blob: cd3708cc4fc54c1a4341f162ff4f94cd190f9839 [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <armnn/ArmNN.hpp>
#include <Graph.hpp>
#include <Network.hpp>
#include <reference/RefWorkloadFactory.hpp>
#include <boost/test/unit_test.hpp>
#include <test/GraphUtils.hpp>
BOOST_AUTO_TEST_SUITE(RefOptimizedNetwork)
BOOST_AUTO_TEST_CASE(OptimizeValidateCpuRefWorkloads)
{
const armnn::TensorInfo desc({3, 5}, armnn::DataType::Float32);
armnn::Network net;
armnn::NormalizationDescriptor nmDesc;
armnn::ActivationDescriptor acDesc;
// in
// |
// nm
// / |
// ac |
// \ |
// ml
// |
// sm
// |
// ot
armnn::IConnectableLayer* layer = net.AddInputLayer(0, "in");
layer->GetOutputSlot(0).SetTensorInfo(desc);
armnn::IConnectableLayer* const normLayer = net.AddNormalizationLayer(nmDesc, "nm");
layer->GetOutputSlot(0).Connect(normLayer->GetInputSlot(0));
normLayer->GetOutputSlot(0).SetTensorInfo(desc);
layer = net.AddActivationLayer(acDesc, "ac");
normLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
layer->GetOutputSlot(0).SetTensorInfo(desc);
armnn::IConnectableLayer* prevLayer = layer;
layer = net.AddMultiplicationLayer("ml");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
normLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1));
layer->GetOutputSlot(0).SetTensorInfo(desc);
prevLayer = layer;
armnn::SoftmaxDescriptor softmaxDescriptor;
layer = net.AddSoftmaxLayer(softmaxDescriptor, "sm");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
layer->GetOutputSlot(0).SetTensorInfo(desc);
prevLayer = layer;
layer = net.AddOutputLayer(0, "ot");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
armnn::IRuntime::CreationOptions options;
armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
std::vector<armnn::BackendId> backends = { armnn::Compute::CpuRef };
armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(net, backends, runtime->GetDeviceSpec());
static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph().AllocateDynamicBuffers();
BOOST_CHECK(optNet);
// Validates workloads.
armnn::RefWorkloadFactory fact;
for (auto&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())
{
BOOST_CHECK_NO_THROW(
layer->CreateWorkload(static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph(), fact));
}
}
BOOST_AUTO_TEST_CASE(OptimizeValidateWorkloadsCpuRefPermuteLayer)
{
// Create runtime in which test will run
armnn::IRuntime::CreationOptions options;
armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
// build up the structure of the network
armnn::INetworkPtr net(armnn::INetwork::Create());
armnn::IConnectableLayer* input = net->AddInputLayer(0);
armnn::PermuteDescriptor descriptor({0, 2, 3, 1});
armnn::IConnectableLayer* permute = net->AddPermuteLayer(descriptor);
armnn::IConnectableLayer* output = net->AddOutputLayer(0);
input->GetOutputSlot(0).Connect(permute->GetInputSlot(0));
permute->GetOutputSlot(0).Connect(output->GetInputSlot(0));
input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 1, 4, 4 }, armnn::DataType::Float32));
permute->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 4, 1, 4 }, armnn::DataType::Float32));
// optimize the network
armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec());
for (auto&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())
{
BOOST_CHECK(layer->GetBackendId() == armnn::Compute::CpuRef);
}
}
BOOST_AUTO_TEST_CASE(OptimizeValidateWorkloadsCpuRefMeanLayer)
{
// Create runtime in which test will run
armnn::IRuntime::CreationOptions options;
armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
// build up the structure of the network
armnn::INetworkPtr net(armnn::INetwork::Create());
armnn::IConnectableLayer* input = net->AddInputLayer(0);
armnn::MeanDescriptor descriptor({ 0, 1 }, false);
armnn::IConnectableLayer* meanLayer = net->AddMeanLayer(descriptor);
armnn::IConnectableLayer* output = net->AddOutputLayer(0);
input->GetOutputSlot(0).Connect(meanLayer->GetInputSlot(0));
meanLayer->GetOutputSlot(0).Connect(output->GetInputSlot(0));
input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 4, 3, 2 }, armnn::DataType::Float32));
meanLayer->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 2 }, armnn::DataType::Float32));
// optimize the network
armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec());
for (auto&& layer : static_cast<armnn::OptimizedNetwork*>(optNet.get())->GetGraph())
{
BOOST_CHECK(layer->GetBackendId() == armnn::Compute::CpuRef);
}
}
BOOST_AUTO_TEST_CASE(DebugTestOnCpuRef)
{
armnn::Network net;
armnn::ActivationDescriptor activation1Descriptor;
activation1Descriptor.m_Function = armnn::ActivationFunction::BoundedReLu;
activation1Descriptor.m_A = 1.f;
activation1Descriptor.m_B = -1.f;
// Defines layers.
auto input = net.AddInputLayer(0, "InputLayer");
auto activation = net.AddActivationLayer(activation1Descriptor, "ActivationLayer");
auto output = net.AddOutputLayer(0, "OutputLayer");
// Connects layers.
input->GetOutputSlot(0).Connect(activation->GetInputSlot(0));
activation->GetOutputSlot(0).Connect(output->GetInputSlot(0));
armnn::TensorShape shape({4});
armnn::TensorInfo info(shape, armnn::DataType::Float32);
input->GetOutputSlot(0).SetTensorInfo(info);
activation->GetOutputSlot(0).SetTensorInfo(info);
armnn::IRuntime::CreationOptions options;
armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
armnn::OptimizerOptions optimizerOptions;
optimizerOptions.m_Debug = true;
armnn::IOptimizedNetworkPtr optimizedNet = armnn::Optimize(net, backends, runtime->GetDeviceSpec(),
optimizerOptions);
const armnn::Graph& graph = static_cast<armnn::OptimizedNetwork*>(optimizedNet.get())->GetGraph();
// Tests that all layers are present in the graph.
BOOST_TEST(graph.GetNumLayers() == 5);
// Tests that the vertices exist and have correct names.
BOOST_TEST(GraphHasNamedLayer(graph, "InputLayer"));
BOOST_TEST(GraphHasNamedLayer(graph, "DebugLayerAfterInputLayer"));
BOOST_TEST(GraphHasNamedLayer(graph, "ActivationLayer"));
BOOST_TEST(GraphHasNamedLayer(graph, "DebugLayerAfterActivationLayer"));
BOOST_TEST(GraphHasNamedLayer(graph, "OutputLayer"));
}
BOOST_AUTO_TEST_SUITE_END()