diff options
author | Keith Davis <keith.davis@arm.com> | 2021-05-21 16:33:48 +0100 |
---|---|---|
committer | Keith Davis <keith.davis@arm.com> | 2021-06-16 17:27:59 +0100 |
commit | 3ae3f978cf9ce3174609b7152af87acb410b0fe0 (patch) | |
tree | 9c71ea6aafbacfeba6938b5e0e29cdc97a784b70 /src | |
parent | 50de4fa4e7e0dd02a442ba350a1b40f293cb5a01 (diff) | |
download | armnn-3ae3f978cf9ce3174609b7152af87acb410b0fe0.tar.gz |
MLCE-510 Add CpuRef Shape Operator to ArmNN
* Add front end
* Add reference workload
* Serialization/Deserialization
* Add unit tests
* Update ArmNN Versioning
Signed-off-by: Keith Davis <keith.davis@arm.com>
Change-Id: I6fcb1fa341d6f08dea4003b13544e6e9f53fefd3
Diffstat (limited to 'src')
34 files changed, 970 insertions, 17 deletions
diff --git a/src/armnn/BackendHelper.cpp b/src/armnn/BackendHelper.cpp index be21412e97..a7bf419a7c 100644 --- a/src/armnn/BackendHelper.cpp +++ b/src/armnn/BackendHelper.cpp @@ -722,6 +722,13 @@ bool LayerSupportHandle::IsRsqrtSupported(const TensorInfo& input, return m_LayerSupport->IsRsqrtSupported(input, output, reasonIfUnsupported.value()); } +bool LayerSupportHandle::IsShapeSupported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) +{ + return m_LayerSupport->IsShapeSupported(input, output, reasonIfUnsupported.value()); +} + bool LayerSupportHandle::IsSliceSupported(const TensorInfo& input, const TensorInfo& output, const SliceDescriptor& descriptor, diff --git a/src/armnn/LayersFwd.hpp b/src/armnn/LayersFwd.hpp index 19cd9bdf6c..cdbcaa7e90 100644 --- a/src/armnn/LayersFwd.hpp +++ b/src/armnn/LayersFwd.hpp @@ -60,6 +60,7 @@ #include "layers/ReduceLayer.hpp" #include "layers/ReshapeLayer.hpp" #include "layers/ResizeLayer.hpp" +#include "layers/ShapeLayer.hpp" #include "layers/SliceLayer.hpp" #include "layers/SoftmaxLayer.hpp" #include "layers/SpaceToBatchNdLayer.hpp" @@ -154,6 +155,7 @@ DECLARE_LAYER(Rank) DECLARE_LAYER(Reduce) DECLARE_LAYER(Reshape) DECLARE_LAYER(Resize) +DECLARE_LAYER(Shape) DECLARE_LAYER(Slice) DECLARE_LAYER(Softmax) DECLARE_LAYER(SpaceToBatchNd) diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp index 5807d1705a..71f19313b8 100644 --- a/src/armnn/Network.cpp +++ b/src/armnn/Network.cpp @@ -482,6 +482,11 @@ IConnectableLayer* INetwork::AddTransposeLayer(const TransposeDescriptor& transp return pNetworkImpl->AddTransposeLayer(transposeDescriptor, name); } +IConnectableLayer* INetwork::AddShapeLayer(const char* name) +{ + return pNetworkImpl->AddShapeLayer(name); +} + IConnectableLayer* INetwork::AddStackLayer(const StackDescriptor& descriptor, const char* name) { @@ -2099,6 +2104,11 @@ IConnectableLayer* NetworkImpl::AddResizeLayer(const ResizeDescriptor& resizeDes return m_Graph->AddLayer<ResizeLayer>(resizeDescriptor, name); } +IConnectableLayer* NetworkImpl::AddShapeLayer(const char* name) +{ + return m_Graph->AddLayer<ShapeLayer>(name); +} + IConnectableLayer* NetworkImpl::AddInstanceNormalizationLayer(const InstanceNormalizationDescriptor& desc, const char* name) { diff --git a/src/armnn/Network.hpp b/src/armnn/Network.hpp index ad9b51cf35..e07075fbb5 100644 --- a/src/armnn/Network.hpp +++ b/src/armnn/Network.hpp @@ -250,6 +250,8 @@ public: IConnectableLayer* AddTransposeLayer(const TransposeDescriptor& transposeDescriptor, const char* name = nullptr); + IConnectableLayer* AddShapeLayer(const char* name = nullptr); + IConnectableLayer* AddStackLayer(const StackDescriptor& stackDescriptor, const char* name = nullptr); diff --git a/src/armnn/layers/ShapeLayer.cpp b/src/armnn/layers/ShapeLayer.cpp new file mode 100644 index 0000000000..4193fa9aab --- /dev/null +++ b/src/armnn/layers/ShapeLayer.cpp @@ -0,0 +1,73 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ShapeLayer.hpp" + +#include "LayerCloneBase.hpp" + +#include <armnn/TypesUtils.hpp> +#include <armnn/utility/NumericCast.hpp> + +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +namespace armnn +{ + +ShapeLayer::ShapeLayer(const char* name) + : Layer(1, 1, LayerType::Shape, name) +{ +} + +std::unique_ptr<IWorkload> ShapeLayer::CreateWorkload(const IWorkloadFactory& factory) const +{ + ShapeQueueDescriptor descriptor; + SetAdditionalInfo(descriptor); + + return factory.CreateShape(descriptor, PrepInfoAndDesc(descriptor)); +} + +ShapeLayer* ShapeLayer::Clone(Graph& graph) const +{ + return CloneBase<ShapeLayer>(graph, GetName()); +} + +void ShapeLayer::ValidateTensorShapesFromInputs() +{ + VerifyLayerConnections(1, CHECK_LOCATION()); + + const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape(); + + VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod); + + auto inferredShape = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() }); + + ARMNN_ASSERT(inferredShape.size() == 1); + + ValidateAndCopyShape(outputShape, inferredShape[0], m_ShapeInferenceMethod, "ShapeLayer"); +} + +std::vector<TensorShape> ShapeLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const +{ + IgnoreUnused(inputShapes); + ARMNN_ASSERT(inputShapes.size() == 1); + + TensorShape outputShape({ inputShapes[0].GetNumDimensions()} ); + + return std::vector<TensorShape>({ outputShape }); +} + +void ShapeLayer::Accept(ILayerVisitor& visitor) const +{ + IgnoreUnused(visitor); + throw armnn::Exception("ShapeLayer VisitShapeLayer is not implemented"); +} + +void ShapeLayer::ExecuteStrategy(IStrategy& strategy) const +{ + strategy.ExecuteStrategy(this, BaseDescriptor(), {}, GetName()); +} + +} // namespace armnn diff --git a/src/armnn/layers/ShapeLayer.hpp b/src/armnn/layers/ShapeLayer.hpp new file mode 100644 index 0000000000..fee285c2f0 --- /dev/null +++ b/src/armnn/layers/ShapeLayer.hpp @@ -0,0 +1,50 