IVGCVSW-2711 Add Serializer and Deserializer for Subtraction

Change-Id: I87836b5314c1f791b4df2ca90d239573ca28a2da
Signed-off-by: Conor Kennedy <conor.kennedy@arm.com>
Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>

10 files changed, 262 insertions, 2 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 62f618a46d..60604f84dc 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -615,6 +615,7 @@ if(BUILD_UNIT_TESTS)
                 src/armnnDeserializer/test/DeserializeResizeBilinear.cpp
                 src/armnnDeserializer/test/DeserializeRsqrt.cpp
                 src/armnnDeserializer/test/DeserializeSpaceToBatchNd.cpp
+                src/armnnDeserializer/test/DeserializeSubtraction.cpp
                 src/armnnDeserializer/test/ParserFlatbuffersSerializeFixture.hpp
                 src/armnnDeserializer/test/SchemaSerialize.s
                 )
diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp
index aa7454339e..73c2042024 100644
--- a/src/armnnDeserializer/Deserializer.cpp
+++ b/src/armnnDeserializer/Deserializer.cpp
@@ -209,6 +209,7 @@ m_ParserFunctions(Layer_MAX+1, &Deserializer::ParseUnsupportedLayer)
     m_ParserFunctions[Layer_RsqrtLayer]                  = &Deserializer::ParseRsqrt;
     m_ParserFunctions[Layer_SoftmaxLayer]                = &Deserializer::ParseSoftmax;
     m_ParserFunctions[Layer_SpaceToBatchNdLayer]         = &Deserializer::ParseSpaceToBatchNd;
+    m_ParserFunctions[Layer_SubtractionLayer]            = &Deserializer::ParseSubtraction;
 }
 
 Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPtr, unsigned int layerIndex)
@@ -269,6 +270,8 @@ Deserializer::LayerBaseRawPtr Deserializer::GetBaseLayer(const GraphPtr& graphPt
             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_SubtractionLayer:
+            return graphPtr->layers()->Get(layerIndex)->layer_as_SubtractionLayer()->base();
         case Layer::Layer_NONE:
         default:
             throw ParseException(boost::str(
@@ -1639,4 +1642,24 @@ void Deserializer::ParseRsqrt(GraphPtr graph, unsigned int layerIndex)
     RegisterOutputSlots(graph, layerIndex, layer);
 }
 
+void Deserializer::ParseSubtraction(GraphPtr graph, unsigned int layerIndex)
+{
+    CHECK_LAYERS(graph, 0, layerIndex);
+    auto inputs = GetInputs(graph, layerIndex);
+    CHECK_LOCATION();
+    CHECK_VALID_SIZE(inputs.size(), 2);
+
+    auto outputs = GetOutputs(graph, layerIndex);
+    CHECK_VALID_SIZE(outputs.size(), 1);
+
+    auto layerName = GetLayerName(graph, layerIndex);
+    IConnectableLayer* layer = m_Network->AddSubtractionLayer(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 cabc91f58d..7595818628 100644
--- a/src/armnnDeserializer/Deserializer.hpp
+++ b/src/armnnDeserializer/Deserializer.hpp
@@ -95,6 +95,7 @@ private:
     void ParseRsqrt(GraphPtr graph, unsigned int layerIndex);
     void ParseSoftmax(GraphPtr graph, unsigned int layerIndex);
     void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex);
+    void ParseSubtraction(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 0a1ef75260..42da558738 100644
--- a/src/armnnDeserializer/DeserializerSupport.md
+++ b/src/armnnDeserializer/DeserializerSupport.md
@@ -30,5 +30,6 @@ The Arm NN SDK Deserialize parser currently supports the following layers:
 * Rsqrt
 * Softmax
 * SpaceToBatchNd
+* Subtraction
 
