blob: c64c0a0d40d86a3003b1b6ed17db449593f35bff [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include <GraphUtils.hpp>
#include <armnn/LayerVisitorBase.hpp>
#include <Network.hpp>
#include <doctest/doctest.h>
namespace
{
bool AreAllLayerInputSlotsConnected(const armnn::IConnectableLayer& layer)
{
bool allConnected = true;
for (unsigned int i = 0; i < layer.GetNumInputSlots(); ++i)
{
const bool inputConnected = layer.GetInputSlot(i).GetConnection() != nullptr;
allConnected &= inputConnected;
}
return allConnected;
}
}
TEST_SUITE("Network")
{
TEST_CASE("LayerGuids")
{
armnn::NetworkImpl net;
LayerGuid inputId = net.AddInputLayer(0)->GetGuid();
LayerGuid addId = net.AddAdditionLayer()->GetGuid();
LayerGuid outputId = net.AddOutputLayer(0)->GetGuid();
CHECK(inputId != addId);
CHECK(addId != outputId);
CHECK(inputId != outputId);
}
TEST_CASE("NetworkBasic")
{
armnn::NetworkImpl net;
CHECK(net.PrintGraph() == armnn::Status::Success);
}
TEST_CASE("LayerNamesAreOptionalForINetwork")
{
armnn::INetworkPtr inet(armnn::INetwork::Create());
inet->AddInputLayer(0);
inet->AddAdditionLayer();
inet->AddActivationLayer(armnn::ActivationDescriptor());
inet->AddOutputLayer(0);
}
TEST_CASE("LayerNamesAreOptionalForNetwork")
{
armnn::NetworkImpl net;
net.AddInputLayer(0);
net.AddAdditionLayer();
net.AddActivationLayer(armnn::ActivationDescriptor());
net.AddOutputLayer(0);
}
TEST_CASE("NetworkModification")
{
armnn::NetworkImpl net;
armnn::IConnectableLayer* const inputLayer = net.AddInputLayer(0, "input layer");
CHECK(inputLayer);
unsigned int dims[] = { 10,1,1,1 };
std::vector<float> convWeightsData(10);
armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float32, 0.0f, 0, true), convWeightsData);
armnn::Convolution2dDescriptor convDesc2d;
armnn::IConnectableLayer* const convLayer = net.AddConvolution2dLayer(convDesc2d,
weights,
armnn::EmptyOptional(),
"conv layer");
CHECK(convLayer);
inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
armnn::FullyConnectedDescriptor fullyConnectedDesc;
// Constant layer that now holds weights data for FullyConnected
armnn::IConnectableLayer* const constantWeightsLayer = net.AddConstantLayer(weights, "const weights");
armnn::IConnectableLayer* const fullyConnectedLayer = net.AddFullyConnectedLayer(fullyConnectedDesc,
"fully connected");
CHECK(constantWeightsLayer);
CHECK(fullyConnectedLayer);
constantWeightsLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(1));
convLayer->GetOutputSlot(0).Connect(fullyConnectedLayer->GetInputSlot(0));
armnn::Pooling2dDescriptor pooling2dDesc;
armnn::IConnectableLayer* const poolingLayer = net.AddPooling2dLayer(pooling2dDesc, "pooling2d");
CHECK(poolingLayer);
fullyConnectedLayer->GetOutputSlot(0).Connect(poolingLayer->GetInputSlot(0));
armnn::ActivationDescriptor activationDesc;
armnn::IConnectableLayer* const activationLayer = net.AddActivationLayer(activationDesc, "activation");
CHECK(activationLayer);
poolingLayer->GetOutputSlot(0).Connect(activationLayer->GetInputSlot(0));
armnn::NormalizationDescriptor normalizationDesc;
armnn::IConnectableLayer* const normalizationLayer = net.AddNormalizationLayer(normalizationDesc, "normalization");
CHECK(normalizationLayer);
activationLayer->GetOutputSlot(0).Connect(normalizationLayer->GetInputSlot(0));
armnn::SoftmaxDescriptor softmaxDesc;
armnn::IConnectableLayer* const softmaxLayer = net.AddSoftmaxLayer(softmaxDesc, "softmax");
CHECK(softmaxLayer);
normalizationLayer->GetOutputSlot(0).Connect(softmaxLayer->GetInputSlot(0));
armnn::BatchNormalizationDescriptor batchNormDesc;
armnn::TensorInfo tensorInfo({ 1 }, armnn::DataType::Float32, 0.0f, 0, true);
std::vector<float> data(tensorInfo.GetNumBytes() / sizeof(float));
armnn::ConstTensor invalidTensor(tensorInfo, data);
armnn::IConnectableLayer* const batchNormalizationLayer = net.AddBatchNormalizationLayer(batchNormDesc,
invalidTensor,
invalidTensor,
invalidTensor,
invalidTensor,
"batch norm");
CHECK(batchNormalizationLayer);
softmaxLayer->GetOutputSlot(0).Connect(batchNormalizationLayer->GetInputSlot(0));
armnn::IConnectableLayer* const additionLayer = net.AddAdditionLayer("addition");
CHECK(additionLayer);
batchNormalizationLayer->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(0));
batchNormalizationLayer->GetOutputSlot(0).Connect(additionLayer->GetInputSlot(1));
armnn::IConnectableLayer* const multiplicationLayer = net.AddMultiplicationLayer("multiplication");
CHECK(multiplicationLayer);
additionLayer->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(0));
additionLayer->GetOutputSlot(0).Connect(multiplicationLayer->GetInputSlot(1));
armnn::IConnectableLayer* const outputLayer = net.AddOutputLayer(0, "output layer");
CHECK(outputLayer);
multiplicationLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
//Tests that all layers are present in the graph.
