IVGCVSW-2788 Modify Serializer test to use introspection API
Change-Id: Ie97012b42cd7847a437dd9f21c9b59179b2e7897
Signed-off-by: Nattapat Chaimanowong <nattapat.chaimanowong@arm.com>
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp
index d0586c9..ca15553 100644
--- a/src/armnnSerializer/test/SerializerTests.cpp
+++ b/src/armnnSerializer/test/SerializerTests.cpp
@@ -3,25 +3,120 @@
// SPDX-License-Identifier: MIT
//
-#include <armnn/ArmNN.hpp>
-#include <armnn/INetwork.hpp>
-
#include "../Serializer.hpp"
+#include <armnn/ArmNN.hpp>
+#include <armnn/INetwork.hpp>
#include <armnnDeserializer/IDeserializer.hpp>
#include <random>
-#include <sstream>
#include <vector>
#include <boost/test/unit_test.hpp>
-#include <flatbuffers/idl.h>
using armnnDeserializer::IDeserializer;
namespace
{
+struct DefaultLayerVerifierPolicy
+{
+ static void Apply()
+ {
+ BOOST_TEST_MESSAGE("Unexpected layer found in network");
+ BOOST_TEST(false);
+ }
+};
+
+class LayerVerifierBase : public armnn::LayerVisitorBase<DefaultLayerVerifierPolicy>
+{
+public:
+ LayerVerifierBase(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : m_LayerName(layerName)
+ , m_InputTensorInfos(inputInfos)
+ , m_OutputTensorInfos(outputInfos) {}
+
+ void VisitInputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId, const char*) override {}
+
+ void VisitOutputLayer(const armnn::IConnectableLayer*, armnn::LayerBindingId id, const char*) override {}
+
+protected:
+ void VerifyNameAndConnections(const armnn::IConnectableLayer* layer, const char* name)
+ {
+ BOOST_TEST(name == m_LayerName.c_str());
+
+ BOOST_TEST(layer->GetNumInputSlots() == m_InputTensorInfos.size());
+ BOOST_TEST(layer->GetNumOutputSlots() == m_OutputTensorInfos.size());
+
+ for (unsigned int i = 0; i < m_InputTensorInfos.size(); i++)
+ {
+ const armnn::IOutputSlot* connectedOutput = layer->GetInputSlot(i).GetConnection();
+ BOOST_CHECK(connectedOutput);
+
+ const armnn::TensorInfo& connectedInfo = connectedOutput->GetTensorInfo();
+ BOOST_TEST(connectedInfo.GetShape() == m_InputTensorInfos[i].GetShape());
+ BOOST_TEST(
+ GetDataTypeName(connectedInfo.GetDataType()) == GetDataTypeName(m_InputTensorInfos[i].GetDataType()));
+ }
+
+ for (unsigned int i = 0; i < m_OutputTensorInfos.size(); i++)
+ {
+ const armnn::TensorInfo& outputInfo = layer->GetOutputSlot(i).GetTensorInfo();
+ BOOST_TEST(outputInfo.GetShape() == m_OutputTensorInfos[i].GetShape());
+ BOOST_TEST(
+ GetDataTypeName(outputInfo.GetDataType()) == GetDataTypeName(m_OutputTensorInfos[i].GetDataType()));
+ }
+ }
+
+private:
+ std::string m_LayerName;
+ std::vector<armnn::TensorInfo> m_InputTensorInfos;
+ std::vector<armnn::TensorInfo> m_OutputTensorInfos;
+};
+
+template<typename T>
+void CompareConstTensorData(const void* data1, const void* data2, unsigned int numElements)
+{
+ T typedData1 = static_cast<T>(data1);
+ T typedData2 = static_cast<T>(data2);
+ BOOST_CHECK(typedData1);
+ BOOST_CHECK(typedData2);
+
+ for (unsigned int i = 0; i < numElements; i++)
+ {
+ BOOST_TEST(typedData1[i] == typedData2[i]);
+ }
+}
+
+void CompareConstTensor(const armnn::ConstTensor& tensor1, const armnn::ConstTensor& tensor2)
+{
+ BOOST_TEST(tensor1.GetShape() == tensor2.GetShape());
+ BOOST_TEST(GetDataTypeName(tensor1.GetDataType()) == GetDataTypeName(tensor2.GetDataType()));
+
+ switch (tensor1.GetDataType())
+ {
+ case armnn::DataType::Float32:
+ CompareConstTensorData<const float*>(
+ tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements());
+ break;
+ case armnn::DataType::QuantisedAsymm8:
+ case armnn::DataType::Boolean:
+ CompareConstTensorData<const uint8_t*>(
+ tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements());
+ break;
+ case armnn::DataType::Signed32:
+ CompareConstTensorData<const int32_t*>(
+ tensor1.GetMemoryArea(), tensor2.GetMemoryArea(), tensor1.GetNumElements());
+ break;
+ default:
+ // Note that Float16 is not yet implemented
+ BOOST_TEST_MESSAGE("Unexpected datatype");
+ BOOST_TEST(false);
+ }
+}
+
armnn::INetworkPtr DeserializeNetwork(const std::string& serializerString)
{
std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()};
@@ -61,182 +156,238 @@
return randomData;
}
-template<typename T>
-void CheckDeserializedNetworkAgainstOriginal(const armnn::INetwork& deserializedNetwork,
- const armnn::INetwork& originalNetwork,
- const std::vector<armnn::TensorShape>& inputShapes,
- const std::vector<armnn::TensorShape>& outputShapes,
- const std::vector<armnn::LayerBindingId>& inputBindingIds = {0},
- const std::vector<armnn::LayerBindingId>& outputBindingIds = {0})
-{
- BOOST_CHECK(inputShapes.size() == inputBindingIds.size());
- BOOST_CHECK(outputShapes.size() == outputBindingIds.size());
-
- armnn::IRuntime::CreationOptions options;
- armnn::IRuntimePtr runtime = armnn::IRuntime::Create(options);
-
- std::vector<armnn::BackendId> preferredBackends = { armnn::BackendId("CpuRef") };
-
- // Optimize original network
- armnn::IOptimizedNetworkPtr optimizedOriginalNetwork =
- armnn::Optimize(originalNetwork, preferredBackends, runtime->GetDeviceSpec());
- BOOST_CHECK(optimizedOriginalNetwork);
-
- // Optimize deserialized network
- armnn::IOptimizedNetworkPtr optimizedDeserializedNetwork =
- armnn::Optimize(deserializedNetwork, preferredBackends, runtime->GetDeviceSpec());
- BOOST_CHECK(optimizedDeserializedNetwork);
-
- armnn::NetworkId networkId1;
- armnn::NetworkId networkId2;
-
- // Load original and deserialized network
- armnn::Status status1 = runtime->LoadNetwork(networkId1, std::move(optimizedOriginalNetwork));
- BOOST_CHECK(status1 == armnn::Status::Success);
-
- armnn::Status status2 = runtime->LoadNetwork(networkId2, std::move(optimizedDeserializedNetwork));
- BOOST_CHECK(status2 == armnn::Status::Success);
-
- // Generate some input data
- armnn::InputTensors inputTensors1;
- armnn::InputTensors inputTensors2;
- std::vector<std::vector<T>> inputData;
- inputData.reserve(inputShapes.size());
-
- for (unsigned int i = 0; i < inputShapes.size(); i++) {
- inputData.push_back(GenerateRandomData<T>(inputShapes[i].GetNumElements()));
-
- inputTensors1.emplace_back(
- i, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId1, inputBindingIds[i]), inputData[i].data()));
-
- inputTensors2.emplace_back(
- i, armnn::ConstTensor(runtime->GetInputTensorInfo(networkId2, inputBindingIds[i]), inputData[i].data()));
- }
-
- armnn::OutputTensors outputTensors1;
- armnn::OutputTensors outputTensors2;
- std::vector<std::vector<T>> outputData1;
- std::vector<std::vector<T>> outputData2;
- outputData1.reserve(outputShapes.size());
- outputData2.reserve(outputShapes.size());
-
- for (unsigned int i = 0; i < outputShapes.size(); i++)
- {
- outputData1.emplace_back(outputShapes[i].GetNumElements());
- outputData2.emplace_back(outputShapes[i].GetNumElements());
-
- outputTensors1.emplace_back(
- i, armnn::Tensor(runtime->GetOutputTensorInfo(networkId1, outputBindingIds[i]), outputData1[i].data()));
-
- outputTensors2.emplace_back(
- i, armnn::Tensor(runtime->GetOutputTensorInfo(networkId2, outputBindingIds[i]), outputData2[i].data()));
- }
-
- // Run original and deserialized network
- runtime->EnqueueWorkload(networkId1, inputTensors1, outputTensors1);
- runtime->EnqueueWorkload(networkId2, inputTensors2, outputTensors2);
-
- // Compare output data
- for (unsigned int i = 0; i < outputShapes.size(); i++)
- {
- BOOST_CHECK_EQUAL_COLLECTIONS(
- outputData1[i].begin(), outputData1[i].end(), outputData2[i].begin(), outputData2[i].end());
- }
-}
-
} // anonymous namespace
BOOST_AUTO_TEST_SUITE(SerializerTests)
-BOOST_AUTO_TEST_CASE(SerializeDeserializeAddition)
+BOOST_AUTO_TEST_CASE(SerializeAddition)
{
- class VerifyAdditionName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+ class AdditionLayerVerifier : public LayerVerifierBase
{
public:
- void VisitAdditionLayer(const armnn::IConnectableLayer*, const char* name) override
+ AdditionLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name) override
