diff options
Diffstat (limited to 'src')
-rw-r--r-- | src/armnn/Network.cpp | 25 | ||||
-rw-r--r-- | src/armnn/layers/Convolution2dLayer.hpp | 1 | ||||
-rw-r--r-- | src/armnn/test/GraphTests.cpp | 14 | ||||
-rw-r--r-- | src/armnnSerializer/test/SerializerTests.cpp | 30 | ||||
-rw-r--r-- | src/backends/backendsCommon/WorkloadData.cpp | 48 |
5 files changed, 22 insertions, 96 deletions
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp index c4869fae04..3508ee882e 100644 --- a/src/armnn/Network.cpp +++ b/src/armnn/Network.cpp @@ -88,19 +88,6 @@ IConnectableLayer* INetwork::AddConvolution2dLayer(const Convolution2dDescriptor return pNetworkImpl->AddConvolution2dLayer(convolution2dDescriptor, name); } -ARMNN_NO_DEPRECATE_WARN_BEGIN -IConnectableLayer* INetwork::AddConvolution2dLayer(const Convolution2dDescriptor& convolution2dDescriptor, - const ConstTensor& weights, - const Optional<ConstTensor>& biases, - const char* name) -{ - return pNetworkImpl->AddConvolution2dLayer(convolution2dDescriptor, - weights, - armnn::Optional<ConstTensor>(biases), - name); -} -ARMNN_NO_DEPRECATE_WARN_END - IConnectableLayer* INetwork::AddConvolution3dLayer(const Convolution3dDescriptor& convolution3dDescriptor, const char* name) { @@ -123,18 +110,6 @@ IConnectableLayer* INetwork::AddDepthwiseConvolution2dLayer( } -ARMNN_NO_DEPRECATE_WARN_BEGIN -IConnectableLayer* INetwork::AddDepthwiseConvolution2dLayer( - const DepthwiseConvolution2dDescriptor& convolution2dDescriptor, - const ConstTensor& weights, - const Optional<ConstTensor>& biases, - const char* name) -{ - return pNetworkImpl->AddDepthwiseConvolution2dLayer(convolution2dDescriptor, weights, biases, name); -} -ARMNN_NO_DEPRECATE_WARN_END - - IConnectableLayer* INetwork::AddDequantizeLayer(const char* name) { return pNetworkImpl->AddDequantizeLayer(name); diff --git a/src/armnn/layers/Convolution2dLayer.hpp b/src/armnn/layers/Convolution2dLayer.hpp index 57999709cd..185a67252d 100644 --- a/src/armnn/layers/Convolution2dLayer.hpp +++ b/src/armnn/layers/Convolution2dLayer.hpp @@ -44,7 +44,6 @@ public: /// @return A vector to the inferred output shape. std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override; - void ExecuteStrategy(IStrategy& strategy) const override; void SerializeLayerParameters(ParameterStringifyFunction& fn) const override; diff --git a/src/armnn/test/GraphTests.cpp b/src/armnn/test/GraphTests.cpp index 95421c5683..eea7ae824a 100644 --- a/src/armnn/test/GraphTests.cpp +++ b/src/armnn/test/GraphTests.cpp @@ -632,13 +632,13 @@ TEST_CASE("IConnectableLayerConstantTensorsByRef") TensorInfo weightsInfo = constInfo; ConstTensor weights(weightsInfo, weightData); DepthwiseConvolution2dDescriptor desc; - ARMNN_NO_DEPRECATE_WARN_BEGIN - // GetConstantTensorsByRef() returns {m_Weights, m_Bias} so we need to use the old AddDepthwiseConvolution2dLayer() - const auto depthwiseLayer = net->AddDepthwiseConvolution2dLayer(desc, weights, EmptyOptional(), "Depthwise"); - ARMNN_NO_DEPRECATE_WARN_END - const void* resultData = depthwiseLayer->GetConstantTensorsByRef()[0].get()->GetConstTensor<void>(); - auto resultValue = reinterpret_cast<const uint8_t*>(resultData); - CHECK(resultValue[0] == 3); + + const auto weightsLayer = net->AddConstantLayer(weights); + + const void* resultDataWeights = weightsLayer->GetConstantTensorsByRef()[0].get()->GetConstTensor<void>(); + auto resultValueWeights = reinterpret_cast<const uint8_t*>(resultDataWeights); + CHECK(resultValueWeights[0] == 3); + } } diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index a568bf15c9..3573a8195c 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -436,19 +436,19 @@ 