraphPtr graph, unsigned int layerIndex);
     void ParseReshape(GraphPtr graph, unsigned int layerIndex);
     void ParseSoftmax(GraphPtr graph, unsigned int layerIndex);
+    void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex);
 
     void RegisterOutputSlotOfConnection(uint32_t connectionIndex, armnn::IOutputSlot* slot);
     void RegisterInputSlotOfConnection(uint32_t connectionIndex, armnn::IInputSlot* slot);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index 988144425c..4ae9780bc7 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -17,5 +17,6 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
 * Pooling2d
 * Reshape
 * Softmax
+* SpaceToBatchNd
 
 More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp b/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
new file mode 100644
index 0000000000..4b34390ed5
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
@@ -0,0 +1,140 @@
+//
+// 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>
+
+BOOST_AUTO_TEST_SUITE(Deserializer)
+
+struct SpaceToBatchNdFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit SpaceToBatchNdFixture(const std::string &inputShape,
+                                   const std::string &blockShape,
+                                   const std::string &padList,
+                                   const std::string &dataLayout,
+                                   const std::string &outputShape,
+                                   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: "SpaceToBatchNdLayer",
+                        layer: {
+                            base: {
+                                index: 1,
+                                layerName: "SpaceToBatchNdLayer",
+                                layerType: "SpaceToBatchNd",
+                                inputSlots: [{
+                                    index: 0,
+                                    connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                }],
+                                outputSlots: [{
+                                    index: 0,
+                                    tensorInfo: {
+                                        dimensions: )" + outputShape + R"(,
+                                        dataType: )" + dataType + R"(
+                                    }
+                                }]
+                            },
+                            descriptor: {
+                                blockShape: )" + blockShape + R"(,
+                                padList: )" + padList + R"(,
+                                dataLayout: )" + dataLayout + R"(,
+                            }
+                        }
+                    },
+                    {
+                        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"(
+                                        },
+                                    }],
+                                }
+                            }
+                        },
+                    }
+                ]
+            }
+        )";
+        SetupSingleInputSingleOutput("InputLayer", "OutputLayer");
+    }
+};
+
+struct SimpleSpaceToBatchNdFixture : SpaceToBatchNdFixture
+{
+    SimpleSpaceToBatchNdFixture() : SpaceToBatchNdFixture("[ 2, 1, 2, 4 ]",
+                                                          "[ 2, 2 ]",
+                                                          "[ 0, 0, 2, 0 ]",
+                                                          "NCHW",
+                                                          "[ 8, 1, 1, 3 ]",
+                                                          "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimpleSpaceToBatchNdFloat32, SimpleSpaceToBatchNdFixture)
+{
+    RunTest<4, armnn::DataType::Float32>(0,
+                                         {
+                                             1.0f,  2.0f,  3.0f,  4.0f,
+                                             5.0f,  6.0f,  7.0f,  8.0f,
+                                             9.0f, 10.0f, 11.0f, 12.0f,
+                                            13.0f, 14.0f, 15.0f, 16.0f
+                                         },
+                                         {
+                                             0.0f,  1.0f,  3.0f,
+                                             0.0f,  9.0f, 11.0f,
+                                             0.0f,  2.0f,  4.0f,
+                                             0.0f, 10.0f, 12.0f,
+                                             0.0f,  5.0f,  7.0f,
+                                             0.0f, 13.0f, 15.0f,
+                                             0.0f,  6.0f,  8.0f,
+                                             0.0f, 14.0f, 16.0f
+                                         });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs
index db70e7bd4c..c1e4e3826a 100644
--- a/src/armnnSerializer/ArmnnSchema.fbs
+++ b/src/armnnSerializer/ArmnnSchema.fbs
@@ -93,7 +93,8 @@ enum LayerType : uint {
     Activation = 9,
     Permute = 10,
     FullyConnected = 11,
-    Constant = 12
+    Constant = 12,
+    SpaceToBatchNd = 13
 }
 
 // Base layer table to be used as part of other layers
@@ -254,6 +255,17 @@ table PermuteDescriptor {
     dimMappings:[uint];
 }
 
+table SpaceToBatchNdLayer {
+    base:LayerBase;
+    descriptor:SpaceToBatchNdDescriptor;
+}
+
+table SpaceToBatchNdDescriptor {
+    blockShape:[uint];
+    padList:[uint];
+    dataLayout:DataLayout;
+}
+
 union Layer {
     ActivationLayer,
     AdditionLayer,
@@ -267,7 +279,8 @@ union Layer {
     PermuteLayer,
     Pooling2dLayer,
     ReshapeLayer,
-    SoftmaxLayer
+    SoftmaxLayer,
+    SpaceToBatchNdLayer
 }
 
 table AnyLayer {
diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp
index b8f5c3b555..1c1cefd455 100644
--- a/src/armnnSerializer/Serializer.cpp
+++ b/src/armnnSerializer/Serializer.cpp
@@ -380,6 +380,35 @@ void SerializerVisitor::VisitFullyConnectedLayer(const armnn::IConnectableLayer*
     CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_FullyConnectedLayer);
 }
 
