IVGCVSW-2701 Add Serializer and Deserializer for Pad

Change-Id: I71184236f0394518f29944a77d4b934cbde9e53d
Signed-off-by: Nattapat Chaimanowong <nattapat.chaimanowong@arm.com>

10 files changed, 257 insertions, 4 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index a21b5f21e8..037a9aee2c 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -605,6 +605,7 @@ if(BUILD_UNIT_TESTS)
                 src/armnnDeserializer/test/DeserializeFullyConnected.cpp
                 src/armnnDeserializer/test/DeserializeMultiplication.cpp
                 src/armnnDeserializer/test/DeserializeNormalization.cpp
+                src/armnnDeserializer/test/DeserializePad.cpp
                 src/armnnDeserializer/test/DeserializePermute.cpp
                 src/armnnDeserializer/test/DeserializePooling2d.cpp
                 src/armnnDeserializer/test/DeserializeReshape.cpp
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index c7049f6a15..b8a1eaa84a 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -198,6 +198,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
     m_ParserFunctions[Layer_MaximumLayer]                = &Deserializer::ParseMaximum;
     m_ParserFunctions[Layer_MultiplicationLayer]         = &Deserializer::ParseMultiplication;
     m_ParserFunctions[Layer_NormalizationLayer]          = &Deserializer::ParseNormalization;
+    m_ParserFunctions[Layer_PadLayer]                    = &Deserializer::ParsePad;
     m_ParserFunctions[Layer_PermuteLayer]                = &Deserializer::ParsePermute;
     m_ParserFunctions[Layer_Pooling2dLayer]              = &Deserializer::ParsePooling2d;
     m_ParserFunctions[Layer_ReshapeLayer]                = &Deserializer::ParseReshape;
@@ -241,6 +242,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
             return graphPtr->layers()->Get(layerIndex)->layer_as_NormalizationLayer()->base();
         case Layer::Layer_OutputLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_OutputLayer()->base()->base();
+        case Layer::Layer_PadLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_PadLayer()->base();
         case Layer::Layer_PermuteLayer:
             return graphPtr->layers()->Get(layerIndex)->layer_as_PermuteLayer()->base();
         case Layer::Layer_Pooling2dLayer:
@@ -1090,6 +1093,44 @@ void Deserializer::ParseFullyConnected(GraphPtr graph, unsigned int layerIndex)
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void Deserializer::ParsePad(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_PadLayer()->descriptor();
+    auto flatBufferPadList = flatBufferDescriptor->padList();
+
+    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::PadDescriptor descriptor(padList);
+
+    auto layerName = GetLayerName(graph, layerIndex);
+    IConnectableLayer* layer = m_Network->AddPadLayer(descriptor, layerName.c_str());
+
+    armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]);
+    layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    RegisterInputSlots(graph, layerIndex, layer);
+    RegisterOutputSlots(graph, layerIndex, layer);
+}
+
 void Deserializer::ParsePermute(GraphPtr graph, unsigned int layerIndex)
 {
     CHECK_LAYERS(graph, 0, layerIndex);
diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp
index fba8b88044..ec10cb5817 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -84,6 +84,7 @@ private:
     void ParseMaximum(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);
     void ParsePermute(GraphPtr graph, unsigned int layerIndex);
     void ParsePooling2d(GraphPtr graph, unsigned int layerIndex);
     void ParseReshape(GraphPtr graph, unsigned int layerIndex);
diff --git a/src/armnnDeserializer/DeserializerSupport.md b/src/armnnDeserializer/DeserializerSupport.md
index cf8f6dea2d..1f479b94b8 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -19,10 +19,11 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
 * Minimum
 * Multiplication
 * Normalization
+* Pad
 * Permute
 * Pooling2d
 * Reshape
 * Softmax
 * SpaceToBatchNd
 
-More machine learning layers will be supported in future releases.
\ No newline at end of file
+More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializer/test/DeserializePad.cpp b/src/armnnDeserializer/test/DeserializePad.cpp
new file mode 100644
index 0000000000..b18710a381
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializePad.cpp
@@ -0,0 +1,129 @@
+//
+// 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 PadFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit PadFixture(const std::string &inputShape,
+                        const std::string &padList,
+                        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: "PadLayer",
+                        layer: {
+                            base: {
+                                index: 1,
+                                layerName: "PadLayer",
+                                layerType: "Pad",
+                                inputSlots: [{
+                                    index: 0,
+                                    connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                }],
+                                outputSlots: [{
+                                    index: 0,
+                                    tensorInfo: {
+                                        dimensions: )" + outputShape + R"(,
+                                        dataType: )" + dataType + R"(
+                                    }
+                                }]
+                            },
+                            descriptor: {
+                                padList: )" + padList + 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 SimplePadFixture : PadFixture
+{
+    SimplePadFixture() : PadFixture("[ 2, 2, 2 ]",
+                                    "[ 0, 1, 2, 1, 2, 2 ]",
+                                    "[ 3, 5, 6 ]",
+                                    "QuantisedAsymm8") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SimplePadQuantisedAsymm8, SimplePadFixture)
+{
+    RunTest<3, armnn::DataType::QuantisedAsymm8>(0,
+                                                 {
+                                                    0, 4, 2, 5, 6, 1, 5, 2
+                                                 },
+                                                 {
+                                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                    4, 0, 0, 0, 0, 2, 5, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6,
+                                                    1, 0, 0, 0, 0, 5, 2, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
+                                                 });
+}
+
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs
index cde0087d6f..552c2cc056 100644
--- a/src/armnnSerializer/ArmnnSchema.fbs
+++ b/src/armnnSerializer/ArmnnSchema.fbs
@@ -100,7 +100,8 @@ enum LayerType : uint {
     Minimum = 16,
     Equal = 17,
     Maximum = 18,
-    Normalization = 19
+    Normalization = 19,
+    Pad = 20
 }
 
