blob: e5e79304be535aead7fe0da3598dcb6de684e9d4 [file] [log] [blame]
//
// Copyright © 2017, 2023 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <armnn/Descriptors.hpp>
#include <armnn/IRuntime.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/Types.hpp>
#include <Runtime.hpp>
#include <doctest/doctest.h>
TEST_SUITE("DebugCallback")
{
namespace
{
using namespace armnn;
INetworkPtr CreateSimpleNetwork()
{
INetworkPtr net(INetwork::Create());
IConnectableLayer* input = net->AddInputLayer(0, "Input");
ActivationDescriptor descriptor;
descriptor.m_Function = ActivationFunction::ReLu;
IConnectableLayer* activationLayer = net->AddActivationLayer(descriptor, "Activation:ReLu");
IConnectableLayer* output = net->AddOutputLayer(0);
input->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0));
activationLayer->GetOutputSlot(0).Connect(output->GetInputSlot(0));
input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 5 }, DataType::Float32));
activationLayer->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 5 }, DataType::Float32));
return net;
}
TEST_CASE("RuntimeRegisterDebugCallback")
{
INetworkPtr net = CreateSimpleNetwork();
IRuntime::CreationOptions options;
IRuntimePtr runtime(IRuntime::Create(options));
// Optimize the network with debug option
OptimizerOptionsOpaque optimizerOptions(false, true);
std::vector<BackendId> backends = { "CpuRef" };
IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optimizerOptions);
NetworkId netId;
CHECK(runtime->LoadNetwork(netId, std::move(optNet)) == Status::Success);
// Set up callback function
int callCount = 0;
std::vector<TensorShape> tensorShapes;
std::vector<unsigned int> slotIndexes;
auto mockCallback = [&](LayerGuid guid, unsigned int slotIndex, ITensorHandle* tensor)
{
armnn::IgnoreUnused(guid);
slotIndexes.push_back(slotIndex);
tensorShapes.push_back(tensor->GetShape());
callCount++;
};
runtime->RegisterDebugCallback(netId, mockCallback);
std::vector<float> inputData({-2, -1, 0, 1, 2});
std::vector<float> outputData(5);
TensorInfo inputTensorInfo = runtime->GetInputTensorInfo(netId, 0);
inputTensorInfo.SetConstant(true);
InputTensors inputTensors
{
{0, ConstTensor(inputTensorInfo, inputData.data())}
};
OutputTensors outputTensors
{
{0, Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())}
};
runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
// Check that the callback was called twice
CHECK(callCount == 2);
// Check that tensor handles passed to callback have correct shapes
const std::vector<TensorShape> expectedShapes({TensorShape({1, 1, 1, 5}), TensorShape({1, 1, 1, 5})});
CHECK(tensorShapes == expectedShapes);
// Check that slot indexes passed to callback are correct
const std::vector<unsigned int> expectedSlotIndexes({0, 0});
CHECK(slotIndexes == expectedSlotIndexes);
}
} // anonymous namespace
}