 More machine learning layers will be supported in future releases.
diff --git a/src/armnnDeserializer/test/DeserializeSubtraction.cpp b/src/armnnDeserializer/test/DeserializeSubtraction.cpp
new file mode 100644
index 0000000000..5058bb840d
--- /dev/null
+++ b/src/armnnDeserializer/test/DeserializeSubtraction.cpp
@@ -0,0 +1,176 @@
+//
+// 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 SubtractionFixture : public ParserFlatbuffersSerializeFixture
+{
+    explicit SubtractionFixture(const std::string & inputShape1,
+                                const std::string & inputShape2,
+                                const std::string & outputShape,
+                                const std::string & dataType)
+    {
+        m_JsonString = R"(
+        {
+            inputIds: [0, 1],
+            outputIds: [3],
+            layers: [
+            {
+                layer_type: "InputLayer",
+                layer: {
+                       base: {
+                             layerBindingId: 0,
+                             base: {
+                                   index: 0,
+                                   layerName: "inputLayer1",
+                                   layerType: "Input",
+                                   inputSlots: [{
+                                       index: 0,
+                                       connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                                   }],
+                                   outputSlots: [ {
+                                       index: 0,
+                                       tensorInfo: {
+                                           dimensions: )" + inputShape1 + R"(,
+                                           dataType: )" + dataType + R"(
+                                       },
+                                   }],
+                              },
+                       }},
+            },
+            {
+            layer_type: "InputLayer",
+            layer: {
+                   base: {
+                         layerBindingId: 1,
+                         base: {
+                               index:1,
+                               layerName: "inputLayer2",
+                               layerType: "Input",
+                               inputSlots: [{
+                                   index: 0,
+                                   connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                               }],
+                               outputSlots: [ {
+                                   index: 0,
+                                   tensorInfo: {
+                                       dimensions: )" + inputShape2 + R"(,
+                                       dataType: )" + dataType + R"(
+                                   },
+                               }],
+                         },
+                   }},
+            },
+            {
+            layer_type: "SubtractionLayer",
+            layer : {
+                    base: {
+                          index:2,
+                          layerName: "subtractionLayer",
+                          layerType: "Subtraction",
+                          inputSlots: [{
+                              index: 0,
+                              connection: {sourceLayerIndex:0, outputSlotIndex:0 },
+                          },
+                          {
+                              index: 1,
+                              connection: {sourceLayerIndex:1, outputSlotIndex:0 },
+                          }],
+                          outputSlots: [ {
+                              index: 0,
+                              tensorInfo: {
+                                  dimensions: )" + outputShape + R"(,
+                                  dataType: )" + dataType + R"(
+                              },
+                          }],
+                    }},
+            },
+            {
+            layer_type: "OutputLayer",
+            layer: {
+                   base:{
+                         layerBindingId: 0,
+                         base: {
+                               index: 3,
+                               layerName: "outputLayer",
+                               layerType: "Output",
+                               inputSlots: [{
+                                   index: 0,
+                                   connection: {sourceLayerIndex:2, outputSlotIndex:0 },
+                               }],
+                               outputSlots: [ {
+                                   index: 0,
+                                   tensorInfo: {
+                                       dimensions: )" + outputShape + R"(,
+                                       dataType: )" + dataType + R"(
+                                   },
+                               }],
+                        }}},
+            }]
+        }
+        )";
+        Setup();
+    }
+};
+
+struct SimpleSubtractionFixture : SubtractionFixture
+{
+    SimpleSubtractionFixture() : SubtractionFixture("[ 1, 4 ]",
+                                                    "[ 1, 4 ]",
+                                                    "[ 1, 4 ]",
+                                                    "QuantisedAsymm8") {}
+};
+
+struct SimpleSubtractionFixture2 : SubtractionFixture
+{
+    SimpleSubtractionFixture2() : SubtractionFixture("[ 1, 4 ]",
+                                                     "[ 1, 4 ]",
+                                                     "[ 1, 4 ]",
+                                                     "Float32") {}
+};
+
+struct SimpleSubtractionFixtureBroadcast : SubtractionFixture
+{
+    SimpleSubtractionFixtureBroadcast() : SubtractionFixture("[ 1, 4 ]",
+                                                             "[ 1, 1 ]",
+                                                             "[ 1, 4 ]",
+                                                             "Float32") {}
+};
+
+BOOST_FIXTURE_TEST_CASE(SubtractionQuantisedAsymm8, SimpleSubtractionFixture)
+{
+    RunTest<2, armnn::DataType::QuantisedAsymm8>(
+        0,
+        {{"inputLayer1", { 4, 5, 6, 7 }},
+         {"inputLayer2", { 3, 2, 1, 0 }}},
+        {{"outputLayer", { 1, 3, 5, 7 }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(SubtractionFloat32, SimpleSubtractionFixture2)
+{
+    RunTest<2, armnn::DataType::Float32>(
+        0,
+        {{"inputLayer1", { 4, 5, 6, 7 }},
+         {"inputLayer2", { 3, 2, 1, 0 }}},
+        {{"outputLayer", { 1, 3, 5, 7 }}});
+}
+
+BOOST_FIXTURE_TEST_CASE(SubtractionBroadcast, SimpleSubtractionFixtureBroadcast)
+{
+    RunTest<2, armnn::DataType::Float32>(
+        0,
+        {{"inputLayer1", { 4, 5, 6, 7 }},
+         {"inputLayer2", { 2 }}},
+        {{"outputLayer", { 2, 3, 4, 5 }}});
+}
+
+BOOST_AUTO_TEST_SUITE_END()
diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs
index dea5889186..9f1d8ecc9f 100644
--- a/src/armnnSerializer/ArmnnSchema.fbs
+++ b/src/armnnSerializer/ArmnnSchema.fbs
@@ -106,7 +106,8 @@ enum LayerType : uint {
     Floor = 22,
     BatchNormalization = 23,
     Greater = 24,
-    ResizeBilinear = 25
+    ResizeBilinear = 25,
+    Subtraction = 26
 }
 
