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author | Keith Davis <keith.davis@arm.com> | 2022-04-07 11:32:00 +0100 |
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committer | Keith Davis <keith.davis@arm.com> | 2022-05-16 16:08:54 +0100 |
commit | b4dd5cc86d4eb841de670f0f102ede599e0d9c40 (patch) | |
tree | 77857cf739baecaf63701b66c1a2646b7930a834 /src/armnnSerializer/test/SerializerTests.cpp | |
parent | b86ec6641b4b06ccddad5eebbc21010d6184fe79 (diff) | |
download | armnn-b4dd5cc86d4eb841de670f0f102ede599e0d9c40.tar.gz |
IVGCVSW-6124 ConstTensorsAsInput: Conv2d - FrontEnd
* Update Front-end and Tools.
* Updated Serializer, Deserializer and unit tests to reflect this.
* Updated TfLiteDelegate, TfLiteParser and OnnxParser.
* Updated Ref.
* Fixed resulting Neon / CL tests
* Unified optimizers for conv2d ops
* Optimizer Fix - Fp32ToBf16
* Partial implementation for ACL backends to fix VTS failures
!android-nn-driver:7477
Signed-off-by: Keith Davis <keith.davis@arm.com>
Change-Id: I5fb18877f7ee32643e15a9818945356274bb401b
Diffstat (limited to 'src/armnnSerializer/test/SerializerTests.cpp')
-rw-r--r-- | src/armnnSerializer/test/SerializerTests.cpp | 152 |
1 files changed, 147 insertions, 5 deletions
diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index 278715bfa4..a042939265 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -333,6 +333,39 @@ TEST_CASE("SerializeConstant") deserializedNetwork->ExecuteStrategy(verifier); } +using Convolution2dDescriptor = armnn::Convolution2dDescriptor; +class Convolution2dLayerVerifier : public LayerVerifierBaseWithDescriptor<Convolution2dDescriptor> +{ +public: + Convolution2dLayerVerifier(const std::string& layerName, + const std::vector<armnn::TensorInfo>& inputInfos, + const std::vector<armnn::TensorInfo>& outputInfos, + const Convolution2dDescriptor& descriptor) + : LayerVerifierBaseWithDescriptor<Convolution2dDescriptor>(layerName, inputInfos, outputInfos, descriptor) {} + + 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(constants, id); + switch (layer->GetType()) + { + case armnn::LayerType::Input: break; + case armnn::LayerType::Output: break; + case armnn::LayerType::Constant: break; + default: + { + VerifyNameAndConnections(layer, name); + const Convolution2dDescriptor& layerDescriptor = + static_cast<const Convolution2dDescriptor&>(descriptor); + CHECK(layerDescriptor.m_BiasEnabled == m_Descriptor.m_BiasEnabled); + } + } + } +}; + TEST_CASE("SerializeConvolution2d") { const std::string layerName("convolution2d"); @@ -362,11 +395,13 @@ TEST_CASE("SerializeConvolution2d") armnn::INetworkPtr network = armnn::INetwork::Create(); armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); + ARMNN_NO_DEPRECATE_WARN_BEGIN armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(descriptor, weights, armnn::Optional<armnn::ConstTensor>(biases), layerName.c_str()); + ARMNN_NO_DEPRECATE_WARN_END armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); @@ -378,9 +413,7 @@ TEST_CASE("SerializeConvolution2d") armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); CHECK(deserializedNetwork); - const std::vector<armnn::ConstTensor>& constants {weights, biases}; - LayerVerifierBaseWithDescriptorAndConstants<armnn::Convolution2dDescriptor> verifier( - layerName, {inputInfo}, {outputInfo}, descriptor, constants); + Convolution2dLayerVerifier verifier(layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor); deserializedNetwork->ExecuteStrategy(verifier); } @@ -417,25 +450,134 @@ TEST_CASE("SerializeConvolution2dWithPerAxisParams") armnn::INetworkPtr network = armnn::INetwork::Create(); armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); + ARMNN_NO_DEPRECATE_WARN_BEGIN armnn::IConnectableLayer* const convLayer = network->AddConvolution2dLayer(descriptor, weights, armnn::Optional<armnn::ConstTensor>(biases), layerName.c_str()); + ARMNN_NO_DEPRECATE_WARN_END + armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); + + inputLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(0)); + convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); + + inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); + convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); + + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); + CHECK(deserializedNetwork); + + Convolution2dLayerVerifier verifier(layerName, {inputInfo, kernelInfo, biasInfo}, {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); + + 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<Convolution2dDescriptor> verifier( - layerName, {inputInfo}, {outputInfo}, descriptor, constants); + LayerVerifierBaseWithDescriptorAndConstants<armnn::Convolution2dDescriptor> verifier( + layerName, {inputInfo, weightsInfo, biasesInfo}, {outputInfo}, descriptor, constants); + deserializedNetwork->ExecuteStrategy(verifier); } |