CHECK(net.GetGraph().GetNumLayers() == 12);
//Tests that the vertices exist and have correct names.
CHECK(GraphHasNamedLayer(net.GetGraph(), "input layer"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "conv layer"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "const weights"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "fully connected"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "pooling2d"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "activation"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "normalization"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "softmax"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "batch norm"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "addition"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "multiplication"));
CHECK(GraphHasNamedLayer(net.GetGraph(), "output layer"));
auto checkOneOutputToOneInputConnection = []
(const armnn::IConnectableLayer* const srcLayer,
const armnn::IConnectableLayer* const tgtLayer,
int expectedSrcNumInputs = 1,
int expectedDstNumOutputs = 1)
{
CHECK(srcLayer->GetNumInputSlots() == expectedSrcNumInputs);
CHECK(srcLayer->GetNumOutputSlots() == 1);
CHECK(tgtLayer->GetNumInputSlots() == 1);
CHECK(tgtLayer->GetNumOutputSlots() == expectedDstNumOutputs);
CHECK(srcLayer->GetOutputSlot(0).GetNumConnections() == 1);
CHECK(srcLayer->GetOutputSlot(0).GetConnection(0) == &tgtLayer->GetInputSlot(0));
CHECK(&srcLayer->GetOutputSlot(0) == tgtLayer->GetInputSlot(0).GetConnection());
};
auto checkOneOutputToTwoInputsConnections = []
(const armnn::IConnectableLayer* const srcLayer,
const armnn::IConnectableLayer* const tgtLayer,
int expectedSrcNumInputs,
int expectedDstNumOutputs = 1)
{
CHECK(srcLayer->GetNumInputSlots() == expectedSrcNumInputs);
CHECK(srcLayer->GetNumOutputSlots() == 1);
CHECK(tgtLayer->GetNumInputSlots() == 2);
CHECK(tgtLayer->GetNumOutputSlots() == expectedDstNumOutputs);
CHECK(srcLayer->GetOutputSlot(0).GetNumConnections() == 2);
for (unsigned int i = 0; i < srcLayer->GetOutputSlot(0).GetNumConnections(); ++i)
{
CHECK(srcLayer->GetOutputSlot(0).GetConnection(i) == &tgtLayer->GetInputSlot(i));
CHECK(&srcLayer->GetOutputSlot(0) == tgtLayer->GetInputSlot(i).GetConnection());
}
};
auto checkOneOutputToTwoInputConnectionForTwoDifferentLayers = []
(const armnn::IConnectableLayer* const srcLayer1,
const armnn::IConnectableLayer* const srcLayer2,
const armnn::IConnectableLayer* const tgtLayer,
int expectedSrcNumInputs1 = 1,
int expectedSrcNumInputs2 = 1,
int expectedDstNumOutputs = 1)
{
CHECK(srcLayer1->GetNumInputSlots() == expectedSrcNumInputs1);
CHECK(srcLayer1->GetNumOutputSlots() == 1);
CHECK(srcLayer2->GetNumInputSlots() == expectedSrcNumInputs2);
CHECK(srcLayer2->GetNumOutputSlots() == 1);
CHECK(tgtLayer->GetNumInputSlots() == 2);
CHECK(tgtLayer->GetNumOutputSlots() == expectedDstNumOutputs);
CHECK(srcLayer1->GetOutputSlot(0).GetNumConnections() == 1);
CHECK(srcLayer2->GetOutputSlot(0).GetNumConnections() == 1);