{
- BOOST_TEST(name == "addition");
+ VerifyNameAndConnections(layer, name);
}
};
+ const std::string layerName("addition");
+ const armnn::TensorInfo tensorInfo({1, 2, 3}, 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 additionLayer = network->AddAdditionLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- armnn::IConnectableLayer* const additionLayer = network->AddAdditionLayer("addition");
inputLayer0->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- armnn::TensorShape shape{1U};
- armnn::TensorInfo info(shape, armnn::DataType::Float32);
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
- additionLayer->GetOutputSlot(0).SetTensorInfo(info);
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+ additionLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
- VerifyAdditionName nameChecker;
- deserializedNetwork->Accept(nameChecker);
+ AdditionLayerVerifier verifier(layerName, {tensorInfo, tensorInfo}, {tensorInfo});
+ deserializedNetwork->Accept(verifier);
+}
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
+BOOST_AUTO_TEST_CASE(SerializeBatchNormalization)
+{
+ class BatchNormalizationLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ BatchNormalizationLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::BatchNormalizationDescriptor& descriptor,
+ const armnn::ConstTensor& mean,
+ const armnn::ConstTensor& variance,
+ const armnn::ConstTensor& beta,
+ const armnn::ConstTensor& gamma)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor)
+ , m_Mean(mean)
+ , m_Variance(variance)
+ , m_Beta(beta)
+ , m_Gamma(gamma) {}
+
+ void VisitBatchNormalizationLayer(const armnn::IConnectableLayer* layer,
+ const armnn::BatchNormalizationDescriptor& descriptor,
+ const armnn::ConstTensor& mean,
+ const armnn::ConstTensor& variance,
+ const armnn::ConstTensor& beta,
+ const armnn::ConstTensor& gamma,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+
+ CompareConstTensor(mean, m_Mean);
+ CompareConstTensor(variance, m_Variance);
+ CompareConstTensor(beta, m_Beta);
+ CompareConstTensor(gamma, m_Gamma);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::BatchNormalizationDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_Eps == m_Descriptor.m_Eps);
+ BOOST_TEST(static_cast<int>(descriptor.m_DataLayout) == static_cast<int>(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::BatchNormalizationDescriptor m_Descriptor;
+ armnn::ConstTensor m_Mean;
+ armnn::ConstTensor m_Variance;
+ armnn::ConstTensor m_Beta;
+ armnn::ConstTensor m_Gamma;
+ };
+
+ const std::string layerName("batchNormalization");
+ const armnn::TensorInfo inputInfo ({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+
+ const armnn::TensorInfo meanInfo({1}, armnn::DataType::Float32);
+ const armnn::TensorInfo varianceInfo({1}, armnn::DataType::Float32);
+ const armnn::TensorInfo betaInfo({1}, armnn::DataType::Float32);
+ const armnn::TensorInfo gammaInfo({1}, armnn::DataType::Float32);
+
+ armnn::BatchNormalizationDescriptor descriptor;
+ descriptor.m_Eps = 0.0010000000475f;
+ descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+
+ std::vector<float> meanData({5.0});
+ std::vector<float> varianceData({2.0});
+ std::vector<float> betaData({1.0});
+ std::vector<float> gammaData({0.0});
+
+ armnn::ConstTensor mean(meanInfo, meanData);
+ armnn::ConstTensor variance(varianceInfo, varianceData);
+ armnn::ConstTensor beta(betaInfo, betaData);
+ armnn::ConstTensor gamma(gammaInfo, gammaData);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const batchNormalizationLayer =
+ network->AddBatchNormalizationLayer(descriptor, mean, variance, beta, gamma, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(batchNormalizationLayer->GetInputSlot(0));
+ batchNormalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ batchNormalizationLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ BatchNormalizationLayerVerifier verifier(
+ layerName, {inputInfo}, {outputInfo}, descriptor, mean, variance, beta, gamma);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeBatchToSpaceNd)
+{
+ class BatchToSpaceNdLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ BatchToSpaceNdLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::BatchToSpaceNdDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitBatchToSpaceNdLayer(const armnn::IConnectableLayer* layer,
+ const armnn::BatchToSpaceNdDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::BatchToSpaceNdDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_Crops == m_Descriptor.m_Crops);
+ BOOST_TEST(descriptor.m_BlockShape == m_Descriptor.m_BlockShape);
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::BatchToSpaceNdDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("spaceToBatchNd");
+ const armnn::TensorInfo inputInfo({4, 1, 2, 2}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({1, 1, 4, 4}, armnn::DataType::Float32);
+
+ armnn::BatchToSpaceNdDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NCHW;
+ desc.m_BlockShape = {2, 2};
+ desc.m_Crops = {{0, 0}, {0, 0}};
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const batchToSpaceNdLayer = network->AddBatchToSpaceNdLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(batchToSpaceNdLayer->GetInputSlot(0));
+ batchToSpaceNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ batchToSpaceNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ BatchToSpaceNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
}
BOOST_AUTO_TEST_CASE(SerializeConstant)
{
- armnn::INetworkPtr network = armnn::INetwork::Create();
-
- armnn::ConstTensor inputTensor;
-
- armnn::IConnectableLayer* const inputLayer0 = network->AddConstantLayer(inputTensor, "constant");
- armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0);
-
- inputLayer0->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0));
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find("constant") != stream.str().npos);
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeConstant)
-{
- class VerifyConstantName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+ class ConstantLayerVerifier : public LayerVerifierBase
{
public:
- void VisitConstantLayer(const armnn::IConnectableLayer*, const armnn::ConstTensor&, const char* name) override
+ ConstantLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::ConstTensor& layerInput)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_LayerInput(layerInput) {}
+
+ void VisitConstantLayer(const armnn::IConnectableLayer* layer,
+ const armnn::ConstTensor& input,
+ const char* name) override
{
- BOOST_TEST(name == "constant");
+ VerifyNameAndConnections(layer, name);
+
+ CompareConstTensor(input, m_LayerInput);
}
+
+ void VisitAdditionLayer(const armnn::IConnectableLayer* layer, const char* name = nullptr) override {}
+
+ private:
+ armnn::ConstTensor m_LayerInput;
};
- armnn::TensorInfo commonTensorInfo({ 2, 3 }, armnn::DataType::Float32);
+ const std::string layerName("constant");
+ const armnn::TensorInfo info({ 2, 3 }, armnn::DataType::Float32);
- std::vector<float> constantData = GenerateRandomData<float>(commonTensorInfo.GetNumElements());
- armnn::ConstTensor constTensor(commonTensorInfo, constantData);
+ std::vector<float> constantData = GenerateRandomData<float>(info.GetNumElements());
+ armnn::ConstTensor constTensor(info, constantData);
- // Builds up the structure of the network.
armnn::INetworkPtr network(armnn::INetwork::Create());
-
armnn::IConnectableLayer* input = network->AddInputLayer(0);
- armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, "constant");
+ armnn::IConnectableLayer* constant = network->AddConstantLayer(constTensor, layerName.c_str());
armnn::IConnectableLayer* add = network->AddAdditionLayer();
armnn::IConnectableLayer* output = network->AddOutputLayer(0);
@@ -244,316 +395,81 @@
constant->GetOutputSlot(0).Connect(add->GetInputSlot(1));
add->GetOutputSlot(0).Connect(output->GetInputSlot(0));
- // Sets the tensors in the network.