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 weightsLayer = network->AddConstantLayer(weights, "weights"); + armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(biases, "bias"); + 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)); + biasLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2)); convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); + weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo); + biasLayer->GetOutputSlot(0).SetTensorInfo(biasesInfo); convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); @@ -458,7 +458,7 @@ TEST_CASE("SerializeConvolution2d") deserializedNetwork->ExecuteStrategy(verifier); } -TEST_CASE("SerializeConvolution2dWithPerAxisParamsTestDeprecatedMethod") +TEST_CASE("SerializeConvolution2dWithPerAxisParams") { using namespace armnn; @@ -491,19 +491,19 @@ TEST_CASE("SerializeConvolution2dWithPerAxisParamsTestDeprecatedMethod") 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 weightsLayer = network->AddConstantLayer(weights, "weights"); + armnn::IConnectableLayer* const biasLayer = network->AddConstantLayer(weights, "bias"); + 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)); + biasLayer->GetOutputSlot(0).Connect(convLayer->GetInputSlot(2)); convLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); + weightsLayer->GetOutputSlot(0).SetTensorInfo(kernelInfo); + biasLayer->GetOutputSlot(0).SetTensorInfo(biasInfo); convLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index f4afbd9a84..753fe06edb 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -1596,54 +1596,6 @@ void Pooling3dQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output"); } - -void ResizeBilinearQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const -{ - const std::string descriptorName{"ResizeBilinearQueueDescriptor"}; - - ValidateNumInputs(workloadInfo, descriptorName, 1); - ValidateNumOutputs(workloadInfo, descriptorName, 1); - - const TensorInfo& inputTensorInfo = workloadInfo.m_InputTensorInfos[0]; - const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0]; - - ValidateTensorNumDimensions(inputTensorInfo, descriptorName, 4, "input"); - ValidateTensorNumDimensions(outputTensorInfo, descriptorName, 4, "output"); - - std::vector<DataType> supportedTypes = - { - DataType::BFloat16, - DataType::Float16, - DataType::Float32, - DataType::QAsymmS8, - DataType::QAsymmU8, - DataType::QSymmS16 - }; - - ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName); - ValidateTensorDataTypesMatch(inputTensorInfo, outputTensorInfo, descriptorName, "input", "output"); - - // ResizeBilinear only changes width and height: batch and channel count must match. - const unsigned int inputBatchSize = inputTensorInfo.GetShape()[0]; - const unsigned int outputBatchSize = outputTensorInfo.GetShape()[0]; - if (inputBatchSize != outputBatchSize) - { - throw InvalidArgumentException( - fmt::format("{}: Input batch size ({}) does not match output batch size ({})", - descriptorName, inputBatchSize, outputBatchSize)); - } - - DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout); - const unsigned int inputChannelCount = inputTensorInfo.GetShape()[dimensionIndices.GetChannelsIndex()]; - const unsigned int outputChannelCount = outputTensorInfo.GetShape()[dimensionIndices.GetChannelsIndex()]; - if (inputChannelCount != outputChannelCount) - { - throw InvalidArgumentException( - fmt::format("{}: Input channel count ({}) does not match output channel count ({})", - descriptorName, inputChannelCount, outputChannelCount)); - } -} - void ResizeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const { const std::string descriptorName{"ResizeQueueDescriptor"}; |