ConcatLayer Class Reference

This layer represents a merge operation. More...

#include <ConcatLayer.hpp>

Inheritance diagram for ConcatLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the Concat type. More...
virtual void	CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true) override
	Set the outputs to be appropriate sub tensors of the input if sub tensors are supported otherwise creates tensor handlers. More...
ConcatLayer *	Clone (Graph &graph) const override
	Creates a dynamically-allocated copy of this layer. More...
void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of ConcatLayer. More...
std::vector< TensorShape >	InferOutputShapes (const std::vector< TensorShape > &inputShapes) const 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. More...
void	Accept (ILayerVisitor &visitor) const override
	Apply a visitor to this layer. More...
Public Member Functions inherited from LayerWithParameters< OriginsDescriptor >
const OriginsDescriptor &	GetParameters () const
void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override
	Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...
Public Member Functions inherited from Layer
	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
	Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)
const std::string &	GetNameStr () const
const OutputHandler &	GetOutputHandler (unsigned int i=0) const
OutputHandler &	GetOutputHandler (unsigned int i=0)
ShapeInferenceMethod	GetShapeInferenceMethod () const
const std::vector< InputSlot > &	GetInputSlots () const
const std::vector< OutputSlot > &	GetOutputSlots () const
std::vector< InputSlot >::iterator	BeginInputSlots ()
std::vector< InputSlot >::iterator	EndInputSlots ()
std::vector< OutputSlot >::iterator	BeginOutputSlots ()
std::vector< OutputSlot >::iterator	EndOutputSlots ()
bool	IsOutputUnconnected ()
void	ResetPriority () const
LayerPriority	GetPriority () const
LayerType	GetType () const
DataType	GetDataType () const
const BackendId &	GetBackendId () const
void	SetBackendId (const BackendId &id)
void	VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
virtual void	ReleaseConstantData ()
template<typename Op >
void	OperateOnConstantTensors (Op op)
const char *	GetName () const override
	Returns the name of the layer. More...
unsigned int	GetNumInputSlots () const override
	Returns the number of connectable input slots. More...
unsigned int	GetNumOutputSlots () const override
	Returns the number of connectable output slots. More...
const InputSlot &	GetInputSlot (unsigned int index) const override
	Get a const input slot handle by slot index. More...
InputSlot &	GetInputSlot (unsigned int index) override
	Get the input slot handle by slot index. More...
const OutputSlot &	GetOutputSlot (unsigned int index=0) const override
	Get the const output slot handle by slot index. More...
OutputSlot &	GetOutputSlot (unsigned int index=0) override
	Get the output slot handle by slot index. More...
void	SetGuid (LayerGuid guid)
LayerGuid	GetGuid () const final
	Returns the unique id of the layer. More...
void	AddRelatedLayerName (const std::string layerName)
const std::list< std::string > &	GetRelatedLayerNames ()
virtual void	Reparent (Graph &dest, std::list< Layer *>::const_iterator iterator)=0
void	BackendSelectionHint (Optional< BackendId > backend) final
	Provide a hint for the optimizer as to which backend to prefer for this layer. More...
Optional< BackendId >	GetBackendHint () const
void	SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)

Protected Member Functions
	ConcatLayer (const OriginsDescriptor &param, const char *name)
	Constructor to create a ConcatLayer. More...
	~ConcatLayer ()=default
	Default destructor. More...
Protected Member Functions inherited from LayerWithParameters< OriginsDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const OriginsDescriptor &param, const char *name)
	~LayerWithParameters ()=default
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload. More...
Protected Member Functions inherited from Layer
virtual	~Layer ()=default
template<typename QueueDescriptor >
void	CollectQueueDescriptorInputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
template<typename QueueDescriptor >
void	CollectQueueDescriptorOutputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
void	ValidateAndCopyShape (const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
void	VerifyShapeInferenceType (const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
template<typename QueueDescriptor >
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload. More...
template<typename LayerType , typename ... Params>
LayerType *	CloneBase (Graph &graph, Params &&... params) const
virtual ConstantTensors	GetConstantTensorsByRef ()
Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle. More...

Additional Inherited Members
Public Types inherited from LayerWithParameters< OriginsDescriptor >
using	DescriptorType = OriginsDescriptor
Protected Types inherited from Layer
using	ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>
Protected Attributes inherited from LayerWithParameters< OriginsDescriptor >
OriginsDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.). More...
Protected Attributes inherited from Layer
std::vector< OutputHandler >	m_OutputHandlers
ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

This layer represents a merge operation.

Definition at line 13 of file ConcatLayer.hpp.

Constructor & Destructor Documentation

ConcatLayer()

ConcatLayer ( const OriginsDescriptor &  param, const char *  name  )

protected

Constructor to create a ConcatLayer.

Parameters

[in]	param	OriginsDescriptor to configure the concat operation.
[in]	name	Optional name for the layer.

Definition at line 18 of file ConcatLayer.cpp.

References armnn::Concat.