- input->GetOutputSlot(0).SetTensorInfo(commonTensorInfo);
- constant->GetOutputSlot(0).SetTensorInfo(commonTensorInfo);
- add->GetOutputSlot(0).SetTensorInfo(commonTensorInfo);
+ input->GetOutputSlot(0).SetTensorInfo(info);
+ constant->GetOutputSlot(0).SetTensorInfo(info);
+ add->GetOutputSlot(0).SetTensorInfo(info);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
- VerifyConstantName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {commonTensorInfo.GetShape()},
- {commonTensorInfo.GetShape()});
+ ConstantLayerVerifier verifier(layerName, {}, {info}, constTensor);
+ deserializedNetwork->Accept(verifier);
}
-BOOST_AUTO_TEST_CASE(SerializeDeserializeFloor)
+BOOST_AUTO_TEST_CASE(SerializeConvolution2d)
{
- class VerifyFloorName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+ class Convolution2dLayerVerifier : public LayerVerifierBase
{
public:
- void VisitMultiplicationLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == "floor");
- }
- };
+ Convolution2dLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::Convolution2dDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor)
+ , m_Weight(weight)
+ , m_Bias(bias) {}
- const armnn::TensorInfo info({4,4}, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
-
- const char* floorLayerName = "floor";
-
- armnn::IConnectableLayer* const floorLayer = network->AddFloorLayer(floorLayerName);
- inputLayer->GetOutputSlot(0).Connect(floorLayer->GetInputSlot(0));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- floorLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer->GetOutputSlot(0).SetTensorInfo(info);
- floorLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(floorLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyFloorName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape()},
- {info.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeMinimum)
-{
- class VerifyMinimumName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- explicit VerifyMinimumName(const std::string& expectedMinimumLayerName)
- : m_ExpectedMinimumLayerName(expectedMinimumLayerName) {}
-
- void VisitMinimumLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == m_ExpectedMinimumLayerName.c_str());
- }
-
- private:
- std::string m_ExpectedMinimumLayerName;
- };
-
- const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
-
- const std::string minimumLayerName("minimum");
-
- armnn::IConnectableLayer* const minimumLayer = network->AddMinimumLayer(minimumLayerName.c_str());
- inputLayer0->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(1));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- minimumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
- minimumLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(minimumLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyMinimumName nameChecker(minimumLayerName);
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeMaximum)
-{
- class VerifyMaximumName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- explicit VerifyMaximumName(const std::string& expectedMaximumLayerName)
- : m_ExpectedMaximumLayerName(expectedMaximumLayerName) {}
-
- void VisitMaximumLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == m_ExpectedMaximumLayerName.c_str());
- }
-
- private:
- std::string m_ExpectedMaximumLayerName;
- };
-
- const armnn::TensorInfo info({ 1, 2, 2, 3 }, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
-
- const std::string maximumLayerName("maximum");
-
- armnn::IConnectableLayer* const maximumLayer = network->AddMaximumLayer(maximumLayerName.c_str());
- inputLayer0->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(1));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- maximumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
- maximumLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(maximumLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyMaximumName nameChecker(maximumLayerName);
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeL2Normalization)
-{
- class VerifyL2NormalizationName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- explicit VerifyL2NormalizationName(const std::string& expectedL2NormalizationLayerName)
- : m_ExpectedL2NormalizationLayerName(expectedL2NormalizationLayerName) {}
-
- void VisitL2NormalizationLayer(const armnn::IConnectableLayer*,
- const armnn::L2NormalizationDescriptor&,
- const char* name) override
- {
- BOOST_TEST(name == m_ExpectedL2NormalizationLayerName.c_str());
- }
- private:
- std::string m_ExpectedL2NormalizationLayerName;
- };
-
- const armnn::TensorInfo info({ 1, 2, 1, 5 }, armnn::DataType::Float32);
-
- armnn::L2NormalizationDescriptor desc;
- desc.m_DataLayout = armnn::DataLayout::NCHW;
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
-
- const char* l2NormLayerName = "l2Normalization";
-
- armnn::IConnectableLayer* const l2NormLayer = network->AddL2NormalizationLayer(desc, l2NormLayerName);
- inputLayer0->GetOutputSlot(0).Connect(l2NormLayer->GetInputSlot(0));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- l2NormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- l2NormLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(l2NormLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyL2NormalizationName nameChecker(l2NormLayerName);
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- { info.GetShape() },
- { info.GetShape() });
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeMultiplication)
-{
- class VerifyMultiplicationName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitMultiplicationLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == "multiplication");
- }
- };
-
- const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
-
- const char* multLayerName = "multiplication";
-
- armnn::IConnectableLayer* const multiplicationLayer = network->AddMultiplicationLayer(multLayerName);
- inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
- multiplicationLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(multLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyMultiplicationName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeConvolution2d)
-{
-
- class VerifyConvolution2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitConvolution2dLayer(const armnn::IConnectableLayer*,
- const armnn::Convolution2dDescriptor&,
- const armnn::ConstTensor&,
- const armnn::Optional<armnn::ConstTensor>&,
+ void VisitConvolution2dLayer(const armnn::IConnectableLayer* layer,
+ const armnn::Convolution2dDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias,
const char* name) override
{
- BOOST_TEST(name == "convolution");
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+
+ CompareConstTensor(weight, m_Weight);
+
+ BOOST_TEST(bias.has_value() == m_Bias.has_value());
+ if (bias.has_value() && m_Bias.has_value())
+ {
+ CompareConstTensor(bias.value(), m_Bias.value());
+ }
}
+
+ private:
+ void VerifyDescriptor(const armnn::Convolution2dDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_PadLeft == m_Descriptor.m_PadLeft);
+ BOOST_TEST(descriptor.m_PadRight == m_Descriptor.m_PadRight);
+ BOOST_TEST(descriptor.m_PadTop == m_Descriptor.m_PadTop);
+ BOOST_TEST(descriptor.m_PadBottom == m_Descriptor.m_PadBottom);
+ BOOST_TEST(descriptor.m_StrideX == m_Descriptor.m_StrideX);
+ BOOST_TEST(descriptor.m_StrideY == m_Descriptor.m_StrideY);
+ BOOST_TEST(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled);
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::Convolution2dDescriptor m_Descriptor;
+ armnn::ConstTensor m_Weight;
+ armnn::Optional<armnn::ConstTensor> m_Bias;
};
- armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
- armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+ const std::string layerName("convolution2d");
+ const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
- armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
- armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32);
- // Construct network
- armnn::INetworkPtr network = armnn::INetwork::Create();
+ std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
+ armnn::ConstTensor weights(weightsInfo, weightsData);
+
+ std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
+ armnn::ConstTensor biases(biasesInfo, biasesData);
armnn::Convolution2dDescriptor descriptor;
descriptor.m_PadLeft = 1;
@@ -565,145 +481,83 @@
descriptor.m_BiasEnabled = true;
descriptor.m_DataLayout = armnn::DataLayout::NHWC;
- std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
- armnn::ConstTensor weights(weightsInfo, weightsData);
-
- std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
- armnn::ConstTensor biases(biasesInfo, biasesData);
-
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0, "input");
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
armnn::IConnectableLayer* const convLayer =
- network->AddConvolution2dLayer(descriptor, weights, biases, "convolution");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output");
+ network->AddConvolution2dLayer(descriptor, weights, biases, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-
convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
- VerifyConvolution2dName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputInfo.GetShape()},
- {outputInfo.GetShape()});
+ Convolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
+ deserializedNetwork->Accept(verifier);
}
-BOOST_AUTO_TEST_CASE(SerializeDeserializeGreater)
+BOOST_AUTO_TEST_CASE(SerializeDepthwiseConvolution2d)
{
- class VerifyGreaterName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+ class DepthwiseConvolution2dLayerVerifier : public LayerVerifierBase
{
public:
- void VisitGreaterLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == "greater");
- }
- };
+ DepthwiseConvolution2dLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::DepthwiseConvolution2dDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor)
+ , m_Weight(weight)
+ , m_Bias(bias) {}
- const armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::DataType::Float32);
- const armnn::TensorInfo inputTensorInfo2({ 1, 2, 2, 2 }, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 2 }, armnn::DataType::Boolean);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1);
- armnn::IConnectableLayer* const greaterLayer = network->AddGreaterLayer("greater");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer1->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1);
- inputLayer2->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(1));
- inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2);
- greaterLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- greaterLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyGreaterName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()},
- {outputTensorInfo.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeReshape)
-{
- class VerifyReshapeName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitReshapeLayer(const armnn::IConnectableLayer*, const armnn::ReshapeDescriptor&, const char* name)
- {
- BOOST_TEST(name == "reshape");
- }
- };
-
- unsigned int inputShape[] = { 1, 9 };
- unsigned int outputShape[] = { 3, 3 };
-
- auto inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::DataType::Float32);
- auto outputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::DataType::Float32);
- auto reshapeOutputTensorInfo = armnn::TensorInfo(2, outputShape, armnn::DataType::Float32);
-
- armnn::ReshapeDescriptor reshapeDescriptor;
- reshapeDescriptor.m_TargetShape = reshapeOutputTensorInfo.GetShape();
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const reshapeLayer = network->AddReshapeLayer(reshapeDescriptor, "reshape");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(reshapeLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- reshapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyReshapeName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeDepthwiseConvolution2d)
-{
- class VerifyDepthwiseConvolution2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer*,