CHECK(srcLayer1->GetOutputSlot(0).GetConnection(0) == &tgtLayer->GetInputSlot(0));
CHECK(srcLayer2->GetOutputSlot(0).GetConnection(0) == &tgtLayer->GetInputSlot(1));
CHECK(&srcLayer1->GetOutputSlot(0) == tgtLayer->GetInputSlot(0).GetConnection());
CHECK(&srcLayer2->GetOutputSlot(0) == tgtLayer->GetInputSlot(1).GetConnection());
};
CHECK(AreAllLayerInputSlotsConnected(*convLayer));
CHECK(AreAllLayerInputSlotsConnected(*fullyConnectedLayer));
CHECK(AreAllLayerInputSlotsConnected(*poolingLayer));
CHECK(AreAllLayerInputSlotsConnected(*activationLayer));
CHECK(AreAllLayerInputSlotsConnected(*normalizationLayer));
CHECK(AreAllLayerInputSlotsConnected(*softmaxLayer));
CHECK(AreAllLayerInputSlotsConnected(*batchNormalizationLayer));
CHECK(AreAllLayerInputSlotsConnected(*additionLayer));
CHECK(AreAllLayerInputSlotsConnected(*multiplicationLayer));
CHECK(AreAllLayerInputSlotsConnected(*outputLayer));
// Checks connectivity.
checkOneOutputToOneInputConnection(inputLayer, convLayer, 0);
checkOneOutputToTwoInputConnectionForTwoDifferentLayers(convLayer, constantWeightsLayer, fullyConnectedLayer, 1, 0);
checkOneOutputToOneInputConnection(fullyConnectedLayer, poolingLayer, 2, 1);
checkOneOutputToOneInputConnection(poolingLayer, activationLayer);
checkOneOutputToOneInputConnection(activationLayer, normalizationLayer);
checkOneOutputToOneInputConnection(normalizationLayer, softmaxLayer);
checkOneOutputToOneInputConnection(softmaxLayer, batchNormalizationLayer);
checkOneOutputToTwoInputsConnections(batchNormalizationLayer, additionLayer, 1);
checkOneOutputToTwoInputsConnections(additionLayer, multiplicationLayer, 2);
checkOneOutputToOneInputConnection(multiplicationLayer, outputLayer, 2, 0);
}
TEST_CASE("NetworkModification_SplitterConcat")
{
armnn::NetworkImpl net;
// Adds an input layer and an input tensor descriptor.
armnn::IConnectableLayer* inputLayer = net.AddInputLayer(0, "input layer");
CHECK(inputLayer);
// Adds a splitter layer.
armnn::ViewsDescriptor splitterDesc(2,4);
armnn::IConnectableLayer* splitterLayer = net.AddSplitterLayer(splitterDesc, "splitter layer");
CHECK(splitterLayer);
inputLayer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0));
// Adds a softmax layer 1.
armnn::SoftmaxDescriptor softmaxDescriptor;
armnn::IConnectableLayer* softmaxLayer1 = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_1");
CHECK(softmaxLayer1);
splitterLayer->GetOutputSlot(0).Connect(softmaxLayer1->GetInputSlot(0));
// Adds a softmax layer 2.
armnn::IConnectableLayer* softmaxLayer2 = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_2");
CHECK(softmaxLayer2);
splitterLayer->GetOutputSlot(1).Connect(softmaxLayer2->GetInputSlot(0));
// Adds a concat layer.
armnn::OriginsDescriptor concatDesc(2, 4);
armnn::IConnectableLayer* concatLayer = net.AddConcatLayer(concatDesc, "concat layer");
CHECK(concatLayer);
softmaxLayer1->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(0));
softmaxLayer2->GetOutputSlot(0).Connect(concatLayer->GetInputSlot(1));
// Adds an output layer.
