| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "../Serializer.hpp" |
| |
| #include <armnn/Descriptors.hpp> |
| #include <armnn/INetwork.hpp> |
| #include <armnn/IRuntime.hpp> |
| #include <armnnDeserializer/IDeserializer.hpp> |
| #include <armnn/utility/IgnoreUnused.hpp> |
| |
| #include <doctest/doctest.h> |
| |
| #include <sstream> |
| |
| TEST_SUITE("SerializerTests") |
| { |
| class VerifyActivationName : public armnn::IStrategy |
| { |
| public: |
| void ExecuteStrategy(const armnn::IConnectableLayer* layer, |
| const armnn::BaseDescriptor& descriptor, |
| const std::vector<armnn::ConstTensor>& constants, |
| const char* name, |
| const armnn::LayerBindingId id = 0) override |
| { |
| IgnoreUnused(layer, descriptor, constants, id); |
| if (layer->GetType() == armnn::LayerType::Activation) |
| { |
| CHECK(std::string(name) == "activation"); |
| } |
| } |
| }; |
| |
| TEST_CASE("ActivationSerialization") |
| { |
| armnnDeserializer::IDeserializerPtr parser = armnnDeserializer::IDeserializer::Create(); |
| |
| armnn::TensorInfo inputInfo(armnn::TensorShape({1, 2, 2, 1}), armnn::DataType::Float32, 1.0f, 0); |
| armnn::TensorInfo outputInfo(armnn::TensorShape({1, 2, 2, 1}), armnn::DataType::Float32, 4.0f, 0); |
| |
| // Construct network |
| armnn::INetworkPtr network = armnn::INetwork::Create(); |
| |
| armnn::ActivationDescriptor descriptor; |
| descriptor.m_Function = armnn::ActivationFunction::ReLu; |
| descriptor.m_A = 0; |
| descriptor.m_B = 0; |
| |
| armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0, "input"); |
| armnn::IConnectableLayer* const activationLayer = network->AddActivationLayer(descriptor, "activation"); |
| armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0, "output"); |
| |
| inputLayer->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0)); |
| inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); |
| |
| activationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); |
| activationLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); |
| |
| armnnSerializer::ISerializerPtr serializer = armnnSerializer::ISerializer::Create(); |
| |
| serializer->Serialize(*network); |
| |
| std::stringstream stream; |
| serializer->SaveSerializedToStream(stream); |
| |
| std::string const serializerString{stream.str()}; |
| std::vector<std::uint8_t> const serializerVector{serializerString.begin(), serializerString.end()}; |
| |
| armnn::INetworkPtr deserializedNetwork = parser->CreateNetworkFromBinary(serializerVector); |
| |
| VerifyActivationName visitor; |
| deserializedNetwork->ExecuteStrategy(visitor); |
| |
| armnn::IRuntime::CreationOptions options; // default options |
| armnn::IRuntimePtr run = armnn::IRuntime::Create(options); |
| auto deserializedOptimized = Optimize(*deserializedNetwork, { armnn::Compute::CpuRef }, run->GetDeviceSpec()); |
| |
| armnn::NetworkId networkIdentifier; |
| |
| // Load graph into runtime |
| run->LoadNetwork(networkIdentifier, std::move(deserializedOptimized)); |
| |
| std::vector<float> inputData {0.0f, -5.3f, 42.0f, -42.0f}; |
| armnn::TensorInfo inputTensorInfo = run->GetInputTensorInfo(networkIdentifier, 0); |
| inputTensorInfo.SetConstant(true); |
| armnn::InputTensors inputTensors |
| { |
| {0, armnn::ConstTensor(inputTensorInfo, inputData.data())} |
| }; |
| |
| std::vector<float> expectedOutputData {0.0f, 0.0f, 42.0f, 0.0f}; |
| |
| std::vector<float> outputData(4); |
| armnn::OutputTensors outputTensors |
| { |
| {0, armnn::Tensor(run->GetOutputTensorInfo(networkIdentifier, 0), outputData.data())} |
| }; |
| run->EnqueueWorkload(networkIdentifier, inputTensors, outputTensors); |
| CHECK(std::equal(outputData.begin(), outputData.end(), expectedOutputData.begin(), expectedOutputData.end())); |
| } |
| |
| } |