- const armnn::DepthwiseConvolution2dDescriptor&,
- const armnn::ConstTensor&,
- const armnn::Optional<armnn::ConstTensor>&,
+ void VisitDepthwiseConvolution2dLayer(const armnn::IConnectableLayer* layer,
+ const armnn::DepthwiseConvolution2dDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias,
const char* name) override
{
- BOOST_TEST(name == "depthwise_convolution");
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+
+ CompareConstTensor(weight, m_Weight);
+
+ BOOST_TEST(bias.has_value() == m_Bias.has_value());
+ if (bias.has_value() && m_Bias.has_value())
+ {
+ CompareConstTensor(bias.value(), m_Bias.value());
+ }
}
+
+ private:
+ void VerifyDescriptor(const armnn::DepthwiseConvolution2dDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_PadLeft == m_Descriptor.m_PadLeft);
+ BOOST_TEST(descriptor.m_PadRight == m_Descriptor.m_PadRight);
+ BOOST_TEST(descriptor.m_PadTop == m_Descriptor.m_PadTop);
+ BOOST_TEST(descriptor.m_PadBottom == m_Descriptor.m_PadBottom);
+ BOOST_TEST(descriptor.m_StrideX == m_Descriptor.m_StrideX);
+ BOOST_TEST(descriptor.m_StrideY == m_Descriptor.m_StrideY);
+ BOOST_TEST(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled);
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::DepthwiseConvolution2dDescriptor m_Descriptor;
+ armnn::ConstTensor m_Weight;
+ armnn::Optional<armnn::ConstTensor> m_Bias;
};
- armnn::TensorInfo inputInfo ({ 1, 5, 5, 3 }, armnn::DataType::Float32);
- armnn::TensorInfo outputInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32);
+ const std::string layerName("depwiseConvolution2d");
+ const armnn::TensorInfo inputInfo ({ 1, 5, 5, 3 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32);
- armnn::TensorInfo weightsInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32);
- armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32);
-
- armnn::DepthwiseConvolution2dDescriptor descriptor;
- descriptor.m_StrideX = 1;
- descriptor.m_StrideY = 1;
- descriptor.m_BiasEnabled = true;
- descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+ const armnn::TensorInfo weightsInfo({ 1, 3, 3, 3 }, armnn::DataType::Float32);
+ const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32);
std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
armnn::ConstTensor weights(weightsInfo, weightsData);
@@ -711,928 +565,102 @@
std::vector<int32_t> biasesData = GenerateRandomData<int32_t>(biasesInfo.GetNumElements());
armnn::ConstTensor biases(biasesInfo, biasesData);
+ armnn::DepthwiseConvolution2dDescriptor descriptor;
+ descriptor.m_StrideX = 1;
+ descriptor.m_StrideY = 1;
+ descriptor.m_BiasEnabled = true;
+ descriptor.m_DataLayout = armnn::DataLayout::NHWC;
+
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
armnn::IConnectableLayer* const depthwiseConvLayer =
- network->AddDepthwiseConvolution2dLayer(descriptor, weights, biases, "depthwise_convolution");
+ network->AddDepthwiseConvolution2dLayer(descriptor, weights, biases, layerName.c_str());
armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
depthwiseConvLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
- VerifyDepthwiseConvolution2dName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputInfo.GetShape()},
- {outputInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeSoftmax)
-{
- class VerifySoftmaxName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitSoftmaxLayer(const armnn::IConnectableLayer*, const armnn::SoftmaxDescriptor&, const char* name)
- {
- BOOST_TEST(name == "softmax");
- }
- };
-
- armnn::TensorInfo tensorInfo({1, 10}, armnn::DataType::Float32);
-
- armnn::SoftmaxDescriptor descriptor;
- descriptor.m_Beta = 1.0f;
-
- 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);
-
- inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
- softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- softmaxLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifySoftmaxName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {tensorInfo.GetShape()},
- {tensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializePooling2d)
-{
- class VerifyPooling2dName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- void VisitPooling2dLayer(const armnn::IConnectableLayer*, const armnn::Pooling2dDescriptor&, const char* name)
- {
- BOOST_TEST(name == "pooling2d");
- }
- };
-
- unsigned int inputShape[] = {1, 2, 2, 1};
- unsigned int outputShape[] = {1, 1, 1, 1};
-
- auto inputInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32);
- auto outputInfo = 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, "pooling2d");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
- pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyPooling2dName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputInfo.GetShape()},
- {outputInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializePermute)
-{
- class VerifyPermuteName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitPermuteLayer(const armnn::IConnectableLayer*, const armnn::PermuteDescriptor&, const char* name)
- {
- BOOST_TEST(name == "permute");
- }
- };
-
- unsigned int inputShape[] = { 4, 3, 2, 1 };
- unsigned int outputShape[] = { 1, 2, 3, 4 };
- unsigned int dimsMapping[] = { 3, 2, 1, 0 };
-
- auto inputTensorInfo = armnn::TensorInfo(4, inputShape, armnn::DataType::Float32);
- auto outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
-
- armnn::PermuteDescriptor permuteDescriptor(armnn::PermutationVector(dimsMapping, 4));
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const permuteLayer = network->AddPermuteLayer(permuteDescriptor, "permute");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- permuteLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- permuteLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyPermuteName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeFullyConnected)
-{
- class VerifyFullyConnectedName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitFullyConnectedLayer(const armnn::IConnectableLayer*,
- const armnn::FullyConnectedDescriptor&,
- const armnn::ConstTensor&,
- const armnn::Optional<armnn::ConstTensor>&,
- const char* name) override
- {
- BOOST_TEST(name == "fully_connected");
- }
- };
-
- armnn::TensorInfo inputInfo ({ 2, 5, 1, 1 }, armnn::DataType::Float32);
- armnn::TensorInfo outputInfo({ 2, 3 }, armnn::DataType::Float32);
-
- armnn::TensorInfo weightsInfo({ 5, 3 }, armnn::DataType::Float32);
- armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32);
-
- armnn::FullyConnectedDescriptor descriptor;
- descriptor.m_BiasEnabled = true;
- descriptor.m_TransposeWeightMatrix = false;
-
- std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
- std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
-
- armnn::ConstTensor weights(weightsInfo, weightsData);
- armnn::ConstTensor biases(biasesInfo, biasesData);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0, "input");
- armnn::IConnectableLayer* const fullyConnectedLayer = network->AddFullyConnectedLayer(descriptor,
- weights,
- biases,
- "fully_connected");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output");
-
- inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-
- fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyFullyConnectedName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputInfo.GetShape()},
- {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<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeGather)
-{
- class VerifyGatherName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VerifyGatherLayer(const armnn::IConnectableLayer *, const char *name)
- {
- BOOST_TEST(name == "gatherLayer");
- }
- };
-
- armnn::TensorInfo paramsInfo({ 8 }, armnn::DataType::QuantisedAsymm8);
- armnn::TensorInfo indicesInfo({ 3 }, armnn::DataType::Signed32);
- armnn::TensorInfo outputInfo({ 3 }, armnn::DataType::QuantisedAsymm8);
-
- paramsInfo.SetQuantizationScale(1.0f);
- paramsInfo.SetQuantizationOffset(0);
- outputInfo.SetQuantizationScale(1.0f);
- outputInfo.SetQuantizationOffset(0);
-
- const std::vector<int32_t>& indicesData = {7, 6, 5};
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer *const constantLayer =
- network->AddConstantLayer(armnn::ConstTensor(indicesInfo, indicesData));
- armnn::IConnectableLayer *const gatherLayer = network->AddGatherLayer("gatherLayer");
- armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(paramsInfo);
- constantLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(1));
- constantLayer->GetOutputSlot(0).SetTensorInfo(indicesInfo);
- gatherLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- gatherLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyGatherName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<uint8_t>(*deserializedNetwork,
- *network,
- {paramsInfo.GetShape()},
- {outputInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeBatchNormalization)
-{
- class VerifyBatchNormalizationName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitBatchNormalizationLayer(const armnn::IConnectableLayer*,
- const armnn::BatchNormalizationDescriptor&,
- const armnn::ConstTensor&,
- const armnn::ConstTensor&,
- const armnn::ConstTensor&,
- const armnn::ConstTensor&,
- const char* name) override
- {
- BOOST_TEST(name == "BatchNormalizationLayer");
- }
- };
-
- armnn::TensorInfo inputInfo ({ 1, 3, 3, 1 }, armnn::DataType::Float32);
- armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32);
-
- armnn::TensorInfo meanInfo({1}, armnn::DataType::Float32);
- armnn::TensorInfo varianceInfo({1}, armnn::DataType::Float32);
- armnn::TensorInfo scaleInfo({1}, armnn::DataType::Float32);
- armnn::TensorInfo offsetInfo({1}, armnn::DataType::Float32);
-
- armnn::BatchNormalizationDescriptor descriptor;
- descriptor.m_Eps = 0.0010000000475f;
- descriptor.m_DataLayout = armnn::DataLayout::NHWC;
-
- std::vector<float> meanData({5.0});
- std::vector<float> varianceData({2.0});
- std::vector<float> scaleData({1.0});
- std::vector<float> offsetData({0.0});
-
- armnn::ConstTensor mean(meanInfo, meanData);
- armnn::ConstTensor variance(varianceInfo, varianceData);
- armnn::ConstTensor scale(scaleInfo, scaleData);
- armnn::ConstTensor offset(offsetInfo, offsetData);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const batchNormalizationLayer = network->AddBatchNormalizationLayer(
- descriptor,
- mean,
- variance,
- scale,
- offset,
- "BatchNormalizationLayer");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(batchNormalizationLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
-
- batchNormalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- batchNormalizationLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyBatchNormalizationName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputInfo.GetShape()},
- {outputInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeDivision)
-{
- class VerifyDivisionName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitDivisionLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == "division");
- }
- };
-
- const armnn::TensorInfo info({ 1, 5, 2, 3 }, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(1);
-
- const char* divLayerName = "division";
-
- armnn::IConnectableLayer* const divisionLayer = network->AddDivisionLayer(divLayerName);
- inputLayer0->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(1));
-
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
- divisionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
- inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
- divisionLayer->GetOutputSlot(0).SetTensorInfo(info);
-
- armnnSerializer::Serializer serializer;
- serializer.Serialize(*network);
-
- std::stringstream stream;
- serializer.SaveSerializedToStream(stream);
- BOOST_TEST(stream.str().length() > 0);
- BOOST_TEST(stream.str().find(divLayerName) != stream.str().npos);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(stream.str());
- BOOST_CHECK(deserializedNetwork);
-
- VerifyDivisionName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeNormalization)
-{