 // Base layer table to be used as part of other layers
@@ -324,6 +325,15 @@ table NormalizationDescriptor {
     dataLayout:DataLayout = NCHW;
 }
 
+table PadLayer {
+    base:LayerBase;
+    descriptor:PadDescriptor;
+}
+
+table PadDescriptor {
+    padList:[uint];
+}
+
 union Layer {
     ActivationLayer,
     AdditionLayer,
@@ -344,7 +354,8 @@ union Layer {
     MinimumLayer,
     EqualLayer,
     MaximumLayer,
-    NormalizationLayer
+    NormalizationLayer,
+    PadLayer
 }
 
 table AnyLayer {
diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp
index 2000726526..868a36d42e 100644
--- a/src/armnnSerializer/Serializer.cpp
+++ b/src/armnnSerializer/Serializer.cpp
@@ -306,6 +306,29 @@ void SerializerVisitor::VisitMultiplicationLayer(const armnn::IConnectableLayer*
     CreateAnyLayer(flatBufferMultiplicationLayer.o, serializer::Layer::Layer_MultiplicationLayer);
 }
 
+void SerializerVisitor::VisitPadLayer(const armnn::IConnectableLayer* layer,
+                                      const armnn::PadDescriptor& padDescriptor,
+                                      const char* name)
+{
+    auto flatBufferBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Pad);
+
+    std::vector<unsigned int> padList;
+    for (auto& p: padDescriptor.m_PadList)
+    {
+        padList.push_back(p.first);
+        padList.push_back(p.second);
+    }
+
+    auto flatBufferPadDesc = serializer::CreatePadDescriptor(m_flatBufferBuilder,
+                                                             m_flatBufferBuilder.CreateVector(padList));
+
+    auto flatBufferPadLayer = serializer::CreatePadLayer(m_flatBufferBuilder,
+                                                         flatBufferBaseLayer,
+                                                         flatBufferPadDesc);
+
+    CreateAnyLayer(flatBufferPadLayer.o, serializer::Layer::Layer_PadLayer);
+}
+
 void SerializerVisitor::VisitPermuteLayer(const armnn::IConnectableLayer* layer,
                                           const armnn::PermuteDescriptor& permuteDescriptor,
                                           const char* name)
diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp
index 7e6097c465..ef56c25f2c 100644
--- a/src/armnnSerializer/Serializer.hpp
+++ b/src/armnnSerializer/Serializer.hpp
@@ -98,6 +98,10 @@ public:
                           armnn::LayerBindingId id,
                           const char* name = nullptr) override;
 
+    void VisitPadLayer(const armnn::IConnectableLayer* layer,
+                       const armnn::PadDescriptor& PadDescriptor,
+                       const char* name = nullptr) override;
+
     void VisitPermuteLayer(const armnn::IConnectableLayer* layer,
                            const armnn::PermuteDescriptor& PermuteDescriptor,
                            const char* name = nullptr) override;
diff --git a/src/armnnSerializer/SerializerSupport.md b/src/armnnSerializer/SerializerSupport.md
index d018a35c3a..a77e8860a2 100644
--- a/src/armnnSerializer/SerializerSupport.md
+++ b/src/armnnSerializer/SerializerSupport.md
@@ -19,10 +19,11 @@ The Arm NN SDK Serializer currently supports the following layers:
 * Minimum
 * Multiplication
 * Normalization
+* Pad
 * Permute
 * Pooling2d
 * Reshape
 * Softmax
 * SpaceToBatchNd
 
-More machine learning layers will be supported in future releases.
\ No newline at end of file
+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 271b3e71bd..110bf0c581 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -980,4 +980,45 @@ BOOST_AUTO_TEST_CASE(SerializeDeserializeEqual)
                                             {outputTensorInfo.GetShape()},
                                             {0, 1});
 }
+
+BOOST_AUTO_TEST_CASE(SerializeDeserializePad)
+{
+    class VerifyPadName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+    {
+    public:
+        void VisitPadLayer(const armnn::IConnectableLayer*,
+                           const armnn::PadDescriptor& descriptor,
+                           const char* name) override
+        {
+            BOOST_TEST(name == "PadLayer");
+        }
+    };
+
+    armnn::PadDescriptor desc({{0, 0}, {1, 0}, {1, 1}, {1, 2}});
+
+    const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({1, 2, 3, 4}, armnn::DataType::Float32);
+    const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 5, 7}, armnn::DataType::Float32);
+
+    armnn::INetworkPtr network = armnn::INetwork::Create();
+    armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+    armnn::IConnectableLayer* const padLayer = network->AddPadLayer(desc, "PadLayer");
+    armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+    inputLayer->GetOutputSlot(0).Connect(padLayer->GetInputSlot(0));
+    inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+    padLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    padLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+    armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+    BOOST_CHECK(deserializedNetwork);
+
+    VerifyPadName nameChecker;
+    deserializedNetwork->Accept(nameChecker);
+
+    CheckDeserializedNetworkAgainstOriginal(*network,
+                                            *deserializedNetwork,
+                                            {inputTensorInfo.GetShape()},
+                                            {outputTensorInfo.GetShape()});
+}
+
 BOOST_AUTO_TEST_SUITE_END()