 // Base layer table to be used as part of other layers
@@ -302,6 +303,10 @@ table SpaceToBatchNdDescriptor {
     dataLayout:DataLayout;
 }
 
+table SubtractionLayer {
+    base:LayerBase;
+}
+
 table BatchToSpaceNdLayer {
     base:LayerBase;
     descriptor:BatchToSpaceNdDescriptor;
@@ -402,7 +407,8 @@ union Layer {
     RsqrtLayer,
     FloorLayer,
     GreaterLayer,
-    ResizeBilinearLayer
+    ResizeBilinearLayer,
+    SubtractionLayer
 }
 
 table AnyLayer {
diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp
index d6df61cbcf..93231d0366 100644
--- a/src/armnnSerializer/Serializer.cpp
+++ b/src/armnnSerializer/Serializer.cpp
@@ -588,6 +588,14 @@ void SerializerVisitor::VisitNormalizationLayer(const armnn::IConnectableLayer*
     CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_NormalizationLayer);
 }
 
+void SerializerVisitor::VisitSubtractionLayer(const armnn::IConnectableLayer* layer, const char* name)
+{
+    auto fbSubtractionBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Subtraction);
+    auto fbSubtractionLayer = serializer::CreateSubtractionLayer(m_flatBufferBuilder, fbSubtractionBaseLayer);
+
+    CreateAnyLayer(fbSubtractionLayer.o, serializer::Layer::Layer_SubtractionLayer);
+}
+
 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 bbc67d49da..b6f5974265 100644
--- a/src/armnnSerializer/Serializer.hpp
+++ b/src/armnnSerializer/Serializer.hpp
@@ -146,6 +146,9 @@ public:
     void VisitNormalizationLayer(const armnn::IConnectableLayer* layer,
                                  const armnn::NormalizationDescriptor& normalizationDescriptor,
                                  const char* name = nullptr) override;
+
+    void VisitSubtractionLayer(const armnn::IConnectableLayer* layer,
+                               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 6071c9c4e8..141a6faa45 100644
--- a/src/armnnSerializer/SerializerSupport.md
+++ b/src/armnnSerializer/SerializerSupport.md
@@ -30,5 +30,6 @@ The Arm NN SDK Serializer currently supports the following layers:
 * Rsqrt
 * Softmax
 * SpaceToBatchNd
+* Subtraction
 
 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 ad6676edc7..572ee80011 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -1250,4 +1250,44 @@ BOOST_AUTO_TEST_CASE(SerializeDeserializeResizeBilinear)
                                             {outputTensorInfo.GetShape()});
 }
 
+BOOST_AUTO_TEST_CASE(SerializeDeserializeSubtraction)
+{
+    class VerifySubtractionName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+    {
+    public:
+        void VisitSubtractionLayer(const armnn::IConnectableLayer*, const char* name) override
+        {
+            BOOST_TEST(name == "subtraction");
+        }
+    };
+
+    const armnn::TensorInfo info = armnn::TensorInfo({ 1, 4 }, armnn::DataType::Float32);
+
+    armnn::INetworkPtr network = armnn::INetwork::Create();
+    armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
+    armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
+    armnn::IConnectableLayer* const subtractionLayer = network->AddSubtractionLayer("subtraction");
+    armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+    inputLayer0->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(0));
+    inputLayer1->GetOutputSlot(0).Connect(subtractionLayer->GetInputSlot(1));
+    subtractionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+    inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+    inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
+    subtractionLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+    armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+    BOOST_CHECK(deserializedNetwork);
+
+    VerifySubtractionName nameChecker;
+    deserializedNetwork->Accept(nameChecker);
+
+    CheckDeserializedNetworkAgainstOriginal(*network,
+                                            *deserializedNetwork,
+                                            {info.GetShape(), info.GetShape()},
+                                            {info.GetShape()},
+                                            {0, 1});
+}
+
 BOOST_AUTO_TEST_SUITE_END()