- class VerifyNormalizationName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitNormalizationLayer(const armnn::IConnectableLayer*,
- const armnn::NormalizationDescriptor& normalizationDescriptor,
- const char* name) override
- {
- BOOST_TEST(name == "NormalizationLayer");
- }
- };
-
- unsigned int inputShape[] = {2, 1, 2, 2};
- unsigned int outputShape[] = {2, 1, 2, 2};
-
- armnn::NormalizationDescriptor desc;
- desc.m_DataLayout = armnn::DataLayout::NCHW;
- desc.m_NormSize = 3;
- desc.m_Alpha = 1;
- desc.m_Beta = 1;
- desc.m_K = 1;
-
- 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 normalizationLayer = network->AddNormalizationLayer(desc, "NormalizationLayer");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(normalizationLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- normalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- normalizationLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyNormalizationName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeEqual)
-{
- class VerifyEqualName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitEqualLayer(const armnn::IConnectableLayer*,
- const char* name) override
- {
- BOOST_TEST(name == "EqualLayer");
- }
- };
-
- const armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32);
- const armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Boolean);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0);
- armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1);
- armnn::IConnectableLayer* const equalLayer = network->AddEqualLayer("EqualLayer");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer1->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(0));
- inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1);
- inputLayer2->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(1));
- inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2);
- equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- equalLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyEqualName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()},
- {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<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeRsqrt)
-{
- class VerifyRsqrtName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitRsqrtLayer(const armnn::IConnectableLayer*, const char* name) override
- {
- BOOST_TEST(name == "rsqrt");
- }
- };
-
- const armnn::TensorInfo tensorInfo({ 3, 1, 2 }, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const rsqrtLayer = network->AddRsqrtLayer("rsqrt");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(rsqrtLayer->GetInputSlot(0));
- rsqrtLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
- rsqrtLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyRsqrtName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {tensorInfo.GetShape()},
- {tensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeResizeBilinear)
-{
- class VerifyResizeBilinearName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitResizeBilinearLayer(const armnn::IConnectableLayer*,
- const armnn::ResizeBilinearDescriptor& descriptor,
- const char* name) override
- {
- BOOST_TEST(name == "ResizeBilinearLayer");
- }
- };
-
- armnn::ResizeBilinearDescriptor desc;
- desc.m_TargetWidth = 4;
- desc.m_TargetHeight = 2;
-
- const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const resizeLayer = network->AddResizeBilinearLayer(desc, "ResizeBilinearLayer");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(resizeLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- resizeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyResizeBilinearName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {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<float>(*deserializedNetwork,
- *network,
- {info.GetShape(), info.GetShape()},
- {info.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeStridedSlice)
-{
- class VerifyStridedSliceName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitStridedSliceLayer(const armnn::IConnectableLayer*,
- const armnn::StridedSliceDescriptor& descriptor,
- const char* name) override
- {
- BOOST_TEST(name == "StridedSliceLayer");
- }
- };
-
- armnn::StridedSliceDescriptor desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1});
- desc.m_EndMask = (1 << 4) - 1;
- desc.m_ShrinkAxisMask = (1 << 1) | (1 << 2);
- desc.m_DataLayout = armnn::DataLayout::NCHW;
-
- const armnn::TensorInfo inputTensorInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({3, 1}, armnn::DataType::Float32);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const stridedSliceLayer = network->AddStridedSliceLayer(desc, "StridedSliceLayer");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(stridedSliceLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- stridedSliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- stridedSliceLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyStridedSliceName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeMean)
-{
- class VerifyMeanName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitMeanLayer(const armnn::IConnectableLayer*, const armnn::MeanDescriptor&, const char* name)
- {
- BOOST_TEST(name == "mean");
- }
- };
-
- armnn::TensorInfo inputTensorInfo({1, 1, 3, 2}, armnn::DataType::Float32);
- armnn::TensorInfo outputTensorInfo({1, 1, 1, 2}, armnn::DataType::Float32);
-
- armnn::MeanDescriptor descriptor;
- descriptor.m_Axis = { 2 };
- descriptor.m_KeepDims = true;
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const meanLayer = network->AddMeanLayer(descriptor, "mean");
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayer->GetOutputSlot(0).Connect(meanLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- meanLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
- meanLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyMeanName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeMerger)
-{
- class VerifyMergerName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitMergerLayer(const armnn::IConnectableLayer* layer,
- const armnn::OriginsDescriptor& mergerDescriptor,
- const char* name = nullptr) override
- {
- BOOST_TEST(name == "MergerLayer");
- }
- };
-
- unsigned int inputShapeOne[] = {2, 3, 2, 2};
- unsigned int inputShapeTwo[] = {2, 3, 2, 2};
- unsigned int outputShape[] = {4, 3, 2, 2};
-
- const armnn::TensorInfo inputOneTensorInfo = armnn::TensorInfo(4, inputShapeOne, armnn::DataType::Float32);
- const armnn::TensorInfo inputTwoTensorInfo = armnn::TensorInfo(4, inputShapeTwo, armnn::DataType::Float32);
- const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32);
-
- std::vector<armnn::TensorShape> shapes;
- shapes.push_back(inputOneTensorInfo.GetShape());
- shapes.push_back(inputTwoTensorInfo.GetShape());
-
- armnn::MergerDescriptor descriptor =
- armnn::CreateMergerDescriptorForConcatenation(shapes.begin(), shapes.end(), 0);
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0);
- inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputOneTensorInfo);
- armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1);
- inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputTwoTensorInfo);
- armnn::IConnectableLayer* const mergerLayer = network->AddMergerLayer(descriptor, "MergerLayer");
- mergerLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
- armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
-
- inputLayerOne->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(0));
- inputLayerTwo->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(1));
- mergerLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifyMergerName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputOneTensorInfo.GetShape(), inputTwoTensorInfo.GetShape()},
- {outputTensorInfo.GetShape()},
- {0, 1});
-}
-
-BOOST_AUTO_TEST_CASE(SerializeDeserializeSplitter)
-{
- class VerifySplitterName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
- {
- public:
- void VisitSplitterLayer(const armnn::IConnectableLayer*,
- const armnn::ViewsDescriptor& viewsDescriptor,
- const char* name) override
- {
- BOOST_TEST(name == "splitter");
- }
- };
-
- unsigned int numViews = 3;
- unsigned int numDimensions = 4;
- unsigned int inputShape[] = {1,18, 4, 4};
- unsigned int outputShape[] = {1, 6, 4, 4};
-
- auto inputTensorInfo = armnn::TensorInfo(numDimensions, inputShape, armnn::DataType::Float32);
- auto outputTensorInfo = armnn::TensorInfo(numDimensions, outputShape, armnn::DataType::Float32);
-
- // This is modelled on how the caffe parser sets up a splitter layer to partition an input
- // along dimension one.
- unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape[0]),
- static_cast<unsigned int>(inputShape[1]),
- static_cast<unsigned int>(inputShape[2]),
- static_cast<unsigned int>(inputShape[3])};
- splitterDimSizes[1] /= numViews;
- armnn::ViewsDescriptor desc(numViews, numDimensions);
-
- for (unsigned int g = 0; g < numViews; ++g)
- {
- desc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g);
-
- // Set the size of the views.
- for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++)
- {
- desc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
- }
- }
-
- const char* splitterLayerName = "splitter";
-
- armnn::INetworkPtr network = armnn::INetwork::Create();
- armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
- armnn::IConnectableLayer* const splitterLayer = network->AddSplitterLayer(desc, splitterLayerName);
- armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0);
- armnn::IConnectableLayer* const outputLayer1 = network->AddOutputLayer(1);
- armnn::IConnectableLayer* const outputLayer2 = network->AddOutputLayer(2);
-
- inputLayer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0));
- inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
- splitterLayer->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0));
- splitterLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
- splitterLayer->GetOutputSlot(1).Connect(outputLayer1->GetInputSlot(0));
- splitterLayer->GetOutputSlot(1).SetTensorInfo(outputTensorInfo);
- splitterLayer->GetOutputSlot(2).Connect(outputLayer2->GetInputSlot(0));
- splitterLayer->GetOutputSlot(2).SetTensorInfo(outputTensorInfo);
-
- armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
- BOOST_CHECK(deserializedNetwork);
-
- VerifySplitterName nameChecker;
- deserializedNetwork->Accept(nameChecker);
-
- CheckDeserializedNetworkAgainstOriginal<float>(*deserializedNetwork,
- *network,
- {inputTensorInfo.GetShape()},
- {outputTensorInfo.GetShape(),
- outputTensorInfo.GetShape(),
- outputTensorInfo.GetShape()},
- {0},
- {0, 1, 2});
+ DepthwiseConvolution2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
+ deserializedNetwork->Accept(verifier);
}
BOOST_AUTO_TEST_CASE(SerializeDeserializeDetectionPostProcess)
{
- class VerifyDetectionPostProcessName : public armnn::LayerVisitorBase<armnn::VisitorNoThrowPolicy>
+ class DetectionPostProcessLayerVerifier : public LayerVerifierBase
{
public:
+ DetectionPostProcessLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::DetectionPostProcessDescriptor& descriptor,
+ const armnn::ConstTensor& anchors)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor)
+ , m_Anchors(anchors) {}
+
void VisitDetectionPostProcessLayer(const armnn::IConnectableLayer* layer,
const armnn::DetectionPostProcessDescriptor& descriptor,
const armnn::ConstTensor& anchors,
const char* name) override
{
- BOOST_TEST(name == "DetectionPostProcessLayer");
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+
+ CompareConstTensor(anchors, m_Anchors);
}
+
+ private:
+ void VerifyDescriptor(const armnn::DetectionPostProcessDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_UseRegularNms == m_Descriptor.m_UseRegularNms);
+ BOOST_TEST(descriptor.m_MaxDetections == m_Descriptor.m_MaxDetections);
+ BOOST_TEST(descriptor.m_MaxClassesPerDetection == m_Descriptor.m_MaxClassesPerDetection);
+ BOOST_TEST(descriptor.m_DetectionsPerClass == m_Descriptor.m_DetectionsPerClass);
