diff options
Diffstat (limited to 'src/armnn')
-rw-r--r-- | src/armnn/BackendHelper.cpp | 15 | ||||
-rw-r--r-- | src/armnn/LayersFwd.hpp | 2 | ||||
-rw-r--r-- | src/armnn/Network.cpp | 11 | ||||
-rw-r--r-- | src/armnn/Network.hpp | 3 | ||||
-rw-r--r-- | src/armnn/layers/TileLayer.cpp | 71 | ||||
-rw-r--r-- | src/armnn/layers/TileLayer.hpp | 45 |
6 files changed, 147 insertions, 0 deletions
diff --git a/src/armnn/BackendHelper.cpp b/src/armnn/BackendHelper.cpp index 18184fbfb2..0a55a08087 100644 --- a/src/armnn/BackendHelper.cpp +++ b/src/armnn/BackendHelper.cpp @@ -1409,6 +1409,21 @@ bool LayerSupportHandle::IsSwitchSupported(const TensorInfo& input0, reasonIfUnsupported); } +bool LayerSupportHandle::IsTileSupported(const TensorInfo& input, + const TensorInfo& output, + const armnn::TileDescriptor &descriptor, + Optional<std::string&> reasonIfUnsupported) +{ + TensorInfos infos{input, output}; + + return m_LayerSupport->IsLayerSupported(LayerType::Tile, + infos, + descriptor, + EmptyOptional(), + EmptyOptional(), + reasonIfUnsupported); +} + bool LayerSupportHandle::IsTransposeConvolution2dSupported( const TensorInfo& input, const TensorInfo& output, diff --git a/src/armnn/LayersFwd.hpp b/src/armnn/LayersFwd.hpp index d3ce6f2a67..743b8d7205 100644 --- a/src/armnn/LayersFwd.hpp +++ b/src/armnn/LayersFwd.hpp @@ -76,6 +76,7 @@ #include "layers/StridedSliceLayer.hpp" #include "layers/SubtractionLayer.hpp" #include "layers/SwitchLayer.hpp" +#include "layers/TileLayer.hpp" #include "layers/TransposeConvolution2dLayer.hpp" #include "layers/TransposeLayer.hpp" #include "layers/UnidirectionalSequenceLstmLayer.hpp" @@ -178,6 +179,7 @@ DECLARE_LAYER(StandIn) DECLARE_LAYER(StridedSlice) DECLARE_LAYER(Subtraction) DECLARE_LAYER(Switch) +DECLARE_LAYER(Tile) DECLARE_LAYER(Transpose) DECLARE_LAYER(TransposeConvolution2d) DECLARE_LAYER(UnidirectionalSequenceLstm) diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp index 27e91ae39c..22d2c78c65 100644 --- a/src/armnn/Network.cpp +++ b/src/armnn/Network.cpp @@ -644,6 +644,12 @@ IConnectableLayer* INetwork::AddReverseV2Layer(const char *name) return pNetworkImpl->AddReverseV2Layer(name); } +IConnectableLayer* INetwork::AddTileLayer(const TileDescriptor &descriptor, + const char *name) +{ + return pNetworkImpl->AddTileLayer(descriptor, name); +} + void INetwork::ExecuteStrategy(IStrategy& strategy) const { return pNetworkImpl->ExecuteStrategy(strategy); @@ -2934,6 +2940,11 @@ IConnectableLayer* NetworkImpl::AddReverseV2Layer(const char *name) return m_Graph->AddLayer<ReverseV2Layer>(name); } +IConnectableLayer* NetworkImpl::AddTileLayer(const TileDescriptor &desc, const char *name) +{ + return m_Graph->AddLayer<TileLayer>(desc, name); +} + IConnectableLayer* NetworkImpl::AddPrecompiledLayer(const PreCompiledDescriptor& preCompiledDescriptor, CompiledBlobPtr compiledBlobPtr, const Optional<BackendId>& backend, diff --git a/src/armnn/Network.hpp b/src/armnn/Network.hpp index ae287f32d1..a84a0e9ba4 100644 --- a/src/armnn/Network.hpp +++ b/src/armnn/Network.hpp @@ -220,6 +220,9 @@ public: IConnectableLayer* AddSwitchLayer(const char* name = nullptr); + IConnectableLayer* AddTileLayer(const TileDescriptor& tileDescriptor, + const char* name = nullptr); + IConnectableLayer* AddTransposeConvolution2dLayer(const TransposeConvolution2dDescriptor& descriptor, const ConstTensor& weights, const Optional<ConstTensor>& biases, diff --git a/src/armnn/layers/TileLayer.cpp b/src/armnn/layers/TileLayer.cpp new file mode 100644 index 0000000000..3c313905fe --- /dev/null +++ b/src/armnn/layers/TileLayer.cpp @@ -0,0 +1,71 @@ +// +// Copyright © 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "TileLayer.hpp" + +#include <armnn/backends/WorkloadFactory.hpp> +#include "layers/LayerCloneBase.hpp" + +namespace armnn +{ +TileLayer::TileLayer(const TileDescriptor ¶m, const char *name) + : LayerWithParameters(1, 1, LayerType::Tile, param, name) +{} + +std::unique_ptr<IWorkload> TileLayer::CreateWorkload(const IWorkloadFactory &factory) const +{ + TileQueueDescriptor descriptor; + SetAdditionalInfo(descriptor); + + return factory.CreateWorkload(LayerType::Tile, descriptor, PrepInfoAndDesc(descriptor)); +} + +TileLayer* TileLayer::Clone(armnn::Graph &graph) const +{ + auto layer = CloneBase<TileLayer>(graph, m_Param, GetName()); + + return std::move(layer); +} + +std::vector<TensorShape> TileLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const +{ + ARMNN_ASSERT(inputShapes.size() == 1); + const TensorShape& inputShape = inputShapes[0]; + const std::vector<uint32_t> multipleShape = m_Param.m_Multiples; + + std::vector<unsigned int> dimSizes; + + // Check input shape and multiples have same length and multiply them together to get output shape + if(inputShape.GetNumDimensions() == multipleShape.size()) + { + for(uint32_t i = 0; i < inputShape.GetNumDimensions(); ++i) + { + dimSizes.insert(dimSizes.begin(), inputShape[i] * multipleShape[i]); + } + } + else + { + throw LayerValidationException("TileLayer: input rank and length of multiples are different."); + } + + return std::vector<TensorShape>({TensorShape({inputShape.GetNumElements(), dimSizes.data()})}); +} + +void TileLayer::ValidateTensorShapesFromInputs() +{ + VerifyLayerConnections(1, CHECK_LOCATION()); + + const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape(); + + VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); + + auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape() }); + + ARMNN_ASSERT(inferredShapes.size() == 1); + + ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "TileLayer"); +} + +}
\ No newline at end of file diff --git a/src/armnn/layers/TileLayer.hpp b/src/armnn/layers/TileLayer.hpp new file mode 100644 index 0000000000..632cdb426b --- /dev/null +++ b/src/armnn/layers/TileLayer.hpp @@ -0,0 +1,45 @@ +// +// Copyright © 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerWithParameters.hpp" + +namespace armnn +{ + +class TileLayer : public LayerWithParameters<TileDescriptor> +{ +public: + /// Makes a workload for the Tile type. + /// @param [in] graph The graph where this layer can be found. + /// @param [in] factory The workload factory which will create the workload. + /// @return A pointer to the created workload, or nullptr if not created. + virtual std::unique_ptr<IWorkload> CreateWorkload(const IWorkloadFactory& factory) const override; + + /// Creates a dynamically-allocated copy of this layer. + /// @param [in] graph The graph into which this layer is being cloned. + TileLayer* Clone(Graph& graph) const override; + + /// Infers the output shapes from given input shapes and layer properties. + /// @param [in] inputShapes The input shapes layer has. + /// @return A vector to the inferred output shape. + std::vector<TensorShape> InferOutputShapes(const std::vector<TensorShape>& inputShapes) const override; + + /// Check if the input tensor tile(s) + /// will lead to a valid configuration of @ref TileLayer. + /// @param [in] shapeInferenceMethod Indicates if output tile shall be overwritten or just validated. + void ValidateTensorShapesFromInputs() override; + +protected: + /// Constructor to create a TileLayer. + /// @param [in] name Optional name for the layer. + TileLayer(const TileDescriptor& param, const char* name); + + /// Default destructor. + ~TileLayer() = default; +}; + +} // namespace armnn |