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerWithParameters.hpp" + +namespace armnn +{ + +class ShapeLayer : public Layer +{ +public: + /// Makes a workload for the Shape 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. + ShapeLayer* Clone(Graph& graph) const override; + + /// Check if the input tensor shape(s) + /// will lead to a valid configuration of @ref ShapeLayer. + /// @param [in] shapeInferenceMethod Indicates if output shape shall be overwritten or just validated. + void ValidateTensorShapesFromInputs() override; + + /// By default returns inputShapes if the number of inputs are equal to number of outputs, + /// otherwise 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; + + void Accept(ILayerVisitor& visitor) const override; + + void ExecuteStrategy(IStrategy& strategy) const override; + +protected: + /// Constructor to create a ShapeLayer. + /// @param [in] name Optional name for the layer. + ShapeLayer(const char* name); + + /// Default destructor. + ~ShapeLayer() = default; +}; + +} // namespace armnn diff --git a/src/armnnDeserializer/Deserializer.cpp b/src/armnnDeserializer/Deserializer.cpp index b5bf9daef0..af6ff842a7 100644 --- a/src/armnnDeserializer/Deserializer.cpp +++ b/src/armnnDeserializer/Deserializer.cpp @@ -257,6 +257,7 @@ m_ParserFunctions(Layer_MAX+1, &IDeserializer::DeserializerImpl::ParseUnsupporte m_ParserFunctions[Layer_ResizeBilinearLayer] = &DeserializerImpl::ParseResizeBilinear; m_ParserFunctions[Layer_ResizeLayer] = &DeserializerImpl::ParseResize; m_ParserFunctions[Layer_RsqrtLayer] = &DeserializerImpl::ParseRsqrt; + m_ParserFunctions[Layer_ShapeLayer] = &DeserializerImpl::ParseShape; m_ParserFunctions[Layer_SliceLayer] = &DeserializerImpl::ParseSlice; m_ParserFunctions[Layer_SoftmaxLayer] = &DeserializerImpl::ParseSoftmax; m_ParserFunctions[Layer_SpaceToBatchNdLayer] = &DeserializerImpl::ParseSpaceToBatchNd; @@ -377,6 +378,8 @@ LayerBaseRawPtr IDeserializer::DeserializerImpl::GetBaseLayer(const GraphPtr& gr return graphPtr->layers()->Get(layerIndex)->layer_as_ResizeLayer()->base(); case Layer::Layer_RsqrtLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_RsqrtLayer()->base(); + case Layer::Layer_ShapeLayer: + return graphPtr->layers()->Get(layerIndex)->layer_as_ShapeLayer()->base(); case Layer::Layer_SliceLayer: return graphPtr->layers()->Get(layerIndex)->layer_as_SliceLayer()->base(); case Layer::Layer_SoftmaxLayer: @@ -2338,6 +2341,26 @@ void IDeserializer::DeserializerImpl::ParseResizeBilinear(GraphPtr graph, unsign RegisterOutputSlots(graph, layerIndex, layer); } +void IDeserializer::DeserializerImpl::ParseShape(GraphPtr graph, unsigned int layerIndex) +{ + CHECK_LAYERS(graph, 0, layerIndex); + + TensorRawPtrVector inputs = GetInputs(graph, layerIndex); + CHECK_VALID_SIZE(inputs.size(), 1); + + TensorRawPtrVector outputs = GetOutputs(graph, layerIndex); + CHECK_VALID_SIZE(outputs.size(), 1); + + auto layerName = GetLayerName(graph, layerIndex); + IConnectableLayer* layer = m_Network->AddShapeLayer( layerName.c_str()); + + armnn::TensorInfo outputTensorInfo = ToTensorInfo(outputs[0]); + layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo); + + RegisterInputSlots(graph, layerIndex, layer); + RegisterOutputSlots(graph, layerIndex, layer); +} + void IDeserializer::DeserializerImpl::ParseSoftmax(GraphPtr graph, unsigned int layerIndex) { CHECK_LAYERS(graph, 0, layerIndex); diff --git a/src/armnnDeserializer/Deserializer.hpp b/src/armnnDeserializer/Deserializer.hpp index 8f38058ae5..0b05e16849 100644 --- a/src/armnnDeserializer/Deserializer.hpp +++ b/src/armnnDeserializer/Deserializer.hpp @@ -125,6 +125,7 @@ private: void ParseResize(GraphPtr graph, unsigned int layerIndex); void ParseResizeBilinear(GraphPtr graph, unsigned int layerIndex); void ParseRsqrt(GraphPtr graph, unsigned int layerIndex); + void ParseShape(GraphPtr graph, unsigned int layerIndex); void ParseSlice(GraphPtr graph, unsigned int layerIndex); void ParseSoftmax(GraphPtr graph, unsigned int layerIndex); void ParseSpaceToBatchNd(GraphPtr graph, unsigned int layerIndex); diff --git a/src/armnnDeserializer/test/DeserializeShape.cpp b/src/armnnDeserializer/test/DeserializeShape.cpp new file mode 100644 index 0000000000..a20fb59699 --- /dev/null +++ b/src/armnnDeserializer/test/DeserializeShape.cpp @@ -0,0 +1,131 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include <boost/test/unit_test.hpp> +#include "ParserFlatbuffersSerializeFixture.hpp" +#include <armnnDeserializer/IDeserializer.hpp> + +#include <string> + +BOOST_AUTO_TEST_SUITE(Deserializer) + +struct ShapeFixture : public ParserFlatbuffersSerializeFixture +{ + explicit ShapeFixture() + { + m_JsonString = R"( + { + layers: [ + { + layer_type: "InputLayer", + layer: { + base: { + base: { + layerName: "InputLayer", + layerType: "Input", + inputSlots: [ + + ], + outputSlots: [ + { + tensorInfo: { + dimensions: [ + 1, + 3, + 3, + 1 + ], + dataType: "Signed32", + quantizationScale: 0.0 + } + } + ] + } + } + } + }, + { + layer_type: "ShapeLayer", + layer: { + base: { + index: 1, + layerName: "shape", + layerType: "Shape", + inputSlots: [ + { + connection: { + sourceLayerIndex: 0, + outputSlotIndex: 0 + } + } + ], + outputSlots: [ + { + tensorInfo: { + dimensions: [ + 4 + ], + dataType: "Signed32", + quantizationScale: 0.0 + } + } + ] + } + } + }, + { + layer_type: "OutputLayer", + layer: { + base: { + base: { + index: 2, + layerName: "OutputLayer", + layerType: "Output", + inputSlots: [ + { + connection: { + sourceLayerIndex: 1, + outputSlotIndex: 0 + } + } + ], + outputSlots: [ + + ] + } + } + } + } + ], + inputIds: [ + 0 + ], + outputIds: [ + 0 + ], + featureVersions: { + bindingIdsScheme: 1 + } + } + )"; + Setup(); + } +}; + + +struct SimpleShapeFixture : ShapeFixture +{ + SimpleShapeFixture() : ShapeFixture() {} +}; + +BOOST_FIXTURE_TEST_CASE(DeserializeShape, SimpleShapeFixture) +{ + RunTest<1, armnn::DataType::Signed32>( + 0, + {{"InputLayer", { 1, 1, 1, 1, 1, 1, 1, 1, 1 }}}, + {{"OutputLayer",{ 1, 3, 3, 1 }}}); +} + +BOOST_AUTO_TEST_SUITE_END() diff --git a/src/armnnSerializer/ArmnnSchema.fbs b/src/armnnSerializer/ArmnnSchema.fbs index 753c2443a4..32a9bba5ab 100644 --- a/src/armnnSerializer/ArmnnSchema.fbs +++ b/src/armnnSerializer/ArmnnSchema.fbs @@ -171,7 +171,8 @@ enum LayerType : uint { Rank = 58, LogicalBinary = 59, Reduce = 60, - Cast = 61 + Cast = 61, + Shape = 62 } // Base layer table to be used as part of other layers @@ -487,7 +488,7 @@ table ReshapeLayer { } table ReshapeDescriptor { - targetShape:[uint]; + targetShape:[uint]; } table PermuteLayer { @@ -499,6 +500,10 @@ table PermuteDescriptor { dimMappings:[uint]; } +table ShapeLayer { + base:LayerBase; +} + table SpaceToBatchNdLayer { base:LayerBase; descriptor:SpaceToBatchNdDescriptor; @@ -972,7 +977,8 @@ union Layer { RankLayer, LogicalBinaryLayer, ReduceLayer, - CastLayer + CastLayer, + ShapeLayer } table AnyLayer { diff --git a/src/armnnSerializer/ArmnnSchema_generated.h b/src/armnnSerializer/ArmnnSchema_generated.h index 675fcc6490..4a352ddb6c 100644 --- a/src/armnnSerializer/ArmnnSchema_generated.h +++ b/src/armnnSerializer/ArmnnSchema_generated.h @@ -4,6 +4,7 @@ // // automatically generated by the FlatBuffers compiler, do not modify + #ifndef FLATBUFFERS_GENERATED_ARMNNSCHEMA_ARMNNSERIALIZER_H_ #define FLATBUFFERS_GENERATED_ARMNNSCHEMA_ARMNNSERIALIZER_H_ @@ -193,6 +194,9 @@ struct PermuteLayerBuilder; struct PermuteDescriptor; struct PermuteDescriptorBuilder; +struct ShapeLayer; +struct ShapeLayerBuilder; + struct SpaceToBatchNdLayer; struct SpaceToBatchNdLayerBuilder; @@ -735,11 +739,12 @@ enum LayerType { LayerType_LogicalBinary = 59, LayerType_Reduce = 60, LayerType_Cast = 61, + LayerType_Shape = 62, LayerType_MIN = LayerType_Addition, - LayerType_MAX = LayerType_Cast + LayerType_MAX = LayerType_Shape }; -inline const LayerType (&EnumValuesLayerType())[62] { +inline const LayerType (&EnumValuesLayerType())[63] { static const LayerType values[] = { LayerType_Addition, LayerType_Input, @@ -802,13 +807,14 @@ inline const LayerType (&EnumValuesLayerType())[62] { LayerType_Rank, LayerType_LogicalBinary, LayerType_Reduce, - LayerType_Cast + LayerType_Cast, + LayerType_Shape }; return values; } inline const char * const *EnumNamesLayerType() { - static const char * const names[63] = { + static const char * const names[64] = { "Addition", "Input", "Multiplication", @@ -871,13 +877,14 @@ inline const char * const *EnumNamesLayerType() { "LogicalBinary", "Reduce", "Cast", + "Shape", nullptr }; return names; } inline const char *EnumNameLayerType(LayerType e) { - if (flatbuffers::IsOutRange(e, LayerType_Addition, LayerType_Cast)) return ""; + if (flatbuffers::IsOutRange(e, LayerType_Addition, LayerType_Shape)) return ""; const size_t index = static_cast<size_t>(e); return EnumNamesLayerType()[index]; } @@ -1219,11 +1226,12 @@ enum Layer { Layer_LogicalBinaryLayer = 60, Layer_ReduceLayer = 61, Layer_CastLayer = 62, + Layer_ShapeLayer = 63, Layer_MIN = Layer_NONE, - Layer_MAX = Layer_CastLayer + Layer_MAX = Layer_ShapeLayer }; -inline const Layer (&EnumValuesLayer())[63] { +inline const Layer (&EnumValuesLayer())[64] { static const Layer values[] = { Layer_NONE, Layer_ActivationLayer, @@ -1287,13 +1295,14 @@ inline const Layer (&EnumValuesLayer())[63] { Layer_RankLayer, Layer_LogicalBinaryLayer, Layer_ReduceLayer, - Layer_CastLayer + Layer_CastLayer, + Layer_ShapeLayer }; return values; } inline const char * const *EnumNamesLayer() { - static const char * const names[64] = { + static const char * const names[65] = { "NONE", "ActivationLayer", "AdditionLayer", @@ -1357,13 +1366,14 @@ inline const char * const *EnumNamesLayer() { "LogicalBinaryLayer", "ReduceLayer", "CastLayer", + "ShapeLayer", nullptr }; return names; } inline const char *EnumNameLayer(Layer e) { - if (flatbuffers::IsOutRange(e, Layer_NONE, Layer_CastLayer)) return ""; + if (flatbuffers::IsOutRange(e, Layer_NONE, Layer_ShapeLayer)) return ""; const size_t index = static_cast<size_t>(e); return EnumNamesLayer()[index]; } @@ -1620,6 +1630,10 @@ template<> struct LayerTraits<armnnSerializer::CastLayer> { static const Layer enum_value = Layer_CastLayer; }; +template<> struct LayerTraits<armnnSerializer::ShapeLayer> { + static const Layer enum_value = Layer_ShapeLayer; +}; + bool VerifyLayer(flatbuffers::Verifier &verifier, const void *obj, Layer type); bool VerifyLayerVector(flatbuffers::Verifier &verifier, const flatbuffers::Vector<flatbuffers::Offset<void>> *values, const flatbuffers::Vector<uint8_t> *types); @@ -5180,6 +5194,49 @@ inline flatbuffers::Offset<PermuteDescriptor> CreatePermuteDescriptorDirect( dimMappings__); } +struct ShapeLayer FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { + typedef ShapeLayerBuilder Builder; + enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE { + VT_BASE = 4 + }; + const armnnSerializer::LayerBase *base() const { + return GetPointer<const armnnSerializer::LayerBase *>(VT_BASE); + } + bool Verify(flatbuffers::Verifier &verifier) const { + return VerifyTableStart(verifier) && + VerifyOffset(verifier, VT_BASE) && + verifier.VerifyTable(base()) && + verifier.EndTable(); + } +}; + +struct ShapeLayerBuilder { + typedef ShapeLayer Table; + flatbuffers::FlatBufferBuilder &fbb_; + flatbuffers::uoffset_t start_; + void