+ BOOST_TEST(descriptor.m_NmsScoreThreshold == m_Descriptor.m_NmsScoreThreshold);
+ BOOST_TEST(descriptor.m_NmsIouThreshold == m_Descriptor.m_NmsIouThreshold);
+ BOOST_TEST(descriptor.m_NumClasses == m_Descriptor.m_NumClasses);
+ BOOST_TEST(descriptor.m_ScaleY == m_Descriptor.m_ScaleY);
+ BOOST_TEST(descriptor.m_ScaleX == m_Descriptor.m_ScaleX);
+ BOOST_TEST(descriptor.m_ScaleH == m_Descriptor.m_ScaleH);
+ BOOST_TEST(descriptor.m_ScaleW == m_Descriptor.m_ScaleW);
+ }
+
+ armnn::DetectionPostProcessDescriptor m_Descriptor;
+ armnn::ConstTensor m_Anchors;
};
- const armnn::TensorInfo inputInfos[] = {
+ const std::string layerName("detectionPostProcess");
+
+ const std::vector<armnn::TensorInfo> inputInfos({
armnn::TensorInfo({ 1, 6, 4 }, armnn::DataType::Float32),
armnn::TensorInfo({ 1, 6, 3}, armnn::DataType::Float32)
- };
+ });
- const armnn::TensorInfo outputInfos[] = {
+ const std::vector<armnn::TensorInfo> outputInfos({
armnn::TensorInfo({ 1, 3, 4 }, armnn::DataType::Float32),
armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32),
armnn::TensorInfo({ 1, 3 }, armnn::DataType::Float32),
armnn::TensorInfo({ 1 }, armnn::DataType::Float32)
- };
+ });
- armnn::DetectionPostProcessDescriptor desc;
- desc.m_UseRegularNms = true;
- desc.m_MaxDetections = 3;
- desc.m_MaxClassesPerDetection = 1;
- desc.m_DetectionsPerClass =1;
- desc.m_NmsScoreThreshold = 0.0;
- desc.m_NmsIouThreshold = 0.5;
- desc.m_NumClasses = 2;
- desc.m_ScaleY = 10.0;
- desc.m_ScaleX = 10.0;
- desc.m_ScaleH = 5.0;
- desc.m_ScaleW = 5.0;
+ armnn::DetectionPostProcessDescriptor descriptor;
+ descriptor.m_UseRegularNms = true;
+ descriptor.m_MaxDetections = 3;
+ descriptor.m_MaxClassesPerDetection = 1;
+ descriptor.m_DetectionsPerClass =1;
+ descriptor.m_NmsScoreThreshold = 0.0;
+ descriptor.m_NmsIouThreshold = 0.5;
+ descriptor.m_NumClasses = 2;
+ descriptor.m_ScaleY = 10.0;
+ descriptor.m_ScaleX = 10.0;
+ descriptor.m_ScaleH = 5.0;
+ descriptor.m_ScaleW = 5.0;
const armnn::TensorInfo anchorsInfo({ 6, 4 }, armnn::DataType::Float32);
const std::vector<float> anchorsData({
@@ -1646,9 +674,8 @@
armnn::ConstTensor anchors(anchorsInfo, anchorsData);
armnn::INetworkPtr network = armnn::INetwork::Create();
-
armnn::IConnectableLayer* const detectionLayer =
- network->AddDetectionPostProcessLayer(desc, anchors, "DetectionPostProcessLayer");
+ network->AddDetectionPostProcessLayer(descriptor, anchors, layerName.c_str());
for (unsigned int i = 0; i < 2; i++)
{
@@ -1667,16 +694,1303 @@
armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
BOOST_CHECK(deserializedNetwork);
- VerifyDetectionPostProcessName nameChecker;
- deserializedNetwork->Accept(nameChecker);
+ DetectionPostProcessLayerVerifier verifier(layerName, inputInfos, outputInfos, descriptor, anchors);
+ deserializedNetwork->Accept(verifier);
+}
- CheckDeserializedNetworkAgainstOriginal<float>(
- *network,
- *deserializedNetwork,
- {inputInfos[0].GetShape(), inputInfos[1].GetShape()},
- {outputInfos[0].GetShape(), outputInfos[1].GetShape(), outputInfos[2].GetShape(), outputInfos[3].GetShape()},
- {0, 1},
- {0, 1, 2, 3});
+BOOST_AUTO_TEST_CASE(SerializeDivision)
+{
+ class DivisionLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ DivisionLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitDivisionLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("division");
+ const armnn::TensorInfo info({ 1, 5, 2, 3 }, 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 divisionLayer = network->AddDivisionLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer0->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(0));
+ inputLayer1->GetOutputSlot(0).Connect(divisionLayer->GetInputSlot(1));
+ divisionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
+ divisionLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ DivisionLayerVerifier verifier(layerName, {info, info}, {info});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeEqual)
+{
+ class EqualLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ EqualLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitEqualLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("equal");
+ const armnn::TensorInfo inputTensorInfo1 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32);
+ const armnn::TensorInfo inputTensorInfo2 = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputTensorInfo = armnn::TensorInfo({2, 1, 2, 4}, armnn::DataType::Boolean);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1);
+ armnn::IConnectableLayer* const equalLayer = network->AddEqualLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer1->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(0));
+ inputLayer2->GetOutputSlot(0).Connect(equalLayer->GetInputSlot(1));
+ equalLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1);
+ inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2);
+ equalLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ EqualLayerVerifier verifier(layerName, {inputTensorInfo1, inputTensorInfo2}, {outputTensorInfo});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeFloor)
+{
+ class FloorLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ FloorLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitFloorLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("floor");
+ const armnn::TensorInfo info({4,4}, armnn::DataType::Float32);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const floorLayer = network->AddFloorLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(floorLayer->GetInputSlot(0));
+ floorLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(info);
+ floorLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ FloorLayerVerifier verifier(layerName, {info}, {info});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeFullyConnected)
+{
+ class FullyConnectedLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ FullyConnectedLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::FullyConnectedDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor)
+ , m_Weight(weight)
+ , m_Bias(bias) {}
+
+ void VisitFullyConnectedLayer(const armnn::IConnectableLayer* layer,
+ const armnn::FullyConnectedDescriptor& descriptor,
+ const armnn::ConstTensor& weight,
+ const armnn::Optional<armnn::ConstTensor>& bias,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+
+ CompareConstTensor(weight, m_Weight);
+
+ BOOST_TEST(bias.has_value() == m_Bias.has_value());
+ if (bias.has_value() && m_Bias.has_value())
+ {
+ CompareConstTensor(bias.value(), m_Bias.value());
+ }
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::FullyConnectedDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled);
+ BOOST_TEST(descriptor.m_TransposeWeightMatrix == m_Descriptor.m_TransposeWeightMatrix);
+ }
+
+ armnn::FullyConnectedDescriptor m_Descriptor;
+ armnn::ConstTensor m_Weight;
+ armnn::Optional<armnn::ConstTensor> m_Bias;
+ };
+
+ const std::string layerName("fullyConnected");
+ const armnn::TensorInfo inputInfo ({ 2, 5, 1, 1 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({ 2, 3 }, armnn::DataType::Float32);
+
+ const armnn::TensorInfo weightsInfo({ 5, 3 }, armnn::DataType::Float32);
+ const armnn::TensorInfo biasesInfo ({ 3 }, armnn::DataType::Float32);
+ std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements());
+ std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements());
+ armnn::ConstTensor weights(weightsInfo, weightsData);
+ armnn::ConstTensor biases(biasesInfo, biasesData);
+
+ armnn::FullyConnectedDescriptor descriptor;
+ descriptor.m_BiasEnabled = true;
+ descriptor.m_TransposeWeightMatrix = false;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const fullyConnectedLayer =
+ network->AddFullyConnectedLayer(descriptor, weights, biases, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
+ fullyConnectedLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ fullyConnectedLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ FullyConnectedLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor, weights, biases);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeGather)
+{
+ class GatherLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ GatherLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitGatherLayer(const armnn::IConnectableLayer* layer, const char *name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+
+ void VisitConstantLayer(const armnn::IConnectableLayer* layer,
+ const armnn::ConstTensor& input,
+ const char *name) override {}
+ };
+
+ const std::string layerName("gather");
+ armnn::TensorInfo paramsInfo({ 8 }, armnn::DataType::QuantisedAsymm8);
+ armnn::TensorInfo outputInfo({ 3 }, armnn::DataType::QuantisedAsymm8);
+ const armnn::TensorInfo indicesInfo({ 3 }, armnn::DataType::Signed32);
+
+ paramsInfo.SetQuantizationScale(1.0f);
+ paramsInfo.SetQuantizationOffset(0);
+ outputInfo.SetQuantizationScale(1.0f);
+ outputInfo.SetQuantizationOffset(0);
+
+ const std::vector<int32_t>& indicesData = {7, 6, 5};
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer *const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer *const constantLayer =
+ network->AddConstantLayer(armnn::ConstTensor(indicesInfo, indicesData));
+ armnn::IConnectableLayer *const gatherLayer = network->AddGatherLayer(layerName.c_str());
+ armnn::IConnectableLayer *const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(0));
+ constantLayer->GetOutputSlot(0).Connect(gatherLayer->GetInputSlot(1));
+ gatherLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(paramsInfo);
+ constantLayer->GetOutputSlot(0).SetTensorInfo(indicesInfo);
+ gatherLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ GatherLayerVerifier verifier(layerName, {paramsInfo, indicesInfo}, {outputInfo});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeGreater)
+{
+ class GreaterLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ GreaterLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitGreaterLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("greater");
+ const armnn::TensorInfo inputTensorInfo1({ 1, 2, 2, 2 }, armnn::DataType::Float32);
+ const armnn::TensorInfo inputTensorInfo2({ 1, 2, 2, 2 }, armnn::DataType::Float32);
+ const armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 2 }, armnn::DataType::Boolean);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer1 = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const inputLayer2 = network->AddInputLayer(1);
+ armnn::IConnectableLayer* const greaterLayer = network->AddGreaterLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer1->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(0));
+ inputLayer2->GetOutputSlot(0).Connect(greaterLayer->GetInputSlot(1));
+ greaterLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(inputTensorInfo1);
+ inputLayer2->GetOutputSlot(0).SetTensorInfo(inputTensorInfo2);
+ greaterLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ GreaterLayerVerifier verifier(layerName, {inputTensorInfo1, inputTensorInfo2}, {outputTensorInfo});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeL2Normalization)
+{
+ class L2NormalizationLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ L2NormalizationLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::L2NormalizationDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitL2NormalizationLayer(const armnn::IConnectableLayer* layer,
+ const armnn::L2NormalizationDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+ private:
+ void VerifyDescriptor(const armnn::L2NormalizationDescriptor& descriptor)
+ {
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::L2NormalizationDescriptor m_Descriptor;
+ };
+
+ const std::string l2NormLayerName("l2Normalization");
+ const armnn::TensorInfo info({1, 2, 1, 5}, armnn::DataType::Float32);
+
+ armnn::L2NormalizationDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NCHW;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer0 = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const l2NormLayer = network->AddL2NormalizationLayer(desc, l2NormLayerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer0->GetOutputSlot(0).Connect(l2NormLayer->GetInputSlot(0));
