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-rw-r--r--src/armnn/test/ConstTensorLayerVisitor.cpp45
-rw-r--r--src/armnn/test/CreateWorkload.hpp10
-rw-r--r--src/armnn/test/NetworkTests.cpp6
-rw-r--r--src/armnn/test/QuantizerTest.cpp30
4 files changed, 52 insertions, 39 deletions
diff --git a/src/armnn/test/ConstTensorLayerVisitor.cpp b/src/armnn/test/ConstTensorLayerVisitor.cpp
index 5b77ddeb97..e17ee46c81 100644
--- a/src/armnn/test/ConstTensorLayerVisitor.cpp
+++ b/src/armnn/test/ConstTensorLayerVisitor.cpp
@@ -128,7 +128,7 @@ BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)
Network net;
- IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights);
+ IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, EmptyOptional());
layer->Accept(visitor);
}
@@ -152,7 +152,7 @@ BOOST_AUTO_TEST_CASE(CheckNamedConvolution2dLayer)
Network net;
- IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, layerName);
+ IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, EmptyOptional(), layerName);
layer->Accept(visitor);
}
@@ -175,12 +175,13 @@ BOOST_AUTO_TEST_CASE(CheckConvolution2dLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestConvolution2dLayerVisitor visitor(descriptor, weights, Optional<ConstTensor>(biases));
+ TestConvolution2dLayerVisitor visitor(descriptor, weights, optionalBiases);
Network net;
- IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, biases);
+ IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, optionalBiases);
layer->Accept(visitor);
}
@@ -204,12 +205,13 @@ BOOST_AUTO_TEST_CASE(CheckNamedConvolution2dLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestConvolution2dLayerVisitor visitor(descriptor, weights, Optional<ConstTensor>(biases), layerName);
+ TestConvolution2dLayerVisitor visitor(descriptor, weights, optionalBiases, layerName);
Network net;
- IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, biases, layerName);
+ IConnectableLayer* const layer = net.AddConvolution2dLayer(descriptor, weights, optionalBiases, layerName);
layer->Accept(visitor);
}
@@ -232,7 +234,7 @@ BOOST_AUTO_TEST_CASE(CheckDepthwiseConvolution2dLayer)
Network net;
- IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights);
+ IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, EmptyOptional());
layer->Accept(visitor);
}
@@ -256,7 +258,10 @@ BOOST_AUTO_TEST_CASE(CheckNamedDepthwiseConvolution2dLayer)
Network net;
- IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, layerName);
+ IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor,
+ weights,
+ EmptyOptional(),
+ layerName);
layer->Accept(visitor);
}
@@ -279,12 +284,13 @@ BOOST_AUTO_TEST_CASE(CheckDepthwiseConvolution2dLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestDepthwiseConvolution2dLayerVisitor visitor(descriptor, weights, Optional<ConstTensor>(biases));
+ TestDepthwiseConvolution2dLayerVisitor visitor(descriptor, weights, optionalBiases);
Network net;
- IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, biases);
+ IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, optionalBiases);
layer->Accept(visitor);
}
@@ -308,12 +314,13 @@ BOOST_AUTO_TEST_CASE(CheckNamedDepthwiseConvolution2dLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestDepthwiseConvolution2dLayerVisitor visitor(descriptor, weights, Optional<ConstTensor>(biases), layerName);
+ TestDepthwiseConvolution2dLayerVisitor visitor(descriptor, weights, optionalBiases, layerName);
Network net;
- IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, biases, layerName);
+ IConnectableLayer* const layer = net.AddDepthwiseConvolution2dLayer(descriptor, weights, optionalBiases, layerName);
layer->Accept(visitor);
}
@@ -330,7 +337,7 @@ BOOST_AUTO_TEST_CASE(CheckFullyConnectedLayer)
Network net;
- IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights);
+ IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, EmptyOptional());
layer->Accept(visitor);
}
@@ -348,7 +355,7 @@ BOOST_AUTO_TEST_CASE(CheckNamedFullyConnectedLayer)
Network net;
- IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, layerName);
+ IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, EmptyOptional(), layerName);
layer->Accept(visitor);
}
@@ -365,12 +372,13 @@ BOOST_AUTO_TEST_CASE(CheckFullyConnectedLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestFullyConnectedLayerVistor visitor(descriptor, weights, Optional<ConstTensor>(biases));
+ TestFullyConnectedLayerVistor visitor(descriptor, weights, optionalBiases);
Network net;
- IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, biases);
+ IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, optionalBiases);
layer->Accept(visitor);
}
@@ -388,12 +396,13 @@ BOOST_AUTO_TEST_CASE(CheckNamedFullyConnectedLayerWithBiases)
std::vector<float> biasData = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0};
std::vector<unsigned int> biasDimensions = {1, 1, 3, 3};
ConstTensor biases(TensorInfo(4, biasDimensions.data(), DataType::Float32), biasData);