add_base(flatbuffers::Offset<armnnSerializer::LayerBase> base) { + fbb_.AddOffset(ShapeLayer::VT_BASE, base); + } + explicit ShapeLayerBuilder(flatbuffers::FlatBufferBuilder &_fbb) + : fbb_(_fbb) { + start_ = fbb_.StartTable(); + } + ShapeLayerBuilder &operator=(const ShapeLayerBuilder &); + flatbuffers::Offset<ShapeLayer> Finish() { + const auto end = fbb_.EndTable(start_); + auto o = flatbuffers::Offset<ShapeLayer>(end); + return o; + } +}; + +inline flatbuffers::Offset<ShapeLayer> CreateShapeLayer( + flatbuffers::FlatBufferBuilder &_fbb, + flatbuffers::Offset<armnnSerializer::LayerBase> base = 0) { + ShapeLayerBuilder builder_(_fbb); + builder_.add_base(base); + return builder_.Finish(); +} + struct SpaceToBatchNdLayer FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { typedef SpaceToBatchNdLayerBuilder Builder; enum FlatBuffersVTableOffset FLATBUFFERS_VTABLE_UNDERLYING_TYPE { @@ -9567,6 +9624,9 @@ struct AnyLayer FLATBUFFERS_FINAL_CLASS : private flatbuffers::Table { const armnnSerializer::CastLayer *layer_as_CastLayer() const { return layer_type() == armnnSerializer::Layer_CastLayer ? static_cast<const armnnSerializer::CastLayer *>(layer()) : nullptr; } + const armnnSerializer::ShapeLayer *layer_as_ShapeLayer() const { + return layer_type() == armnnSerializer::Layer_ShapeLayer ? static_cast<const armnnSerializer::ShapeLayer *>(layer()) : nullptr; + } bool Verify(flatbuffers::Verifier &verifier) const { return VerifyTableStart(verifier) && VerifyField<uint8_t>(verifier, VT_LAYER_TYPE) && @@ -9824,6 +9884,10 @@ template<> inline const armnnSerializer::CastLayer *AnyLayer::layer_as<armnnSeri return layer_as_CastLayer(); } +template<> inline const armnnSerializer::ShapeLayer *AnyLayer::layer_as<armnnSerializer::ShapeLayer>() const { + return layer_as_ShapeLayer(); +} + struct AnyLayerBuilder { typedef AnyLayer Table; flatbuffers::FlatBufferBuilder &fbb_; @@ -10292,6 +10356,10 @@ inline bool VerifyLayer(flatbuffers::Verifier &verifier, const void *obj, Layer auto ptr = reinterpret_cast<const armnnSerializer::CastLayer *>(obj); return verifier.VerifyTable(ptr); } + case Layer_ShapeLayer: { + auto ptr = reinterpret_cast<const armnnSerializer::ShapeLayer *>(obj); + return verifier.VerifyTable(ptr); + } default: return true; } } diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp index 30a7e74a58..fd7f8dc7dc 100644 --- a/src/armnnSerializer/Serializer.cpp +++ b/src/armnnSerializer/Serializer.cpp @@ -1309,6 +1309,17 @@ void SerializerStrategy::SerializeNormalizationLayer(const armnn::IConnectableLa CreateAnyLayer(flatBufferLayer.o, serializer::Layer::Layer_NormalizationLayer); } +void SerializerStrategy::SerializeShapeLayer(const armnn::IConnectableLayer* layer, + const char* name) +{ + IgnoreUnused(name); + + auto shapeBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_Shape); + auto shapeLayer = serializer::CreateShapeLayer(m_flatBufferBuilder, shapeBaseLayer); + + CreateAnyLayer(shapeLayer.o, serializer::Layer::Layer_ShapeLayer); +} + void SerializerStrategy::SerializeStackLayer(const armnn::IConnectableLayer* layer, const armnn::StackDescriptor& stackDescriptor, const char* name) @@ -2138,6 +2149,11 @@ void SerializerStrategy::ExecuteStrategy(const armnn::IConnectableLayer* layer, SerializeResizeLayer(layer, layerDescriptor, name); break; } + case armnn::LayerType::Shape: + { + SerializeShapeLayer(layer, name); + break; + } case armnn::LayerType::Slice: { const armnn::SliceDescriptor& layerDescriptor = diff --git a/src/armnnSerializer/Serializer.hpp b/src/armnnSerializer/Serializer.hpp index 7bbcc2464e..c99e87d3e9 100644 --- a/src/armnnSerializer/Serializer.hpp +++ b/src/armnnSerializer/Serializer.hpp @@ -315,6 +315,9 @@ private: const armnn::NormalizationDescriptor& normalizationDescriptor, const char* name = nullptr); + void SerializeShapeLayer(const armnn::IConnectableLayer* layer, + const char* name = nullptr); + void SerializeSplitterLayer(const armnn::IConnectableLayer* layer, const armnn::ViewsDescriptor& viewsDescriptor, const char* name = nullptr); diff --git a/src/armnnSerializer/test/SerializerTests.cpp b/src/armnnSerializer/test/SerializerTests.cpp index 8e7ca37cfa..98532d0cec 100644 --- a/src/armnnSerializer/test/SerializerTests.cpp +++ b/src/armnnSerializer/test/SerializerTests.cpp @@ -1951,6 +1951,31 @@ TEST_CASE("EnsureResizeBilinearBackwardCompatibility") deserializedNetwork->ExecuteStrategy(verifier); } +TEST_CASE("SerializeShape") +{ + const std::string layerName("shape"); + const armnn::TensorInfo inputInfo({1, 3, 3, 1}, armnn::DataType::Signed32); + const armnn::TensorInfo outputInfo({ 4 }, armnn::DataType::Signed32); + + armnn::INetworkPtr network = armnn::INetwork::Create(); + armnn::IConnectableLayer* const inputLayer = network->AddInputLayer(0); + armnn::IConnectableLayer* const shapeLayer = network->AddShapeLayer(layerName.c_str()); + armnn::IConnectableLayer* const outputLayer = network->AddOutputLayer(0); + + inputLayer->GetOutputSlot(0).Connect(shapeLayer->GetInputSlot(0)); + shapeLayer->GetOutputSlot(0).Connect(outputLayer->GetInputSlot(0)); + + inputLayer->GetOutputSlot(0).SetTensorInfo(inputInfo); + shapeLayer->GetOutputSlot(0).SetTensorInfo(outputInfo); + + armnn::INetworkPtr deserializedNetwork = DeserializeNetwork(SerializeNetwork(*network)); + CHECK(deserializedNetwork); + + LayerVerifierBase verifier(layerName, {inputInfo}, {outputInfo}); + + deserializedNetwork->ExecuteStrategy(verifier); +} + TEST_CASE("SerializeSlice") { const std::string layerName{"slice"}; diff --git a/src/backends/backendsCommon/LayerSupportBase.cpp b/src/backends/backendsCommon/LayerSupportBase.cpp index 2e171f98ae..8a24e1161b 100644 --- a/src/backends/backendsCommon/LayerSupportBase.cpp +++ b/src/backends/backendsCommon/LayerSupportBase.cpp @@ -557,6 +557,13 @@ bool LayerSupportBase::IsRsqrtSupported(const TensorInfo&, // input return DefaultLayerSupport(__func__, __FILE__, __LINE__, reasonIfUnsupported); } +bool LayerSupportBase::IsShapeSupported(const TensorInfo&, // input + const TensorInfo&, // output + Optional<std::string&> reasonIfUnsupported) const +{ + return DefaultLayerSupport(__func__, __FILE__, __LINE__, reasonIfUnsupported); +} + bool LayerSupportBase::IsSliceSupported(const TensorInfo&, // input const TensorInfo&, // output const SliceDescriptor&, // descriptor diff --git a/src/backends/backendsCommon/LayerSupportBase.hpp b/src/backends/backendsCommon/LayerSupportBase.hpp index a4f972f961..0277a782a1 100644 --- a/src/backends/backendsCommon/LayerSupportBase.hpp +++ b/src/backends/backendsCommon/LayerSupportBase.hpp @@ -344,6 +344,10 @@ public: const TensorInfo& output, Optional<std::string&> reasonIfUnsupported = EmptyOptional()) const override; + bool IsShapeSupported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported = EmptyOptional()) const override; + bool IsSliceSupported(const TensorInfo& input, const TensorInfo& output, const SliceDescriptor& descriptor, diff --git a/src/backends/backendsCommon/WorkloadData.cpp b/src/backends/backendsCommon/WorkloadData.cpp index 44a6a17b37..8c78136185 100644 --- a/src/backends/backendsCommon/WorkloadData.cpp +++ b/src/backends/backendsCommon/WorkloadData.cpp @@ -2805,6 +2805,33 @@ void MergeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const ValidateTensorDataTypesMatch(inputTensorInfo0, outputTensorInfo, descriptorName, "input_0", "output"); } +void ShapeQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const +{ + const std::string& descriptorName{"ShapeQueueDescriptor"}; + + ValidateNumInputs(workloadInfo, descriptorName, 1); + ValidateNumOutputs(workloadInfo, descriptorName, 1); + + const TensorInfo& inputTensorInfo = workloadInfo.m_InputTensorInfos[0]; + const TensorInfo& outputTensorInfo = workloadInfo.m_OutputTensorInfos[0]; + + std::vector<DataType> supportedTypes = + { + DataType::BFloat16, + DataType::Float16, + DataType::Float32, + DataType::QAsymmS8, + DataType::QAsymmU8, + DataType::QAsymmS8, + DataType::QSymmS8, + DataType::QSymmS16, + DataType::Signed32 + }; + + ValidateDataTypes(inputTensorInfo, supportedTypes, descriptorName); + ValidateDataTypes(outputTensorInfo, {DataType::Signed32}, descriptorName); +} + void SwitchQueueDescriptor::Validate(const WorkloadInfo& workloadInfo) const { const std::string& descriptorName{"SwitchQueueDescriptor"}; diff --git a/src/backends/backendsCommon/WorkloadData.hpp b/src/backends/backendsCommon/WorkloadData.hpp index 11ce2cb44f..36653bdc0d 100644 --- a/src/backends/backendsCommon/WorkloadData.hpp +++ b/src/backends/backendsCommon/WorkloadData.hpp @@ -690,4 +690,9 @@ struct ReduceQueueDescriptor : QueueDescriptorWithParameters<ReduceDescriptor> void Validate(const WorkloadInfo& workloadInfo) const; }; +struct ShapeQueueDescriptor : QueueDescriptor +{ + void Validate(const WorkloadInfo& workloadInfo) const; +}; + } // namespace armnn diff --git a/src/backends/backendsCommon/WorkloadFactory.cpp b/src/backends/backendsCommon/WorkloadFactory.cpp index c5fc9d0fe2..61ad20995b 100644 --- a/src/backends/backendsCommon/WorkloadFactory.cpp +++ b/src/backends/backendsCommon/WorkloadFactory.cpp @@ -1003,6 +1003,16 @@ bool IWorkloadFactory::IsLayerConfigurationSupported(const BackendId& backendId, reason); break; } + case LayerType::Shape: + { + const TensorInfo& input = layer.GetInputSlot(0).GetConnection()->GetTensorInfo(); + const TensorInfo& output = layer.GetOutputSlot(0).GetTensorInfo(); + + result = layerSupportObject.IsShapeSupported(OverrideDataType(input, dataType), + OverrideDataType(output, dataType), + reason); + break; + } case LayerType::Slice: { auto cLayer = PolymorphicDowncast<const SliceLayer*>(&layer); @@ -1673,6 +1683,12 @@ std::unique_ptr<IWorkload> IWorkloadFactory::CreateRsqrt(const RsqrtQueueDescrip return std::unique_ptr<IWorkload>(); } +std::unique_ptr<IWorkload> IWorkloadFactory::CreateShape(const ShapeQueueDescriptor& /*descriptor*/, + const WorkloadInfo& /*info*/) const +{ + return std::unique_ptr<IWorkload>(); +} + std::unique_ptr<IWorkload> IWorkloadFactory::CreateSlice(const SliceQueueDescriptor& /*descriptor*/, const WorkloadInfo& /*info*/) const { diff --git a/src/backends/backendsCommon/WorkloadFactory.hpp b/src/backends/backendsCommon/WorkloadFactory.hpp index 42360d37ff..1987b9b664 100644 --- a/src/backends/backendsCommon/WorkloadFactory.hpp +++ b/src/backends/backendsCommon/WorkloadFactory.hpp @@ -252,6 +252,9 @@ public: virtual std::unique_ptr<IWorkload> CreateRsqrt(const RsqrtQueueDescriptor& descriptor, const WorkloadInfo& info) const; + virtual std::unique_ptr<IWorkload> CreateShape(const ShapeQueueDescriptor& descriptor, + const WorkloadInfo& info) const; + virtual std::unique_ptr<IWorkload> CreateSlice(const SliceQueueDescriptor& descriptor, const WorkloadInfo& info) const; diff --git a/src/backends/backendsCommon/common.mk b/src/backends/backendsCommon/common.mk index 73a16d00e1..ff9375dec1 100644 --- a/src/backends/backendsCommon/common.mk +++ b/src/backends/backendsCommon/common.mk @@ -85,6 +85,7 @@ COMMON_TEST_SOURCES := \ test/layerTests/SliceTestImpl.cpp \ test/layerTests/QuantizeTestImpl.cpp \ test/layerTests/SinTestImpl.cpp \ + test/layerTests/ShapeTestImpl.cpp \ test/layerTests/SoftmaxTestImpl.cpp \ test/layerTests/SpaceToBatchNdTestImpl.cpp \ test/layerTests/SpaceToDepthTestImpl.cpp \ diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt index 82381a8b84..162368fd43 100644 --- a/src/backends/backendsCommon/test/CMakeLists.txt +++ b/src/backends/backendsCommon/test/CMakeLists.txt @@ -157,6 +157,8 @@ list(APPEND armnnBackendsCommonUnitTests_sources layerTests/RsqrtTestImpl.hpp layerTests/SinTestImpl.cpp layerTests/SinTestImpl.hpp + layerTests/ShapeTestImpl.cpp + layerTests/ShapeTestImpl.cpp layerTests/SliceTestImpl.cpp layerTests/SliceTestImpl.hpp layerTests/SoftmaxTestImpl.cpp diff --git a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp index 5a05ee1d85..adc7bc4c3c 100644 --- a/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp +++ b/src/backends/backendsCommon/test/IsLayerSupportedTestImpl.hpp @@ -663,6 +663,8 @@ DECLARE_LAYER_POLICY_2_PARAM(Resize) DECLARE_LAYER_POLICY_2_PARAM(Reshape) +DECLARE_LAYER_POLICY_1_PARAM(Shape) + DECLARE_LAYER_POLICY_2_PARAM(Slice) DECLARE_LAYER_POLICY_2_PARAM(Softmax) diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp index 4ae6553362..46eb6ee2a5 100644 --- a/src/backends/backendsCommon/test/LayerTests.hpp +++ b/src/backends/backendsCommon/test/LayerTests.hpp @@ -55,6 +55,7 @@ #include <backendsCommon/test/layerTests/ReshapeTestImpl.hpp> #include <backendsCommon/test/layerTests/ResizeTestImpl.hpp> #include <backendsCommon/test/layerTests/RsqrtTestImpl.hpp> +#include <backendsCommon/test/layerTests/ShapeTestImpl.hpp> #include <backendsCommon/test/layerTests/SinTestImpl.hpp> #include <backendsCommon/test/layerTests/SliceTestImpl.hpp> #include <backendsCommon/test/layerTests/SoftmaxTestImpl.hpp> diff --git a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp new file mode 100644 index 0000000000..d6c03141ab --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.cpp @@ -0,0 +1,306 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ShapeTestImpl.hpp" + +#include <backendsCommon/test/DataTypeUtils.hpp> +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +template<typename T, std::size_t n> +LayerTestResult<int32_t, 1> ShapeTest( + armnn::TensorInfo inputTensorInfo, + std::vector<T> input, + armnn::TensorInfo outputTensorInfo, + std::vector<int32_t> expectedOutputData, + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + IgnoreUnused(memoryManager); + + std::vector<int32_t> actualOutput(outputTensorInfo.GetNumElements()); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); + + armnn::ShapeQueueDescriptor data; + armnn::WorkloadInfo info; + AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateShape(data, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), input.data()); + + workload->Execute(); + + CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); + + return LayerTestResult<int32_t, 1>(actualOutput, + expectedOutputData, + outputHandle->GetShape(), + outputTensorInfo.GetShape()); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<int32_t, 1> ShapeDimSize1Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + armnn::TensorInfo inputTensorInfo({ 1 }, ArmnnType, 1.0f, 0); + armnn::TensorInfo outputTensorInfo({ 1 }, armnn::DataType::Signed32); + + auto input = ConvertToDataType<ArmnnType>({ 1.0f }, inputTensorInfo); + + return ShapeTest<T, 1>(inputTensorInfo, input, outputTensorInfo, { 1 }, workloadFactory, memoryManager, + tensorHandleFactory); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<int32_t, 1> ShapeDimSize2Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + armnn::TensorInfo inputTensorInfo({ 1, 2 }, ArmnnType, 1.0f, 0); + armnn::TensorInfo outputTensorInfo({ 2 }, armnn::DataType::Signed32); + + auto input = ConvertToDataType<ArmnnType>({ 1.0f, 1.0f }, inputTensorInfo); + + return ShapeTest<T, 2>(inputTensorInfo, input, outputTensorInfo, { 1, 2 }, workloadFactory, memoryManager, + tensorHandleFactory); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<int32_t, 1> ShapeDimSize3Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + armnn::TensorInfo inputTensorInfo({ 1, 2, 3 }, ArmnnType, 1.0f, 0); + armnn::TensorInfo outputTensorInfo({ 3 }, armnn::DataType::Signed32); + + auto input = ConvertToDataType<ArmnnType>({ 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f }, inputTensorInfo); + + return ShapeTest<T, 3>(inputTensorInfo, input, outputTensorInfo, { 1, 2, 3 }, workloadFactory, memoryManager, + tensorHandleFactory); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<int32_t, 1> ShapeDimSize4Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + armnn::TensorInfo inputTensorInfo({ 2, 2, 3, 2 }, ArmnnType, 1.0f, 0); + armnn::TensorInfo outputTensorInfo({ 4 }, armnn::DataType::Signed32); + + auto input = ConvertToDataType<ArmnnType>({ 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, + 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, + 1.0f }, + inputTensorInfo); + + return ShapeTest<T, 4>(inputTensorInfo, input, outputTensorInfo, { 2, 2, 3, 2 }, workloadFactory, memoryManager, + tensorHandleFactory); +} + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::Signed32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::QSymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize4Test<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::Signed32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::QSymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize3Test<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::Signed32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::QSymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize2Test<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::Float16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::QAsymmU8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::Signed32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::QSymmS16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::QSymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::QAsymmS8>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<int32_t, 1> +ShapeDimSize1Test<armnn::DataType::BFloat16>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory);