    : LayerWithParameters(param.GetNumViews(), 1, LayerType::Concat, param, name)
{
}

~ConcatLayer()

~ConcatLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

Accept()

void Accept ( ILayerVisitor &  visitor ) const

overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 312 of file ConcatLayer.cpp.

References Layer::GetName(), LayerWithParameters< OriginsDescriptor >::GetParameters(), and ILayerVisitor::VisitConcatLayer().

{
    visitor.VisitConcatLayer(this, GetParameters(), GetName());
}

Clone()

ConcatLayer * Clone ( Graph &  graph ) const

overridevirtual

Creates a dynamically-allocated copy of this layer.

Parameters

[in]

graph

The graph into which this layer is being cloned.

Implements Layer.

Definition at line 190 of file ConcatLayer.cpp.

References Layer::GetName(), and LayerWithParameters< OriginsDescriptor >::m_Param.

{
    return CloneBase<ConcatLayer>(graph, m_Param, GetName());
}

CreateTensorHandles()

void CreateTensorHandles ( const TensorHandleFactoryRegistry &  registry, const IWorkloadFactory &  factory, const bool  IsMemoryManaged = true  )

overridevirtual

Set the outputs to be appropriate sub tensors of the input if sub tensors are supported otherwise creates tensor handlers.

Parameters

[in]	registry	Contains all the registered tensor handle factories available for use.
[in]	factory	The workload factory which will create the workload.
[in]	IsMemoryManaged	Determine whether or not to assign a memory manager during creation

Reimplemented from Layer.

Definition at line 171 of file ConcatLayer.cpp.

References ARMNN_ASSERT, TensorHandleFactoryRegistry::GetFactory(), Layer::GetOutputSlot(), OutputSlot::GetTensorHandleFactoryId(), and ITensorHandleFactory::LegacyFactoryId.

{
    OutputSlot& slot = GetOutputSlot(0);
    ITensorHandleFactory::FactoryId factoryId = slot.GetTensorHandleFactoryId();

    if (factoryId == ITensorHandleFactory::LegacyFactoryId)
    {
        CreateTensors(registry, workloadFactory, isMemoryManaged);
    }
    else
    {
        ITensorHandleFactory* handleFactory = registry.GetFactory(factoryId);
        ARMNN_ASSERT(handleFactory);
        CreateTensors(registry, *handleFactory, isMemoryManaged);
    }
}

CreateWorkload()

std::unique_ptr< IWorkload > CreateWorkload ( const IWorkloadFactory &  factory ) const

overridevirtual

Makes a workload for the Concat type.

Parameters

[in]	graph	The graph where this layer can be found.
[in]	factory	The workload factory which will create the workload.

Returns

A pointer to the created workload, or nullptr if not created.

Implements Layer.

Definition at line 23 of file ConcatLayer.cpp.

References ARMNN_ASSERT_MSG, ARMNN_NO_DEPRECATE_WARN_BEGIN, ARMNN_NO_DEPRECATE_WARN_END, armnn::Concat, armnn::Constant, IWorkloadFactory::CreateConcat(), ITensorHandleFactory::GetCapabilities(), OriginsDescriptor::GetConcatAxis(), InputSlot::GetConnectedOutputSlot(), OutputHandler::GetData(), TensorHandleFactoryRegistry::GetFactory(), Layer::GetInputSlot(), OutputSlot::GetNumConnections(), OriginsDescriptor::GetNumDimensions(), Layer::GetNumInputSlots(), OriginsDescriptor::GetNumViews(), OutputSlot::GetOutputHandler(), Layer::GetOutputHandler(), Layer::GetOutputSlot(), OutputSlot::GetOwningLayer(), TensorInfo::GetShape(), OutputSlot::GetTensorHandleFactoryId(), OutputHandler::GetTensorInfo(), OutputSlot::GetTensorInfo(), Layer::GetType(), OriginsDescriptor::GetViewOrigin(), armnn::info, armnn::Input, TensorInfo::IsTypeSpaceMatch(), Layer::m_OutputHandlers, LayerWithParameters< Parameters >::m_Param, LayerWithParameters< OriginsDescriptor >::m_Param, ConcatQueueDescriptor::m_ViewOrigins, armnn::PaddingRequired, LayerWithParameters< OriginsDescriptor >::PrepInfoAndDesc(), and OutputHandler::SetData().

{
    ConcatQueueDescriptor descriptor;

    // Copies the view origins to the descriptor.
    descriptor.m_ViewOrigins.reserve(m_Param.GetNumViews());
    for (unsigned int i = 0; i < m_Param.GetNumViews(); ++i)
    {
        descriptor.m_ViewOrigins.emplace_back(
            std::vector<unsigned int>(m_Param.GetViewOrigin(i), m_Param.GetViewOrigin(i) + m_Param.GetNumDimensions()));
    }

    return factory.CreateConcat(descriptor, PrepInfoAndDesc(descriptor));
}

InferOutputShapes()

std::vector< TensorShape > InferOutputShapes ( const std::vector< TensorShape > &  inputShapes ) const

overridevirtual

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.

Parameters

[in]

inputShapes

The input shapes layer has.

Returns

A vector to the inferred output shape.