+ Optional<ConstTensor> optionalBiases(biases);
- TestFullyConnectedLayerVistor visitor(descriptor, weights, Optional<ConstTensor>(biases), layerName);
+ TestFullyConnectedLayerVistor visitor(descriptor, weights, optionalBiases, layerName);
Network net;
- IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, biases, layerName);
+ IConnectableLayer* const layer = net.AddFullyConnectedLayer(descriptor, weights, optionalBiases, layerName);
layer->Accept(visitor);
}
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp
index a68a6e3f42..1193ab721e 100644
--- a/src/armnn/test/CreateWorkload.hpp
+++ b/src/armnn/test/CreateWorkload.hpp
@@ -1148,12 +1148,18 @@ std::pair<armnn::IOptimizedNetworkPtr, std::unique_ptr<PreCompiledWorkload>> Cre
armnn::ConstTensor biases(biasTensorInfo, biasData);
// Create convolution layer with biases
- convLayer = net.AddConvolution2dLayer(convDesc2d, weights, biases, convLayerName.c_str());
+ convLayer = net.AddConvolution2dLayer(convDesc2d,
+ weights,
+ Optional<ConstTensor>(biases),
+ convLayerName.c_str());
}
else
{
// Create convolution layer without biases
- convLayer = net.AddConvolution2dLayer(convDesc2d, weights, convLayerName.c_str());
+ convLayer = net.AddConvolution2dLayer(convDesc2d,
+ weights,
+ EmptyOptional(),
+ convLayerName.c_str());
}
BOOST_TEST(convLayer);
diff --git a/src/armnn/test/NetworkTests.cpp b/src/armnn/test/NetworkTests.cpp
index 155304be36..47fd67b8d4 100644
--- a/src/armnn/test/NetworkTests.cpp
+++ b/src/armnn/test/NetworkTests.cpp
@@ -78,7 +78,10 @@ BOOST_AUTO_TEST_CASE(NetworkModification)
armnn::ConstTensor weights(armnn::TensorInfo(4, dims, armnn::DataType::Float32), convWeightsData);
armnn::Convolution2dDescriptor convDesc2d;
- armnn::IConnectableLayer* const convLayer = net.AddConvolution2dLayer(convDesc2d, weights, "conv layer");
+ armnn::IConnectableLayer* const convLayer = net.AddConvolution2dLayer(convDesc2d,
+ weights,
+ armnn::EmptyOptional(),
+ "conv layer");
BOOST_TEST(convLayer);
inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0));
@@ -86,6 +89,7 @@ BOOST_AUTO_TEST_CASE(NetworkModification)
armnn::FullyConnectedDescriptor fullyConnectedDesc;
armnn::IConnectableLayer* const fullyConnectedLayer = net.AddFullyConnectedLayer(fullyConnectedDesc,
weights,
+ armnn::EmptyOptional(),
"fully connected");
BOOST_TEST(fullyConnectedLayer);
diff --git a/src/armnn/test/QuantizerTest.cpp b/src/armnn/test/QuantizerTest.cpp
index 4f22317651..f2c739d274 100644
--- a/src/armnn/test/QuantizerTest.cpp
+++ b/src/armnn/test/QuantizerTest.cpp
@@ -686,16 +686,14 @@ INetworkPtr CreateNetworkWithFullyConnectedLayer(const bool biasEnabled,
// Add the layers
IConnectableLayer* input0 = network->AddInputLayer(0);
IConnectableLayer* fullyConnected;
+ Optional<ConstTensor> optionalBias;
+ std::vector<float> biasData{10.0f, 20.0f, 30.0f};
if (desc.m_BiasEnabled)
{
- std::vector<float> biasData{10.0f, 20.0f, 30.0f};
ConstTensor bias(info, biasData);
- fullyConnected = network->AddFullyConnectedLayer(desc, weights, bias);
- }
- else
- {
- fullyConnected = network->AddFullyConnectedLayer(desc, weights);
+ optionalBias = Optional<ConstTensor>(bias);
}
+ fullyConnected = network->AddFullyConnectedLayer(desc, weights, optionalBias);
IConnectableLayer* output = network->AddOutputLayer(1);
// Establish connections
@@ -814,16 +812,14 @@ void TestQuantizeConvolution2d(bool useBiases)
// Add the layers
IConnectableLayer* input0 = network->AddInputLayer(0);
IConnectableLayer* conv2d;
+ Optional<ConstTensor> optionalBiases;
+ std::vector<float> biasesData{-1.0f, 1.5f, 2.0f};
if (useBiases)
{
- std::vector<float> biasesData{-1.0f, 1.5f, 2.0f};
ConstTensor biases(info, biasesData);
- conv2d = network->AddConvolution2dLayer(descriptor, weights, biases);
- }
- else
- {
- conv2d = network->AddConvolution2dLayer(descriptor, weights);
+ optionalBiases = Optional<ConstTensor>(biases);
}
+ conv2d = network->AddConvolution2dLayer(descriptor, weights, optionalBiases);
IConnectableLayer* output = network->AddOutputLayer(1);
// Establish connections
@@ -902,16 +898,14 @@ void TestQuantizeDepthwiseConvolution2d(bool useBiases)
// Add the layers
IConnectableLayer* input0 = network->AddInputLayer(0);
IConnectableLayer* depthwiseConv2d;
+ Optional<ConstTensor> optionalBiases;
+ std::vector<float> biasesData{-1.0f, 1.5f, 2.0f};
if (useBiases)
{
- std::vector<float> biasesData{-1.0f, 1.5f, 2.0f};
ConstTensor biases(info, biasesData);
- depthwiseConv2d = network->AddDepthwiseConvolution2dLayer(descriptor, weights, biases);
- }
- else
- {
- depthwiseConv2d = network->AddDepthwiseConvolution2dLayer(descriptor, weights);
+ optionalBiases = Optional<ConstTensor>(biases);
}
+ depthwiseConv2d = network->AddDepthwiseConvolution2dLayer(descriptor, weights, optionalBiases);
IConnectableLayer* output = network->AddOutputLayer(1);
// Establish connections
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 15:09:59 +0000