armnn::IConnectableLayer* outputLayer = net.AddOutputLayer(0, "output layer");
CHECK(outputLayer);
concatLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0));
CHECK(splitterLayer->GetNumOutputSlots() == 2);
CHECK(splitterLayer->GetOutputSlot(0).GetConnection(0) == &softmaxLayer1->GetInputSlot(0));
CHECK(&splitterLayer->GetOutputSlot(0) == softmaxLayer1->GetInputSlot(0).GetConnection());
CHECK(splitterLayer->GetOutputSlot(1).GetConnection(0) == &softmaxLayer2->GetInputSlot(0));
CHECK(&splitterLayer->GetOutputSlot(1) == softmaxLayer2->GetInputSlot(0).GetConnection());
CHECK(concatLayer->GetNumInputSlots() == 2);
CHECK(softmaxLayer1->GetOutputSlot(0).GetConnection(0) == &concatLayer->GetInputSlot(0));
CHECK(&softmaxLayer1->GetOutputSlot(0) == concatLayer->GetInputSlot(0).GetConnection());
CHECK(softmaxLayer2->GetOutputSlot(0).GetConnection(0) == &concatLayer->GetInputSlot(1));
CHECK(&softmaxLayer2->GetOutputSlot(0) == concatLayer->GetInputSlot(1).GetConnection());
}
TEST_CASE("NetworkModification_SplitterAddition")
{
armnn::NetworkImpl net;
// Adds an input layer and an input tensor descriptor.
armnn::IConnectableLayer* layer = net.AddInputLayer(0, "input layer");
CHECK(layer);
// Adds a splitter layer.
armnn::ViewsDescriptor splitterDesc(2,4);
armnn::IConnectableLayer* const splitterLayer = net.AddSplitterLayer(splitterDesc, "splitter layer");
CHECK(splitterLayer);
layer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0));
// Adds a softmax layer 1.
armnn::SoftmaxDescriptor softmaxDescriptor;
armnn::IConnectableLayer* const softmax1Layer = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_1");
CHECK(softmax1Layer);
splitterLayer->GetOutputSlot(0).Connect(softmax1Layer->GetInputSlot(0));
// Adds a softmax layer 2.
armnn::IConnectableLayer* const softmax2Layer = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_2");
CHECK(softmax2Layer);
splitterLayer->GetOutputSlot(1).Connect(softmax2Layer->GetInputSlot(0));
// Adds addition layer.
layer = net.AddAdditionLayer("add layer");
CHECK(layer);
softmax1Layer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
softmax2Layer->GetOutputSlot(0).Connect(layer->GetInputSlot(1));
// Adds an output layer.
armnn::IConnectableLayer* prevLayer = layer;
layer = net.AddOutputLayer(0, "output layer");
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
CHECK(layer);
}
TEST_CASE("NetworkModification_SplitterMultiplication")
{
armnn::NetworkImpl net;
// Adds an input layer and an input tensor descriptor.
armnn::IConnectableLayer* layer = net.AddInputLayer(0, "input layer");
CHECK(layer);
// Adds a splitter layer.
armnn::ViewsDescriptor splitterDesc(2,4);
armnn::IConnectableLayer* const splitterLayer = net.AddSplitterLayer(splitterDesc, "splitter layer");
CHECK(splitterLayer);
layer->GetOutputSlot(0).Connect(splitterLayer->GetInputSlot(0));
// Adds a softmax layer 1.
armnn::SoftmaxDescriptor softmaxDescriptor;
armnn::IConnectableLayer* const softmax1Layer = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_1");
CHECK(softmax1Layer);
splitterLayer->GetOutputSlot(0).Connect(softmax1Layer->GetInputSlot(0));
// Adds a softmax layer 2.
armnn::IConnectableLayer* const softmax2Layer = net.AddSoftmaxLayer(softmaxDescriptor, "softmax_2");
CHECK(softmax2Layer);
splitterLayer->GetOutputSlot(1).Connect(softmax2Layer->GetInputSlot(0));
// Adds multiplication layer.
layer = net.AddMultiplicationLayer("multiplication layer");
CHECK(layer);
softmax1Layer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
softmax2Layer->GetOutputSlot(0).Connect(layer->GetInputSlot(1));
// Adds an output layer.