+ l2NormLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+ l2NormLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ L2NormalizationLayerVerifier verifier(l2NormLayerName, {info}, {info}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeMaximum)
+{
+ class MaximumLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ MaximumLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitMaximumLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("maximum");
+ const armnn::TensorInfo info({ 1, 2, 2, 3 }, 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 maximumLayer = network->AddMaximumLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer0->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(0));
+ inputLayer1->GetOutputSlot(0).Connect(maximumLayer->GetInputSlot(1));
+ maximumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
+ maximumLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ MaximumLayerVerifier verifier(layerName, {info, info}, {info});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeMean)
+{
+ class MeanLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ MeanLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::MeanDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitMeanLayer(const armnn::IConnectableLayer* layer,
+ const armnn::MeanDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::MeanDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_Axis == m_Descriptor.m_Axis);
+ BOOST_TEST(descriptor.m_KeepDims == m_Descriptor.m_KeepDims);
+ }
+
+ armnn::MeanDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("mean");
+ const armnn::TensorInfo inputInfo({1, 1, 3, 2}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({1, 1, 1, 2}, armnn::DataType::Float32);
+
+ armnn::MeanDescriptor descriptor;
+ descriptor.m_Axis = { 2 };
+ descriptor.m_KeepDims = true;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const meanLayer = network->AddMeanLayer(descriptor, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(meanLayer->GetInputSlot(0));
+ meanLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ meanLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ MeanLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeMerger)
+{
+ class MergerLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ MergerLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::OriginsDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitMergerLayer(const armnn::IConnectableLayer* layer,
+ const armnn::OriginsDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::OriginsDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.GetConcatAxis() == m_Descriptor.GetConcatAxis());
+ BOOST_TEST(descriptor.GetNumViews() == m_Descriptor.GetNumViews());
+ BOOST_TEST(descriptor.GetNumDimensions() == m_Descriptor.GetNumDimensions());
+
+ for (uint32_t i = 0; i < descriptor.GetNumViews(); i++)
+ {
+ for (uint32_t j = 0; j < descriptor.GetNumDimensions(); j++)
+ {
+ BOOST_TEST(descriptor.GetViewOrigin(i)[j] == m_Descriptor.GetViewOrigin(i)[j]);
+ }
+ }
+ }
+
+ armnn::OriginsDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("merger");
+ const armnn::TensorInfo inputInfo = armnn::TensorInfo({2, 3, 2, 2}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo = armnn::TensorInfo({4, 3, 2, 2}, armnn::DataType::Float32);
+
+ const std::vector<armnn::TensorShape> shapes({inputInfo.GetShape(), inputInfo.GetShape()});
+
+ armnn::OriginsDescriptor descriptor =
+ armnn::CreateMergerDescriptorForConcatenation(shapes.begin(), shapes.end(), 0);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayerOne = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const inputLayerTwo = network->AddInputLayer(1);
+ armnn::IConnectableLayer* const mergerLayer = network->AddMergerLayer(descriptor, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayerOne->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(0));
+ inputLayerTwo->GetOutputSlot(0).Connect(mergerLayer->GetInputSlot(1));
+ mergerLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayerOne->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ inputLayerTwo->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ mergerLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ MergerLayerVerifier verifier(layerName, {inputInfo, inputInfo}, {outputInfo}, descriptor);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeMinimum)
+{
+ class MinimumLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ MinimumLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitMinimumLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("minimum");
+ const armnn::TensorInfo info({ 1, 2, 2, 3 }, 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 minimumLayer = network->AddMinimumLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer0->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(0));
+ inputLayer1->GetOutputSlot(0).Connect(minimumLayer->GetInputSlot(1));
+ minimumLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
+ minimumLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ MinimumLayerVerifier verifier(layerName, {info, info}, {info});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeMultiplication)
+{
+ class MultiplicationLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ MultiplicationLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitMultiplicationLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("multiplication");
+ const armnn::TensorInfo info({ 1, 5, 2, 3 }, 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 multiplicationLayer = network->AddMultiplicationLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer0->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0));
+ inputLayer1->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1));
+ multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer0->GetOutputSlot(0).SetTensorInfo(info);
+ inputLayer1->GetOutputSlot(0).SetTensorInfo(info);
+ multiplicationLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ MultiplicationLayerVerifier verifier(layerName, {info, info}, {info});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeNormalization)
+{
+ class NormalizationLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ NormalizationLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::NormalizationDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitNormalizationLayer(const armnn::IConnectableLayer* layer,
+ const armnn::NormalizationDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::NormalizationDescriptor& descriptor)
+ {
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ BOOST_TEST(descriptor.m_NormSize == m_Descriptor.m_NormSize);
+ BOOST_TEST(descriptor.m_Alpha == m_Descriptor.m_Alpha);
+ BOOST_TEST(descriptor.m_Beta == m_Descriptor.m_Beta);
+ BOOST_TEST(descriptor.m_K == m_Descriptor.m_K);
+ BOOST_TEST(
+ static_cast<int>(descriptor.m_NormChannelType) == static_cast<int>(m_Descriptor.m_NormChannelType));
+ BOOST_TEST(
+ static_cast<int>(descriptor.m_NormMethodType) == static_cast<int>(m_Descriptor.m_NormMethodType));
+ }
+
+ armnn::NormalizationDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("normalization");
+ const armnn::TensorInfo info({2, 1, 2, 2}, armnn::DataType::Float32);
+
+ armnn::NormalizationDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NCHW;
+ desc.m_NormSize = 3;
+ desc.m_Alpha = 1;
+ desc.m_Beta = 1;
+ desc.m_K = 1;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const normalizationLayer = network->AddNormalizationLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(normalizationLayer->GetInputSlot(0));
+ normalizationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(info);
+ normalizationLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ NormalizationLayerVerifier verifier(layerName, {info}, {info}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializePad)
+{
+ class PadLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ PadLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::PadDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitPadLayer(const armnn::IConnectableLayer* layer,
+ const armnn::PadDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::PadDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_PadList == m_Descriptor.m_PadList);
+ }
+
+ armnn::PadDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("pad");
+ 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::PadDescriptor desc({{0, 0}, {1, 0}, {1, 1}, {1, 2}});
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const padLayer = network->AddPadLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(padLayer->GetInputSlot(0));
+ padLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+ padLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ PadLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializePermute)
+{
+ class PermuteLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ PermuteLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::PermuteDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitPermuteLayer(const armnn::IConnectableLayer* layer,
+ const armnn::PermuteDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::PermuteDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_DimMappings.IsEqual(m_Descriptor.m_DimMappings));
+ }
+
+ armnn::PermuteDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("permute");
+ const armnn::TensorInfo inputTensorInfo({4, 3, 2, 1}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputTensorInfo({1, 2, 3, 4}, armnn::DataType::Float32);
+
+ armnn::PermuteDescriptor descriptor(armnn::PermutationVector({3, 2, 1, 0}));
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const permuteLayer = network->AddPermuteLayer(descriptor, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(permuteLayer->GetInputSlot(0));
+ permuteLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
+ permuteLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ PermuteLayerVerifier verifier(layerName, {inputTensorInfo}, {outputTensorInfo}, descriptor);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializePooling2d)
+{
+ class Pooling2dLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ Pooling2dLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::Pooling2dDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitPooling2dLayer(const armnn::IConnectableLayer* layer,
+ const armnn::Pooling2dDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::Pooling2dDescriptor& descriptor)
+ {
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ BOOST_TEST(descriptor.m_PadLeft == m_Descriptor.m_PadLeft);
+ BOOST_TEST(descriptor.m_PadRight == m_Descriptor.m_PadRight);
+ BOOST_TEST(descriptor.m_PadTop == m_Descriptor.m_PadTop);
+ BOOST_TEST(descriptor.m_PadBottom == m_Descriptor.m_PadBottom);
+ BOOST_TEST(descriptor.m_PoolWidth == m_Descriptor.m_PoolWidth);
+ BOOST_TEST(descriptor.m_PoolHeight == m_Descriptor.m_PoolHeight);
+ BOOST_TEST(descriptor.m_StrideX == m_Descriptor.m_StrideX);
+ BOOST_TEST(descriptor.m_StrideY == m_Descriptor.m_StrideY);
+
+ BOOST_TEST(
+ static_cast<int>(descriptor.m_PaddingMethod) == static_cast<int>(m_Descriptor.m_PaddingMethod));
+ BOOST_TEST(
+ static_cast<int>(descriptor.m_PoolType) == static_cast<int>(m_Descriptor.m_PoolType));
+ BOOST_TEST(
+ static_cast<int>(descriptor.m_OutputShapeRounding) ==
+ static_cast<int>(m_Descriptor.m_OutputShapeRounding));
+ }
+
+ armnn::Pooling2dDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("pooling2d");
+ const armnn::TensorInfo inputInfo({1, 2, 2, 1}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({1, 1, 1, 1}, 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, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(pooling2dLayer->GetInputSlot(0));
+ pooling2dLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ pooling2dLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ Pooling2dLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeReshape)
+{