+// Build FlatBuffer for SpaceToBatchNd Layer
+void SerializerVisitor::VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer* layer,
+                                                 const armnn::SpaceToBatchNdDescriptor& spaceToBatchNdDescriptor,
+                                                 const char* name)
+{
+    // Create FlatBuffer BaseLayer
+    auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_SpaceToBatchNd);
+
+    std::vector<unsigned int> padList;
+    padList.reserve(spaceToBatchNdDescriptor.m_PadList.size()*2);
+    for (auto& pad : spaceToBatchNdDescriptor.m_PadList)
+    {
+        padList.push_back(pad.first);
+        padList.push_back(pad.second);
+    }
+
+    auto flatBufferDescriptor =
+        CreateSpaceToBatchNdDescriptor(m_flatBufferBuilder,
+                                       m_flatBufferBuilder.CreateVector(spaceToBatchNdDescriptor.m_BlockShape),
+                                       m_flatBufferBuilder.CreateVector(padList),
+                                       GetFlatBufferDataLayout(spaceToBatchNdDescriptor.m_DataLayout));
+
+    auto flatBufferLayer = serializer::CreateSpaceToBatchNdLayer(m_flatBufferBuilder,
+                                                                 flatBufferBaseLayer,
+                                                                 flatBufferDescriptor);
+
+    CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_SpaceToBatchNdLayer);
+}
+
 fb::Offset<serializer::LayerBase> SerializerVisitor::CreateLayerBase(const IConnectableLayer* layer,
                                                                      const serializer::LayerType layerType)
 {
diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp
index 781648fa62..a86e04f05d 100644
--- a/src/armnnSerializer/Serializer.hpp
+++ b/src/armnnSerializer/Serializer.hpp
@@ -98,6 +98,10 @@ public:
                            const armnn::SoftmaxDescriptor& softmaxDescriptor,
                            const char* name = nullptr) override;
 
+    void VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer* layer,
+                                  const armnn::SpaceToBatchNdDescriptor& spaceToBatchNdDescriptor,
+                                  const char* name = nullptr) override;
+
 private:
 
     /// Creates the Input Slots and Output Slots and LayerBase for the layer.
diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md
index 9e84b63adc..776f6129bd 100644
--- a/src/armnnSerializer/SerializerSupport.md
+++ b/src/armnnSerializer/SerializerSupport.md
@@ -17,5 +17,6 @@ The Arm NN SDK Serializer currently supports the following layers:
 * Pooling2d
 * Reshape
 * Softmax
+* SpaceToBatchNd
 
 More machine learning layers will be supported in future releases.
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index 4e90dbe9e1..f64c14a184 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -636,4 +636,50 @@ BOOST_AUTO_TEST_CASE(SerializeDeserializeFullyConnected)
                                             outputInfo.GetShape());
 }
 
+BOOST_AUTO_TEST_CASE(SerializeDeserializeSpaceToBatchNd)
+{
+    class VerifySpaceToBatchNdName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+    {
+    public:
+        void VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer*,
+                                      const armnn::SpaceToBatchNdDescriptor& spaceToBatchNdDescriptor,
+                                      const char* name) override
+        {
+            BOOST_TEST(name == "SpaceToBatchNdLayer");
+        }
+    };
+
+    unsigned int inputShape[] = {2, 1, 2, 4};
+    unsigned int outputShape[] = {8, 1, 1, 3};
+
+    armnn::SpaceToBatchNdDescriptor desc;
+    desc.m_DataLayout = armnn::DataLayout::NCHW;
+    desc.m_BlockShape = {2, 2};
+    desc.m_PadList = {{0, 0}, {2, 0}};
+
+    auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32);
+    auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
+
+    armnn::INetworkPtr network = armnn::INetwork::Create();
+    armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+    armnn::IConnectableLayer* const spaceToBatchNdLayer = network->AddSpaceToBatchNdLayer(desc, "SpaceToBatchNdLayer");
+    armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+    inputLayer->GetOutputSlot(0).Connect(spaceToBatchNdLayer->GetInputSlot(0));
+    inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+    spaceToBatchNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    spaceToBatchNdLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+    BOOST_CHECK(deserializedNetwork);
+
+    VerifySpaceToBatchNdName nameChecker;
+    deserializedNetwork->Accept(nameChecker);
+
+    CheckDeserializedNetworkAgainstOriginal(*network,
+                                            *deserializedNetwork,
+                                            inputTensorInfo.GetShape(),
+                                            outputTensorInfo.GetShape());
+}
+
 BOOST_AUTO_TEST_SUITE_END()