armnn::IConnectableLayer* prevLayer = layer;
layer = net.AddOutputLayer(0, "output layer");
CHECK(layer);
prevLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
}
TEST_CASE("Network_AddQuantize")
{
struct Test : public armnn::IStrategy
{
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
{
armnn::IgnoreUnused(descriptor, constants, id);
switch (layer->GetType())
{
case armnn::LayerType::Input: break;
case armnn::LayerType::Output: break;
case armnn::LayerType::Quantize:
{
m_Visited = true;
CHECK(layer);
std::string expectedName = std::string("quantize");
CHECK(std::string(layer->GetName()) == expectedName);
CHECK(std::string(name) == expectedName);
CHECK(layer->GetNumInputSlots() == 1);
CHECK(layer->GetNumOutputSlots() == 1);
const armnn::TensorInfo& infoIn = layer->GetInputSlot(0).GetConnection()->GetTensorInfo();
CHECK((infoIn.GetDataType() == armnn::DataType::Float32));
const armnn::TensorInfo& infoOut = layer->GetOutputSlot(0).GetTensorInfo();
CHECK((infoOut.GetDataType() == armnn::DataType::QAsymmU8));
break;
}
default:
{
// nothing
}
}
}
bool m_Visited = false;
};
auto graph = armnn::INetwork::Create();
auto input = graph->AddInputLayer(0, "input");
auto quantize = graph->AddQuantizeLayer("quantize");
auto output = graph->AddOutputLayer(1, "output");
input->GetOutputSlot(0).Connect(quantize->GetInputSlot(0));
quantize->GetOutputSlot(0).Connect(output->GetInputSlot(0));
armnn::TensorInfo infoIn({3,1}, armnn::DataType::Float32);
input->GetOutputSlot(0).SetTensorInfo(infoIn);
armnn::TensorInfo infoOut({3,1}, armnn::DataType::QAsymmU8);
quantize->GetOutputSlot(0).SetTensorInfo(infoOut);
Test testQuantize;
graph->ExecuteStrategy(testQuantize);
CHECK(testQuantize.m_Visited == true);
}
TEST_CASE("Network_AddMerge")
{
struct Test : public armnn::IStrategy
{
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
{
armnn::IgnoreUnused(descriptor, constants, id);
switch (layer->GetType())
{
case armnn::LayerType::Input: break;
case armnn::LayerType::Output: break;
case armnn::LayerType::Merge:
{
m_Visited = true;
CHECK(layer);
std::string expectedName = std::string("merge");
CHECK(std::string(layer->GetName()) == expectedName);
CHECK(std::string(name) == expectedName);
CHECK(layer->GetNumInputSlots() == 2);
CHECK(layer->GetNumOutputSlots() == 1);
const armnn::TensorInfo& infoIn0 = layer->GetInputSlot(0).GetConnection()->GetTensorInfo();
CHECK((infoIn0.GetDataType() == armnn::DataType::Float32));
const armnn::TensorInfo& infoIn1 = layer->GetInputSlot(1).GetConnection()->GetTensorInfo();
CHECK((infoIn1.GetDataType() == armnn::DataType::Float32));
const armnn::TensorInfo& infoOut = layer->GetOutputSlot(0).GetTensorInfo();
CHECK((infoOut.GetDataType() == armnn::DataType::Float32));
break;
}
default:
{
// nothing
}
}
}
bool m_Visited = false;
};
armnn::INetworkPtr network = armnn::INetwork::Create();
armnn::IConnectableLayer* input0 = network->AddInputLayer(0);
armnn::IConnectableLayer* input1 = network->AddInputLayer(1);
armnn::IConnectableLayer* merge = network->AddMergeLayer("merge");
armnn::IConnectableLayer* output = network->AddOutputLayer(0);
input0->GetOutputSlot(0).Connect(merge->GetInputSlot(0));
input1->GetOutputSlot(0).Connect(merge->GetInputSlot(1));
merge->GetOutputSlot(0).Connect(output->GetInputSlot(0));
const armnn::TensorInfo info({3,1}, armnn::DataType::Float32);
input0->GetOutputSlot(0).SetTensorInfo(info);
input1->GetOutputSlot(0).SetTensorInfo(info);
merge->GetOutputSlot(0).SetTensorInfo(info);
Test testMerge;
network->ExecuteStrategy(testMerge);
CHECK(testMerge.m_Visited == true);
}
TEST_CASE("StandInLayerNetworkTest")
{
// Create a simple network with a StandIn some place in it.
armnn::NetworkImpl net;
auto input = net.AddInputLayer(0);
// Add some valid layer.
auto floor = net.AddFloorLayer("Floor");
// Add a standin layer
armnn::StandInDescriptor standInDescriptor;
standInDescriptor.m_NumInputs = 1;
standInDescriptor.m_NumOutputs = 1;
auto standIn = net.AddStandInLayer(standInDescriptor, "StandIn");
// Finally the output.
auto output = net.AddOutputLayer(0);
// Connect up the layers
input->GetOutputSlot(0).Connect(floor->GetInputSlot(0));
floor->GetOutputSlot(0).Connect(standIn->GetInputSlot(0));
standIn->GetOutputSlot(0).Connect(output->GetInputSlot(0));
// Check that the layer is there.