+ class ReshapeLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ ReshapeLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::ReshapeDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitReshapeLayer(const armnn::IConnectableLayer* layer,
+ const armnn::ReshapeDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::ReshapeDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_TargetShape == m_Descriptor.m_TargetShape);
+ }
+
+ armnn::ReshapeDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("reshape");
+ const armnn::TensorInfo inputInfo({1, 9}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({3, 3}, armnn::DataType::Float32);
+
+ armnn::ReshapeDescriptor descriptor({3, 3});
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const reshapeLayer = network->AddReshapeLayer(descriptor, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(reshapeLayer->GetInputSlot(0));
+ reshapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ ReshapeLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, descriptor);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeResizeBilinear)
+{
+ class ResizeBilinearLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ ResizeBilinearLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::ResizeBilinearDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitResizeBilinearLayer(const armnn::IConnectableLayer* layer,
+ const armnn::ResizeBilinearDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::ResizeBilinearDescriptor& descriptor)
+ {
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ BOOST_TEST(descriptor.m_TargetWidth == m_Descriptor.m_TargetWidth);
+ BOOST_TEST(descriptor.m_TargetHeight == m_Descriptor.m_TargetHeight);
+ }
+
+ armnn::ResizeBilinearDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("resizeBilinear");
+ const armnn::TensorInfo inputInfo = armnn::TensorInfo({1, 3, 5, 5}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo = armnn::TensorInfo({1, 3, 2, 4}, armnn::DataType::Float32);
+
+ armnn::ResizeBilinearDescriptor desc;
+ desc.m_TargetWidth = 4;
+ desc.m_TargetHeight = 2;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const resizeLayer = network->AddResizeBilinearLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(resizeLayer->GetInputSlot(0));
+ resizeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ resizeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ ResizeBilinearLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeRsqrt)
+{
+ class RsqrtLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ RsqrtLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitRsqrtLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("rsqrt");
+ const armnn::TensorInfo tensorInfo({ 3, 1, 2 }, armnn::DataType::Float32);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const rsqrtLayer = network->AddRsqrtLayer(layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(rsqrtLayer->GetInputSlot(0));
+ rsqrtLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+ rsqrtLayer->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ RsqrtLayerVerifier verifier(layerName, {tensorInfo}, {tensorInfo});
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeSoftmax)
+{
+ class SoftmaxLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ SoftmaxLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::SoftmaxDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitSoftmaxLayer(const armnn::IConnectableLayer* layer,
+ const armnn::SoftmaxDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::SoftmaxDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_Beta == m_Descriptor.m_Beta);
+ }
+
+ armnn::SoftmaxDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("softmax");
+ const armnn::TensorInfo info({1, 10}, armnn::DataType::Float32);
+
+ armnn::SoftmaxDescriptor descriptor;
+ descriptor.m_Beta = 1.0f;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const softmaxLayer = network->AddSoftmaxLayer(descriptor, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
+ softmaxLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(info);
+ softmaxLayer->GetOutputSlot(0).SetTensorInfo(info);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ SoftmaxLayerVerifier verifier(layerName, {info}, {info}, descriptor);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeSpaceToBatchNd)
+{
+ class SpaceToBatchNdLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ SpaceToBatchNdLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::SpaceToBatchNdDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitSpaceToBatchNdLayer(const armnn::IConnectableLayer* layer,
+ const armnn::SpaceToBatchNdDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::SpaceToBatchNdDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_PadList == m_Descriptor.m_PadList);
+ BOOST_TEST(descriptor.m_BlockShape == m_Descriptor.m_BlockShape);
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+
+ armnn::SpaceToBatchNdDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("spaceToBatchNd");
+ const armnn::TensorInfo inputInfo({2, 1, 2, 4}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo({8, 1, 1, 3}, armnn::DataType::Float32);
+
+ armnn::SpaceToBatchNdDescriptor desc;
+ desc.m_DataLayout = armnn::DataLayout::NCHW;
+ desc.m_BlockShape = {2, 2};
+ desc.m_PadList = {{0, 0}, {2, 0}};
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const spaceToBatchNdLayer = network->AddSpaceToBatchNdLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(spaceToBatchNdLayer->GetInputSlot(0));
+ spaceToBatchNdLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ spaceToBatchNdLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ SpaceToBatchNdLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeSplitter)
+{
+ class SplitterLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ SplitterLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::ViewsDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitSplitterLayer(const armnn::IConnectableLayer* layer,
+ const armnn::ViewsDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::ViewsDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.GetNumViews() == m_Descriptor.GetNumViews());
+ BOOST_TEST(descriptor.GetNumDimensions() == m_Descriptor.GetNumDimensions());
+
+ for (uint32_t i = 0; i < descriptor.GetNumViews(); i++)
+ {
+ for (uint32_t j = 0; j < descriptor.GetNumDimensions(); j++)
+ {
+ BOOST_TEST(descriptor.GetViewOrigin(i)[j] == m_Descriptor.GetViewOrigin(i)[j]);
+ BOOST_TEST(descriptor.GetViewSizes(i)[j] == m_Descriptor.GetViewSizes(i)[j]);
+ }
+ }
+ }
+
+ armnn::ViewsDescriptor m_Descriptor;
+ };
+
+ const unsigned int numViews = 3;
+ const unsigned int numDimensions = 4;
+ const unsigned int inputShape[] = {1, 18, 4, 4};
+ const unsigned int outputShape[] = {1, 6, 4, 4};
+
+ // This is modelled on how the caffe parser sets up a splitter layer to partition an input along dimension one.
+ unsigned int splitterDimSizes[4] = {static_cast<unsigned int>(inputShape[0]),
+ static_cast<unsigned int>(inputShape[1]),
+ static_cast<unsigned int>(inputShape[2]),
+ static_cast<unsigned int>(inputShape[3])};
+ splitterDimSizes[1] /= numViews;
+ armnn::ViewsDescriptor desc(numViews, numDimensions);
+
+ for (unsigned int g = 0; g < numViews; ++g)
+ {
+ desc.SetViewOriginCoord(g, 1, splitterDimSizes[1] * g);
+
+ for (unsigned int dimIdx=0; dimIdx < 4; dimIdx++)
+ {
+ desc.SetViewSize(g, dimIdx, splitterDimSizes[dimIdx]);
+ }
+ }
+
+ const std::string layerName("splitter");
+ const armnn::TensorInfo inputInfo(numDimensions, inputShape, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo(numDimensions, outputShape, armnn::DataType::Float32);
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const splitterLayer = network->AddSplitterLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer0 = network->AddOutputLayer(0);
+ armnn::IConnectableLayer* const outputLayer1 = network->AddOutputLayer(1);
+ armnn::IConnectableLayer* const outputLayer2 = network->AddOutputLayer(2);
+
+ inputLayer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0));
+ splitterLayer->GetOutputSlot(0).Connect(outputLayer0->GetInputSlot(0));
+ splitterLayer->GetOutputSlot(1).Connect(outputLayer1->GetInputSlot(0));
+ splitterLayer->GetOutputSlot(2).Connect(outputLayer2->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ splitterLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+ splitterLayer->GetOutputSlot(1).SetTensorInfo(outputInfo);
+ splitterLayer->GetOutputSlot(2).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ SplitterLayerVerifier verifier(layerName, {inputInfo}, {outputInfo, outputInfo, outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeStridedSlice)
+{
+ class StridedSliceLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ StridedSliceLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos,
+ const armnn::StridedSliceDescriptor& descriptor)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos)
+ , m_Descriptor(descriptor) {}
+
+ void VisitStridedSliceLayer(const armnn::IConnectableLayer* layer,
+ const armnn::StridedSliceDescriptor& descriptor,
+ const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ VerifyDescriptor(descriptor);
+ }
+
+ private:
+ void VerifyDescriptor(const armnn::StridedSliceDescriptor& descriptor)
+ {
+ BOOST_TEST(descriptor.m_Begin == m_Descriptor.m_Begin);
+ BOOST_TEST(descriptor.m_End == m_Descriptor.m_End);
+ BOOST_TEST(descriptor.m_Stride == m_Descriptor.m_Stride);
+ BOOST_TEST(descriptor.m_BeginMask == m_Descriptor.m_BeginMask);
+ BOOST_TEST(descriptor.m_EndMask == m_Descriptor.m_EndMask);
+ BOOST_TEST(descriptor.m_ShrinkAxisMask == m_Descriptor.m_ShrinkAxisMask);
+ BOOST_TEST(descriptor.m_EllipsisMask == m_Descriptor.m_EllipsisMask);
+ BOOST_TEST(descriptor.m_NewAxisMask == m_Descriptor.m_NewAxisMask);
+ BOOST_TEST(GetDataLayoutName(descriptor.m_DataLayout) == GetDataLayoutName(m_Descriptor.m_DataLayout));
+ }
+ armnn::StridedSliceDescriptor m_Descriptor;
+ };
+
+ const std::string layerName("stridedSlice");
+ const armnn::TensorInfo inputInfo = armnn::TensorInfo({3, 2, 3, 1}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputInfo = armnn::TensorInfo({3, 1}, armnn::DataType::Float32);
+
+ armnn::StridedSliceDescriptor desc({0, 0, 1, 0}, {1, 1, 1, 1}, {1, 1, 1, 1});
+ desc.m_EndMask = (1 << 4) - 1;
+ desc.m_ShrinkAxisMask = (1 << 1) | (1 << 2);
+ desc.m_DataLayout = armnn::DataLayout::NCHW;
+
+ armnn::INetworkPtr network = armnn::INetwork::Create();
+ armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0);
+ armnn::IConnectableLayer* const stridedSliceLayer = network->AddStridedSliceLayer(desc, layerName.c_str());
+ armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0);
+
+ inputLayer->GetOutputSlot(0).Connect(stridedSliceLayer->GetInputSlot(0));
+ stridedSliceLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
+
+ inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo);
+ stridedSliceLayer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network));
+ BOOST_CHECK(deserializedNetwork);
+
+ StridedSliceLayerVerifier verifier(layerName, {inputInfo}, {outputInfo}, desc);
+ deserializedNetwork->Accept(verifier);
+}
+
+BOOST_AUTO_TEST_CASE(SerializeSubtraction)
+{
+ class SubtractionLayerVerifier : public LayerVerifierBase
+ {
+ public:
+ SubtractionLayerVerifier(const std::string& layerName,
+ const std::vector<armnn::TensorInfo>& inputInfos,
+ const std::vector<armnn::TensorInfo>& outputInfos)
+ : LayerVerifierBase(layerName, inputInfos, outputInfos) {}
+
+ void VisitSubtractionLayer(const armnn::IConnectableLayer* layer, const char* name) override
+ {
+ VerifyNameAndConnections(layer, name);
+ }
+ };
+
+ const std::string layerName("subtraction");
+ const armnn::TensorInfo info({ 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(layerName.c_str());
+ 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);
+
+ SubtractionLayerVerifier verifier(layerName, {info, info}, {info});
+ deserializedNetwork->Accept(verifier);
}
BOOST_AUTO_TEST_SUITE_END()