Reimplemented from Layer.

Definition at line 195 of file ConcatLayer.cpp.

References ARMNN_ASSERT, OriginsDescriptor::GetNumDimensions(), OriginsDescriptor::GetNumViews(), OriginsDescriptor::GetViewOrigin(), and LayerWithParameters< OriginsDescriptor >::m_Param.

{
    ARMNN_ASSERT(inputShapes.size() == m_Param.GetNumViews());

    unsigned int numDims = m_Param.GetNumDimensions();
    for (unsigned int i=0; i< inputShapes.size(); i++)
    {
        auto& inputShape = inputShapes[i];

        ConditionalThrowIfNotEqual<LayerValidationException>(
            "ConcatLayer: Num Dimensions must match all inputs.",
            numDims,
            inputShape.GetNumDimensions());
    }

    // Finds the bounding box (extents) of all the views.
    std::vector<unsigned int> extentMin(numDims);
    std::vector<unsigned int> extentMax(numDims);
    for (unsigned int i = 0; i < inputShapes.size(); i++)
    {
        const uint32_t* origin = m_Param.GetViewOrigin(i);
        const armnn::TensorShape& shape = inputShapes[i];
        for (unsigned int d = 0; d < numDims; d++)
        {
            extentMin[d] = std::min(extentMin[d], origin[d]);
            extentMax[d] = std::max(extentMax[d], origin[d] + shape[d]);
        }
    }

    // Checks that the bounding box starts at the origin.
    if (!std::all_of(extentMin.begin(), extentMin.end(), [](unsigned int s) { return s == 0; }))
    {
        throw LayerValidationException("ConcatLayer: there is no view that starts at the origin");
    }

    // Checks that there are no overlaps of views (this would lead to undefined output at those locations).
    // Checks each pair of views against each other
    // (and doesn't bother to check against self, or check the same pair both ways round).
    for (unsigned int a = 0; a < inputShapes.size(); a++)
    {
        const uint32_t* aOrigin = m_Param.GetViewOrigin(a);
        const armnn::TensorShape& aShape = inputShapes[a];
        for (unsigned int b = 0; b < a; b++)
        {
            const uint32_t* bOrigin = m_Param.GetViewOrigin(b);
            const armnn::TensorShape& bShape = inputShapes[b];

            bool allAxesOverlap = true;
            for (unsigned int d = 0; d < numDims && allAxesOverlap; d++)
            {
                unsigned int a1 = aOrigin[d];
                unsigned int a2 = aOrigin[d] + aShape[d];

                unsigned int b1 = bOrigin[d];
                unsigned int b2 = bOrigin[d] + bShape[d];

                if (a2 <= b1 || b2 <= a1)
                {
                    allAxesOverlap = false;
                }
            }
            if (allAxesOverlap)
            {
                throw LayerValidationException("ConcatLayer: Some views overlap.");
            }
        }
    }

    // Checks that there are no "holes", i.e. regions of the output which is not covered by a view.
    // Because we already checked that there are no overlaps, this can be done simply by checking that
    // the total 'volume' of the views is the same as the output.
    unsigned int totalViewsVolume = 0;
    for (unsigned int i = 0; i < inputShapes.size(); i++)
    {
        totalViewsVolume += inputShapes[i].GetNumElements();
    }
    unsigned int outputVolume = 1;
    for (unsigned int d = 0; d < numDims; d++)
    {
        outputVolume *= (extentMax[d] - extentMin[d]);
    }

    ConditionalThrowIfNotEqual<LayerValidationException>(
        "ConcatLayer: there are some gaps between views",
        totalViewsVolume,
        outputVolume);

    return std::vector<TensorShape>({ TensorShape({numDims, extentMax.data()}) });
}

ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

Check if the input tensor shape(s) will lead to a valid configuration of ConcatLayer.

Parameters

[in]

shapeInferenceMethod

Indicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 285 of file ConcatLayer.cpp.

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetNumInputSlots(), OriginsDescriptor::GetNumViews(), Layer::GetOutputSlot(), TensorInfo::GetShape(), armnn::GetTensorInfo(), OutputSlot::GetTensorInfo(), LayerWithParameters< OriginsDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

{
    // Validates Concat layer.
    ConditionalThrowIfNotEqual<LayerValidationException>(
        "ConcatLayer: Num Inputs must match num views.",
        m_Param.GetNumViews(),
        GetNumInputSlots());

    VerifyLayerConnections(m_Param.GetNumViews(), CHECK_LOCATION());

    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();

    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);

    std::vector<TensorShape> inputShapes;
    for (unsigned int i = 0; i < GetNumInputSlots(); ++i)
    {
        inputShapes.push_back(GetInputSlot(i).GetConnection()->GetTensorInfo().GetShape());
    }

    auto inferredShapes = InferOutputShapes(inputShapes);

    ARMNN_ASSERT(inferredShapes.size() == 1);

    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ConcatLayer");
}

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The documentation for this class was generated from the following files:

• src/armnn/layers/ConcatLayer.hpp
• src/armnn/layers/ConcatLayer.cpp