IVGCVSW-2646 Add Serializer & Deserializer for Conv2D

 * Added Convolution2dLayer to Schema.fbs
 * Added ConstTensorData serialization and deserialization helper functions
 * Added Convolution2d serialization and deserialization support
 * Added serialization and deserialization unit tests

Change-Id: Id376c08410ae01511972a2b0abdce9cfab907462
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>

1 files changed, 81 insertions, 0 deletions

diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index 77bf78683a..31ef0455c3 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -65,6 +65,87 @@ BOOST_AUTO_TEST_CASE(SimpleNetworkSerialization)
     BOOST_TEST(stream.str().length() > 0);
 }
 
+BOOST_AUTO_TEST_CASE(Conv2dSerialization)
+{
+    armnn::IRuntime::CreationOptions options; // default options
+    armnn::IRuntimePtr run = armnn::IRuntime::Create(options);
+
+    armnnDeserializeParser::IDeserializeParserPtr parser = armnnDeserializeParser::IDeserializeParser::Create();
+
+    armnn::TensorInfo inputInfo(armnn::TensorShape({1, 5, 5, 1}), armnn::DataType::Float32, 1.0f, 0);
+    armnn::TensorInfo outputInfo(armnn::TensorShape({1, 3, 3, 1}), armnn::DataType::Float32, 4.0f, 0);
+
+    armnn::TensorInfo weightsInfo(armnn::TensorShape({1, 3, 3, 1}), armnn::DataType::Float32, 2.0f, 0);
+
+    std::vector<float> weightsData({4, 5, 6, 0, 0, 0, 3, 2, 1});
+
+    // Construct network
+    armnn::INetworkPtr network = armnn::INetwork::Create();
+
+    armnn::Convolution2dDescriptor descriptor;
+    descriptor.m_PadLeft = 1;
+    descriptor.m_PadRight = 1;
+    descriptor.m_PadTop = 1;
+    descriptor.m_PadBottom = 1;
+    descriptor.m_StrideX = 2;
+    descriptor.m_StrideY = 2;
+    descriptor.m_BiasEnabled = false;
+    descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+
+    armnn::ConstTensor weights(weightsInfo, weightsData);
+
+    armnn::IConnectableLayer* const inputLayer  = network->AddInputLayer(0, "input");
+    armnn::IConnectableLayer* const convLayer   = network->AddConvolution2dLayer(descriptor, weights, "conv");
+    armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output");
+
+    inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
+    inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+
+    convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+    convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+    armnnSerializer::Serializer serializer;
+    serializer.Serialize(*network);
+
+    std::stringstream stream;
+    serializer.SaveSerializedToStream(stream);
+
+    std::string const serializerString{stream.str()};
+    std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()};
+
+    armnn::INetworkPtr deserializedNetwork = parser->CreateNetworkFromBinary(serializerVector);
+
+    auto deserializedOptimized = Optimize(*deserializedNetwork, {armnn::Compute::CpuRef}, run->GetDeviceSpec());
+
+    armnn::NetworkId networkIdentifier;
+
+    // Load graph into runtime
+    run->LoadNetwork(networkIdentifier, std::move(deserializedOptimized));
+
+    std::vector<float> inputData
+    {
+            1, 5, 2, 3, 5, 8, 7, 3, 6, 3, 3, 3, 9, 1, 9, 4, 1, 8, 1, 3, 6, 8, 1, 9, 2
+    };
+    armnn::InputTensors inputTensors
+    {
+            {0, armnn::ConstTensor(run->GetInputTensorInfo(networkIdentifier, 0), inputData.data())}
+    };
+
+    std::vector<float> expectedOutputData
+    {
+            23, 33, 24, 91, 99, 48, 26, 50, 19
+    };
+
+    std::vector<float> outputData(9);
+    armnn::OutputTensors outputTensors
+    {
+            {0, armnn::Tensor(run->GetOutputTensorInfo(networkIdentifier, 0), outputData.data())}
+    };
+    run->EnqueueWorkload(networkIdentifier, inputTensors, outputTensors);
+    BOOST_CHECK_EQUAL_COLLECTIONS(outputData.begin(), outputData.end(),
+                                  expectedOutputData.begin(), expectedOutputData.end());
+}
+
 BOOST_AUTO_TEST_CASE(SimpleNetworkWithMultiplicationSerialization)
 {
     const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);