diff options
Diffstat (limited to 'src/armnnSerializer')
-rw-r--r-- | src/armnnSerializer/test/SerializerTests.cpp | 55 |
1 files changed, 1 insertions, 54 deletions
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index a042939265..43a8aae9a7 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -417,7 +417,7 @@ TEST_CASE("SerializeConvolution2d") deserializedNetwork->ExecuteStrategy(verifier); } -TEST_CASE("SerializeConvolution2dWithPerAxisParams") +TEST_CASE("SerializeConvolution2dWithPerAxisParamsTestDeprecatedMethod") { using namespace armnn; @@ -521,59 +521,6 @@ TEST_CASE("SerializeConvolution2dWeightsAndBiasesAsConstantLayers") armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); CHECK(deserializedNetwork); - Convolution2dLayerVerifier verifier(layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor); - - deserializedNetwork->ExecuteStrategy(verifier); -} - -TEST_CASE("SerializeConvolution2dWeightsAndBiasesAsConstantLayers") -{ - const std::string layerName("convolution2d"); - const armnn::TensorInfo inputInfo ({ 1, 5, 5, 1 }, armnn::DataType::Float32); - const armnn::TensorInfo outputInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32); - - const armnn::TensorInfo weightsInfo({ 1, 3, 3, 1 }, armnn::DataType::Float32, 0.0f, 0, true); - const armnn::TensorInfo biasesInfo ({ 1 }, armnn::DataType::Float32, 0.0f, 0, true); - - std::vector<float> weightsData = GenerateRandomData<float>(weightsInfo.GetNumElements()); - armnn::ConstTensor weights(weightsInfo, weightsData); - - std::vector<float> biasesData = GenerateRandomData<float>(biasesInfo.GetNumElements()); - armnn::ConstTensor biases(biasesInfo, biasesData); - - armnn::Convolution2dDescriptor descriptor; - descriptor.m_PadLeft = 1; - descriptor.m_PadRight = 1; - descriptor.m_PadTop = 1; - descriptor.m_PadBottom = 1; - descriptor.m_StrideX = 2; - descriptor.m_StrideY = 2; - descriptor.m_DilationX = 2; - descriptor.m_DilationY = 2; - descriptor.m_BiasEnabled = true; - descriptor.m_DataLayout = armnn::DataLayout::NHWC; - - armnn::INetworkPtr network = armnn::INetwork::Create(); - armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); - armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights, "Weights"); - armnn::IConnectableLayer* const biasesLayer = network->AddConstantLayer(biases, "Biases"); - armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(descriptor, - layerName.c_str()); - armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); - - inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); - weightsLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(1)); - biasesLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2)); - convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); - - inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); - weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo); - biasesLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo); - convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); - - armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); - CHECK(deserializedNetwork); - const std::vector<armnn::ConstTensor>& constants {weights, biases}; LayerVerifierBaseWithDescriptorAndConstants<armnn::Convolution2dDescriptor> verifier( layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants); |