Fp16SupportTest.cpp File Reference

#include <armnn/Descriptors.hpp>
#include <armnn/IRuntime.hpp>
#include <armnn/INetwork.hpp>
#include <Half.hpp>
#include <Graph.hpp>
#include <Optimizer.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <armnn/utility/IgnoreUnused.hpp>
#include <boost/test/unit_test.hpp>
#include <set>

Go to the source code of this file.

Functions
	BOOST_AUTO_TEST_CASE (Fp16DataTypeSupport)
	BOOST_AUTO_TEST_CASE (Fp16AdditionTest)

Function Documentation

BOOST_AUTO_TEST_CASE() [1/2]

BOOST_AUTO_TEST_CASE

(

Fp16DataTypeSupport

)

Definition at line 24 of file Fp16SupportTest.cpp.

References Graph::AddLayer(), OutputSlot::Connect(), armnn::Float16, TensorInfo::GetDataType(), Layer::GetOutputSlot(), OutputSlot::GetTensorInfo(), and OutputSlot::SetTensorInfo().

{
    Graph graph;

    Layer* const inputLayer1 = graph.AddLayer<InputLayer>(1, "input1");
    Layer* const inputLayer2 = graph.AddLayer<InputLayer>(2, "input2");

    Layer* const additionLayer = graph.AddLayer<AdditionLayer>("addition");
    Layer* const outputLayer = graph.AddLayer<armnn::OutputLayer>(0, "output");

    TensorInfo fp16TensorInfo({1, 2, 3, 5}, armnn::DataType::Float16);
    inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
    inputLayer2->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
    additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));

    inputLayer1->GetOutputSlot().SetTensorInfo(fp16TensorInfo);
    inputLayer2->GetOutputSlot().SetTensorInfo(fp16TensorInfo);
    additionLayer->GetOutputSlot().SetTensorInfo(fp16TensorInfo);

    BOOST_CHECK(inputLayer1->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
    BOOST_CHECK(inputLayer2->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
    BOOST_CHECK(additionLayer->GetOutputSlot(0).GetTensorInfo().GetDataType() == armnn::DataType::Float16);
}

BOOST_AUTO_TEST_CASE() [2/2]

BOOST_AUTO_TEST_CASE

(

Fp16AdditionTest

)

Definition at line 48 of file Fp16SupportTest.cpp.

References BOOST_AUTO_TEST_SUITE_END(), IOutputSlot::Connect(), IRuntime::Create(), INetwork::Create(), armnn::Float16, IConnectableLayer::GetInputSlot(), IConnectableLayer::GetOutputSlot(), armnn::GpuAcc, armnn::Optimize(), and IOutputSlot::SetTensorInfo().

{
   using namespace half_float::literal;
   // Create runtime in which test will run
   IRuntime::CreationOptions options;
   IRuntimePtr runtime(IRuntime::Create(options));

   // Builds up the structure of the network.
   INetworkPtr net(INetwork::Create());

   IConnectableLayer* inputLayer1 = net->AddInputLayer(0);
   IConnectableLayer* inputLayer2 = net->AddInputLayer(1);
   IConnectableLayer* additionLayer = net->AddAdditionLayer();
   IConnectableLayer* outputLayer = net->AddOutputLayer(0);

   inputLayer1->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
   inputLayer2->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
   additionLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));

   //change to float16
   TensorInfo fp16TensorInfo(TensorShape({4}), DataType::Float16);
   inputLayer1->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);
   inputLayer2->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);
   additionLayer->GetOutputSlot(0).SetTensorInfo(fp16TensorInfo);

   // optimize the network
   std::vector<BackendId> backends = {Compute::GpuAcc};
   IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());

   // Loads it into the runtime.
   NetworkId netId;
   runtime->LoadNetwork(netId, std::move(optNet));

   std::vector<Half> input1Data
   {
       1.0_h, 2.0_h, 3.0_h, 4.0_h
   };

   std::vector<Half> input2Data
   {
       100.0_h, 200.0_h, 300.0_h, 400.0_h
   };

   InputTensors inputTensors
   {
       {0,ConstTensor(runtime->GetInputTensorInfo(netId, 0), input1Data.data())},
       {1,ConstTensor(runtime->GetInputTensorInfo(netId, 0), input2Data.data())}
   };

   std::vector<Half> outputData(input1Data.size());
   OutputTensors outputTensors
   {
       {0,Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())}
   };

   // Does the inference.
   runtime->EnqueueWorkload(netId, inputTensors, outputTensors);

   // Checks the results.
   BOOST_TEST(outputData == std::vector<Half>({ 101.0_h, 202.0_h, 303.0_h, 404.0_h})); // Add
}