CHECK(GraphHasNamedLayer(net.GetGraph(), "StandIn"));
// Check that it is connected as expected.
CHECK(input->GetOutputSlot(0).GetConnection(0) == &floor->GetInputSlot(0));
CHECK(floor->GetOutputSlot(0).GetConnection(0) == &standIn->GetInputSlot(0));
CHECK(standIn->GetOutputSlot(0).GetConnection(0) == &output->GetInputSlot(0));
}
TEST_CASE("StandInLayerSingleInputMultipleOutputsNetworkTest")
{
// Another test with one input and two outputs on the StandIn layer.
armnn::NetworkImpl net;
// Create the input.
auto input = net.AddInputLayer(0);
// Add a standin layer
armnn::StandInDescriptor standInDescriptor;
standInDescriptor.m_NumInputs = 1;
standInDescriptor.m_NumOutputs = 2;
auto standIn = net.AddStandInLayer(standInDescriptor, "StandIn");
// Add two outputs.
auto output0 = net.AddOutputLayer(0);
auto output1 = net.AddOutputLayer(1);
// Connect up the layers
input->GetOutputSlot(0).Connect(standIn->GetInputSlot(0));
// Connect the two outputs of the Standin to the two outputs.
standIn->GetOutputSlot(0).Connect(output0->GetInputSlot(0));
standIn->GetOutputSlot(1).Connect(output1->GetInputSlot(0));
// Check that the layer is there.
CHECK(GraphHasNamedLayer(net.GetGraph(), "StandIn"));
// Check that it is connected as expected.
CHECK(input->GetOutputSlot(0).GetConnection(0) == &standIn->GetInputSlot(0));
CHECK(standIn->GetOutputSlot(0).GetConnection(0) == &output0->GetInputSlot(0));
CHECK(standIn->GetOutputSlot(1).GetConnection(0) == &output1->GetInputSlot(0));
}
TEST_CASE("ObtainConv2DDescriptorFromIConnectableLayer")
{
armnn::NetworkImpl net;
unsigned int dims[] = { 10,1,1,1 };
std::vector<float> convWeightsData(10);
armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float32, 0.0f, 0, true), convWeightsData);
armnn::Convolution2dDescriptor convDesc2d;
convDesc2d.m_PadLeft = 2;
convDesc2d.m_PadRight = 3;
convDesc2d.m_PadTop = 4;
convDesc2d.m_PadBottom = 5;
convDesc2d.m_StrideX = 2;
convDesc2d.m_StrideY = 1;
convDesc2d.m_DilationX = 3;
convDesc2d.m_DilationY = 3;
convDesc2d.m_BiasEnabled = false;
convDesc2d.m_DataLayout = armnn::DataLayout::NCHW;
armnn::IConnectableLayer* const convLayer = net.AddConvolution2dLayer(convDesc2d,
weights,
armnn::EmptyOptional(),
"conv layer");
CHECK(convLayer);
const armnn::BaseDescriptor& descriptor = convLayer->GetParameters();
CHECK(descriptor.IsNull() == false);
const armnn::Convolution2dDescriptor& originalDescriptor =
static_cast<const armnn::Convolution2dDescriptor&>(descriptor);
CHECK(originalDescriptor.m_PadLeft == 2);
CHECK(originalDescriptor.m_PadRight == 3);
CHECK(originalDescriptor.m_PadTop == 4);
CHECK(originalDescriptor.m_PadBottom == 5);
CHECK(originalDescriptor.m_StrideX == 2);
CHECK(originalDescriptor.m_StrideY == 1);
CHECK(originalDescriptor.m_DilationX == 3);
CHECK(originalDescriptor.m_DilationY == 3);
CHECK(originalDescriptor.m_BiasEnabled == false);
CHECK(originalDescriptor.m_DataLayout == armnn::DataLayout::NCHW);
}
TEST_CASE("CheckNullDescriptor")
{
armnn::NetworkImpl net;
armnn::IConnectableLayer* const addLayer = net.AddAdditionLayer();
CHECK(addLayer);
const armnn::BaseDescriptor& descriptor = addLayer->GetParameters();
// additional layer has no descriptor so a NullDescriptor will be returned
CHECK(descriptor.IsNull() == true);
}
}