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-rw-r--r--src/armnnSerializer/test/SerializerTests.cpp132
1 files changed, 105 insertions, 27 deletions
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index 5b55682dfa..4b6bf1ec53 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -15,12 +15,34 @@
#include <vector>
#include <boost/test/unit_test.hpp>
-
#include <flatbuffers/idl.h>
-BOOST_AUTO_TEST_SUITE(SerializerTests)
+using armnnDeserializeParser::IDeserializeParser;
+
+namespace
+{
+
+armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString)
+{
+ std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()};
+ return armnnDeserializeParser::IDeserializeParser::Create()->CreateNetworkFromBinary(serializerVector);
+}
+
+std::string SerializeNetwork(const armnn::INetwork& network)
+{
+ armnnSerializer::Serializer serializer;
+ serializer.Serialize(network);
-armnnDeserializeParser::IDeserializeParserPtr g_Parser = armnnDeserializeParser::IDeserializeParser::Create();
+ std::stringstream stream;
+ serializer.SaveSerializedToStream(stream);
+
+ std::string serializerString{stream.str()};
+ return serializerString;
+}
+
+} // anonymous namespace
+
+BOOST_AUTO_TEST_SUITE(SerializerTests)
BOOST_AUTO_TEST_CASE(SimpleNetworkSerialization)
{
@@ -78,55 +100,47 @@ BOOST_AUTO_TEST_CASE(SimpleSoftmaxIntegration)
// Create test network
armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer *const softmaxLayer = network->AddSoftmaxLayer(descriptor, "softmax");
- armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, "softmax");
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
softmaxLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
- // Serialize
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- const std::string serializerString{stream.str()};
-
- // Deserialize
- armnn::INetworkPtr deserializedNetwork =
- g_Parser->CreateNetworkFromBinary({serializerString.begin(), serializerString.end()});
+ // Serialize & deserialize network
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
armnn::IRuntime::CreationOptions options;
- armnn::IRuntimePtr run = armnn::IRuntime::Create(options);
+ armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);
armnn::IOptimizedNetworkPtr optimizedNetwork =
- armnn::Optimize(*network, {armnn::Compute::CpuRef}, run->GetDeviceSpec());
+ armnn::Optimize(*network, {armnn::Compute::CpuRef}, runtime->GetDeviceSpec());
BOOST_CHECK(optimizedNetwork);
armnn::IOptimizedNetworkPtr deserializedOptimizedNetwork =
- armnn::Optimize(*deserializedNetwork, {armnn::Compute::CpuRef}, run->GetDeviceSpec());
+ armnn::Optimize(*deserializedNetwork, {armnn::Compute::CpuRef}, runtime->GetDeviceSpec());
BOOST_CHECK(deserializedOptimizedNetwork);
armnn::NetworkId networkId1;
armnn::NetworkId networkId2;
- run->LoadNetwork(networkId1, std::move(optimizedNetwork));
- run->LoadNetwork(networkId2, std::move(deserializedOptimizedNetwork));
+ runtime->LoadNetwork(networkId1, std::move(optimizedNetwork));
+ runtime->LoadNetwork(networkId2, std::move(deserializedOptimizedNetwork));
std::vector<float> inputData(tensorInfo.GetNumElements());
std::iota(inputData.begin(), inputData.end(), 0);
armnn::InputTensors inputTensors1
{
- {0, armnn::ConstTensor(run->GetInputTensorInfo(networkId1, 0), inputData.data())}
+ {0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId1, 0), inputData.data())}
};
armnn::InputTensors inputTensors2
{
- {0, armnn::ConstTensor(run->GetInputTensorInfo(networkId2, 0), inputData.data())}
+ {0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId2, 0), inputData.data())}
};
std::vector<float> outputData1(inputData.size());
@@ -134,19 +148,83 @@ BOOST_AUTO_TEST_CASE(SimpleSoftmaxIntegration)
armnn::OutputTensors outputTensors1
{
- {0, armnn::Tensor(run->GetOutputTensorInfo(networkId1, 0), outputData1.data())}
+ {0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId1, 0), outputData1.data())}
};
armnn::OutputTensors outputTensors2
{
- {0, armnn::Tensor(run->GetOutputTensorInfo(networkId2, 0), outputData2.data())}
+ {0, armnn::Tensor(runtime->GetOutputTensorInfo(networkId2, 0), outputData2.data())}
};
- run->EnqueueWorkload(networkId1, inputTensors1, outputTensors1);
- run->EnqueueWorkload(networkId2, inputTensors2, outputTensors2);
+ runtime->EnqueueWorkload(networkId1, inputTensors1, outputTensors1);
+ runtime->EnqueueWorkload(networkId2, inputTensors2, outputTensors2);
BOOST_CHECK_EQUAL_COLLECTIONS(outputData1.begin(), outputData1.end(),
outputData2.begin(), outputData2.end());
}
+BOOST_AUTO_TEST_CASE(SimplePooling2dIntegration)
+{
+ armnn::NetworkId networkIdentifier;
+ armnn::IRuntime::CreationOptions options; // default options
+ armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);
+
+ unsigned int inputShape[] = {1, 2, 2, 1};
+ unsigned int outputShape[] = {1, 1, 1, 1};
+
+ auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32);
+ auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
+
+ armnn::Pooling2dDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NHWC;
+ desc.m_PadTop = 0;
+ desc.m_PadBottom = 0;
+ desc.m_PadLeft = 0;
+ desc.m_PadRight = 0;
+ desc.m_PoolType = armnn::PoolingAlgorithm::Average;
+ desc.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
+ desc.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ desc.m_PoolHeight = 2;
+ desc.m_PoolWidth = 2;
+ desc.m_StrideX = 2;
+ desc.m_StrideY = 2;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer *const pooling2dLayer = network->AddPooling2dLayer(desc, "ReshapeLayer");
+ armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0));
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+ pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+ pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ auto deserializeNetwork = DeserializeNetwork(SerializeNetwork(*network));
+
+ //Optimize the deserialized network
+ auto deserializedOptimized = Optimize(*deserializeNetwork, {armnn::Compute::CpuRef},
+ runtime->GetDeviceSpec());
+
+ // Load graph into runtime
+ runtime->LoadNetwork(networkIdentifier, std::move(deserializedOptimized));
+
+ std::vector<float> input1Data(inputTensorInfo.GetNumElements());
+ std::iota(input1Data.begin(), input1Data.end(), 4);
+
+ armnn::InputTensors inputTensors
+ {
+ {0, armnn::ConstTensor(runtime->GetInputTensorInfo(networkIdentifier, 0), input1Data.data())}
+ };
+
+ std::vector<float> outputData(input1Data.size());
+ armnn::OutputTensors outputTensors
+ {
+ {0, armnn::Tensor(runtime->GetOutputTensorInfo(networkIdentifier, 0), outputData.data())}
+ };
+
+ runtime->EnqueueWorkload(networkIdentifier, inputTensors, outputTensors);
+
+ BOOST_CHECK_EQUAL(outputData[0], 5.5);
+}
+
BOOST_AUTO_TEST_SUITE_END()
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 02:59:06 +0000