\ No newline at end of file diff --git a/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp new file mode 100644 index 0000000000..85f7c0a453 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ShapeTestImpl.hpp @@ -0,0 +1,45 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerTestResult.hpp" + +#include <ResolveType.hpp> + +#include <armnn/backends/IBackendInternal.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +template<typename T , std::size_t n> +LayerTestResult<int32_t, 1> ShapeTest( + armnn::TensorInfo inputTensorInfo, + std::vector<T> input, + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<int32_t, 1> ShapeDimSize1Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<int32_t, 1> ShapeDimSize2Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<int32_t, 1> ShapeDimSize3Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<int32_t, 1> ShapeDimSize4Test( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); diff --git a/src/backends/reference/RefLayerSupport.cpp b/src/backends/reference/RefLayerSupport.cpp index 14a40f9d5d..1b05c4e0f4 100644 --- a/src/backends/reference/RefLayerSupport.cpp +++ b/src/backends/reference/RefLayerSupport.cpp @@ -1859,6 +1859,24 @@ bool RefLayerSupport::IsRsqrtSupported(const TensorInfo& input, reasonIfUnsupported); } +bool RefLayerSupport::IsShapeSupported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported) const +{ + IgnoreUnused(input); + bool supported = true; + + std::array<DataType, 1> supportedTypes = + { + DataType::Signed32 + }; + + supported &= CheckSupportRule(TypeAnyOf(output, supportedTypes), reasonIfUnsupported, + "Reference Shape: output type not supported"); + + return supported; +} + bool RefLayerSupport::IsSliceSupported(const TensorInfo& input, const TensorInfo& output, const SliceDescriptor& descriptor, diff --git a/src/backends/reference/RefLayerSupport.hpp b/src/backends/reference/RefLayerSupport.hpp index 7a95bb06ac..c060f79b5a 100644 --- a/src/backends/reference/RefLayerSupport.hpp +++ b/src/backends/reference/RefLayerSupport.hpp @@ -297,12 +297,16 @@ public: const TensorInfo& output, const ResizeDescriptor& descriptor, Optional<std::string&> reasonIfUnsupported = EmptyOptional()) const override; - + ARMNN_DEPRECATED_MSG("Use IsElementwiseUnarySupported instead") bool IsRsqrtSupported(const TensorInfo& input, const TensorInfo& output, Optional<std::string&> reasonIfUnsupported = EmptyOptional()) const override; + bool IsShapeSupported(const TensorInfo& input, + const TensorInfo& output, + Optional<std::string&> reasonIfUnsupported = EmptyOptional()) const override; + bool IsSliceSupported(const TensorInfo& input, const TensorInfo& output, const SliceDescriptor& descriptor, diff --git a/src/backends/reference/RefWorkloadFactory.cpp b/src/backends/reference/RefWorkloadFactory.cpp index 8e3bbe468f..606f531630 100644 --- a/src/backends/reference/RefWorkloadFactory.cpp +++ b/src/backends/reference/RefWorkloadFactory.cpp @@ -7,7 +7,6 @@ #include <backendsCommon/MemImportWorkload.hpp> #include <backendsCommon/MakeWorkloadHelper.hpp> #include <backendsCommon/TensorHandle.hpp> -#include <reference/workloads/RefFillWorkload.hpp> #include "RefWorkloadFactory.hpp" #include "RefBackendId.hpp" #include "workloads/RefWorkloads.hpp" @@ -626,6 +625,12 @@ std::unique_ptr<IWorkload> RefWorkloadFactory::CreateRsqrt(const RsqrtQueueDescr return CreateElementwiseUnary(elementwiseUnaryDescriptor, info); } +std::unique_ptr<IWorkload> RefWorkloadFactory::CreateShape(const ShapeQueueDescriptor& descriptor, + const WorkloadInfo& info) const +{ + return std::make_unique<RefShapeWorkload>(descriptor, info); +} + std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSlice(const SliceQueueDescriptor& descriptor, const WorkloadInfo& info) const { diff --git a/src/backends/reference/RefWorkloadFactory.hpp b/src/backends/reference/RefWorkloadFactory.hpp index 734c5e49c3..2beffa77f3 100644 --- a/src/backends/reference/RefWorkloadFactory.hpp +++ b/src/backends/reference/RefWorkloadFactory.hpp @@ -243,6 +243,9 @@ public: std::unique_ptr<IWorkload> CreateRsqrt(const RsqrtQueueDescriptor& descriptor, const WorkloadInfo& info) const override; + std::unique_ptr<IWorkload> CreateShape(const ShapeQueueDescriptor& descriptor, + const WorkloadInfo& info) const override; + std::unique_ptr<IWorkload> CreateSlice(const SliceQueueDescriptor& descriptor, const WorkloadInfo& info) const override; diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp index 1cc6fa8d36..45e3717268 100644 --- a/src/backends/reference/test/RefLayerTests.cpp +++ b/src/backends/reference/test/RefLayerTests.cpp @@ -1733,6 +1733,43 @@ ARMNN_AUTO_TEST_CASE(DepthToSpaceNhwcInt16_2, DepthToSpaceTest2<DataType::QSymmS ARMNN_AUTO_TEST_CASE(DepthToSpaceNhwcInt16_3, DepthToSpaceTest3<DataType::QSymmS16>, DataLayout::NHWC); ARMNN_AUTO_TEST_CASE(DepthToSpaceNhwcInt16_4, DepthToSpaceTest4<DataType::QSymmS16>, DataLayout::NHWC); +// Shape +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1Float16, ShapeDimSize1Test<DataType::Float16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1Float32, ShapeDimSize1Test<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1QAsymmU8, ShapeDimSize1Test<DataType::QAsymmU8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1Signed32, ShapeDimSize1Test<DataType::Signed32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1QSymmS16, ShapeDimSize1Test<DataType::QSymmS16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1QSymmS8, ShapeDimSize1Test<DataType::QSymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1QAsymmS8, ShapeDimSize1Test<DataType::QAsymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize1BFloat16, ShapeDimSize1Test<DataType::BFloat16>) + +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2Float16, ShapeDimSize2Test<DataType::Float16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2Float32, ShapeDimSize2Test<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2QAsymmU8, ShapeDimSize2Test<DataType::QAsymmU8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2Signed32, ShapeDimSize2Test<DataType::Signed32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2QSymmS16, ShapeDimSize2Test<DataType::QSymmS16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2QSymmS8, ShapeDimSize2Test<DataType::QSymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2QAsymmS8, ShapeDimSize2Test<DataType::QAsymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize2BFloat16, ShapeDimSize2Test<DataType::BFloat16>) + +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3Float16, ShapeDimSize3Test<DataType::Float16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3Float32, ShapeDimSize3Test<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3QAsymmU8, ShapeDimSize3Test<DataType::QAsymmU8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3Signed32, ShapeDimSize3Test<DataType::Signed32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3QSymmS16, ShapeDimSize3Test<DataType::QSymmS16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3QSymmS8, ShapeDimSize3Test<DataType::QSymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3QAsymmS8, ShapeDimSize3Test<DataType::QAsymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize3BFloat16, ShapeDimSize3Test<DataType::BFloat16>) + +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4Float16, ShapeDimSize4Test<DataType::Float16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4Float32, ShapeDimSize4Test<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4QAsymmU8, ShapeDimSize4Test<DataType::QAsymmU8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4Signed32, ShapeDimSize4Test<DataType::Signed32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4QSymmS16, ShapeDimSize4Test<DataType::QSymmS16>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4QSymmS8, ShapeDimSize4Test<DataType::QSymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4QAsymmS8, ShapeDimSize4Test<DataType::QAsymmS8>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ShapeDimSize4BFloat16, ShapeDimSize4Test<DataType::BFloat16>) + // SpaceToDepth ARMNN_AUTO_TEST_CASE_WITH_THF(SpaceToDepthNchwAsymmQ8, SpaceToDepthNchwAsymmQ8Test) ARMNN_AUTO_TEST_CASE_WITH_THF(SpaceToDepthNhwcAsymmQ8, SpaceToDepthNhwcAsymmQ8Test) diff --git a/src/backends/reference/workloads/CMakeLists.txt b/src/backends/reference/workloads/CMakeLists.txt index 09e02e67bd..7a769e5246 100644 --- a/src/backends/reference/workloads/CMakeLists.txt +++ b/src/backends/reference/workloads/CMakeLists.txt @@ -143,6 +143,7 @@ list(APPEND armnnRefBackendWorkloads_sources RefResizeBilinearWorkload.hpp RefResizeWorkload.cpp RefResizeWorkload.hpp + RefShapeWorkload.hpp RefSliceWorkload.cpp RefSliceWorkload.hpp RefSoftmaxWorkload.cpp diff --git a/src/backends/reference/workloads/RefShapeWorkload.hpp b/src/backends/reference/workloads/RefShapeWorkload.hpp new file mode 100644 index 0000000000..8e2a410b0c --- /dev/null +++ b/src/backends/reference/workloads/RefShapeWorkload.hpp @@ -0,0 +1,48 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include <backendsCommon/Workload.hpp> +#include <backendsCommon/WorkloadData.hpp> + +#include "RefWorkloadUtils.hpp" + +namespace armnn +{ + +struct RefShapeWorkload : public BaseWorkload<ShapeQueueDescriptor> +{ +public: + using BaseWorkload<ShapeQueueDescriptor>::BaseWorkload; + virtual void Execute() const override + { + Execute(m_Data.m_Inputs, m_Data.m_Outputs); + } + void ExecuteAsync(WorkingMemDescriptor& workingMemDescriptor) override + { + Execute(workingMemDescriptor.m_Inputs, workingMemDescriptor.m_Outputs); + } + +private: + void Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const + { + const TensorShape Shape = GetTensorInfo(inputs[0]).GetShape(); + + const TensorInfo& outputInfo = GetTensorInfo(outputs[0]); + + unsigned int numBytes = + GetTensorInfo(inputs[0]).GetNumDimensions() * GetDataTypeSize(outputInfo.GetDataType()); + + std::memcpy(outputs[0]->Map(), &Shape, numBytes); + outputs[0]->Unmap(); + } +}; + +} //namespace armnn + + + + diff --git a/src/backends/reference/workloads/RefWorkloads.hpp b/src/backends/reference/workloads/RefWorkloads.hpp index d3995f2b82..afe63d13c0 100644 --- a/src/backends/reference/workloads/RefWorkloads.hpp +++ b/src/backends/reference/workloads/RefWorkloads.hpp @@ -35,10 +35,10 @@ #include "RefDequantizeWorkload.hpp" #include "RefElementwiseWorkload.hpp" #include "RefElementwiseUnaryWorkload.hpp" +#include "RefFakeQuantizationFloat32Workload.hpp" #include "RefFillWorkload.hpp" -#include "RefFullyConnectedWorkload.hpp" #include "RefFloorWorkload.hpp" -#include "RefFakeQuantizationFloat32Workload.hpp" +#include "RefFullyConnectedWorkload.hpp" #include "RefGatherWorkload.hpp" #include "RefInstanceNormalizationWorkload.hpp" #include "RefL2NormalizationWorkload.hpp" @@ -59,6 +59,7 @@ #include "RefReshapeWorkload.hpp" #include "RefResizeBilinearWorkload.hpp" #include "RefResizeWorkload.hpp" +#include "RefShapeWorkload.hpp" #include "RefSliceWorkload.hpp" #include "RefSplitterWorkload.hpp" #include "RefSoftmaxWorkload.hpp" |