diff options
Diffstat (limited to 'src/armnnSerializer/test/SerializerTests.cpp')
| -rw-r--r-- | src/armnnSerializer/test/SerializerTests.cpp | 89 |
1 files changed, 77 insertions, 12 deletions
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index a765290de8..278715bfa4 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -553,11 +553,8 @@ TEST_CASE("SerializeDepthwiseConvolution2d") armnn::INetworkPtr network = armnn::INetwork::Create(); armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); - armnn::IConnectableLayer* const depthwiseConvLayer = - network->AddDepthwiseConvolution2dLayer(descriptor, - weights, - armnn::Optional<armnn::ConstTensor>(biases), - layerName.c_str()); + armnn::IConnectableLayer* const depthwiseConvLayer = network->AddDepthwiseConvolution2dLayer(descriptor, + layerName.c_str()); armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); @@ -566,12 +563,20 @@ TEST_CASE("SerializeDepthwiseConvolution2d") inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); + armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights); + weightsLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(1u)); + weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.GetInfo()); + + armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases); + biasLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(2u)); + biasLayer->GetOutputSlot(0).SetTensorInfo(biases.GetInfo()); + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); CHECK(deserializedNetwork); const std::vector<armnn::ConstTensor>& constants {weights, biases}; LayerVerifierBaseWithDescriptorAndConstants<armnn::DepthwiseConvolution2dDescriptor> verifier( - layerName, {inputInfo}, {outputInfo}, descriptor, constants); + layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants); deserializedNetwork->ExecuteStrategy(verifier); } @@ -610,11 +615,8 @@ TEST_CASE("SerializeDepthwiseConvolution2dWithPerAxisParams") armnn::INetworkPtr network = armnn::INetwork::Create(); armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); - armnn::IConnectableLayer* const depthwiseConvLayer = - network->AddDepthwiseConvolution2dLayer(descriptor, - weights, - armnn::Optional<armnn::ConstTensor>(biases), - layerName.c_str()); + armnn::IConnectableLayer* const depthwiseConvLayer = network->AddDepthwiseConvolution2dLayer(descriptor, + layerName.c_str()); armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); inputLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(0)); @@ -623,12 +625,75 @@ TEST_CASE("SerializeDepthwiseConvolution2dWithPerAxisParams") inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); depthwiseConvLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); + armnn::IConnectableLayer* const weightsLayer = network->AddConstantLayer(weights); + weightsLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(1u)); + weightsLayer->GetOutputSlot(0).SetTensorInfo(weights.GetInfo()); + + armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases); + biasLayer->GetOutputSlot(0).Connect(depthwiseConvLayer->GetInputSlot(2u)); + biasLayer->GetOutputSlot(0).SetTensorInfo(biases.GetInfo()); + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); CHECK(deserializedNetwork); const std::vector<armnn::ConstTensor>& constants {weights, biases}; LayerVerifierBaseWithDescriptorAndConstants<armnn::DepthwiseConvolution2dDescriptor> verifier( - layerName, {inputInfo}, {outputInfo}, descriptor, constants); + layerName, {inputInfo, kernelInfo, biasInfo}, {outputInfo}, descriptor, constants); + deserializedNetwork->ExecuteStrategy(verifier); +} + +TEST_CASE("SerializeDepthwiseConvolution2dWeightsAndBiasesAsConstantLayers") +{ + const std::string layerName("depthwiseConvolution2d"); + 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::DepthwiseConvolution2dDescriptor 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->AddDepthwiseConvolution2dLayer(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::DepthwiseConvolution2dDescriptor> verifier( + layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants); + deserializedNetwork->ExecuteStrategy(verifier); } |