This layer represents a strided slice operation. More...

#include <StridedSliceLayer.hpp>

Inheritance diagram for StridedSliceLayer:

Collaboration diagram for StridedSliceLayer:

Public Member Functions
virtual std::unique_ptr< IWorkload >	CreateWorkload (const IWorkloadFactory &factory) const override
	Makes a workload for the StridedSlice type.
StridedSliceLayer *	Clone (Graph &graph) const override
	Creates a dynamically-allocated copy of this layer.
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.
void	ValidateTensorShapesFromInputs () override
	Check if the input tensor shape(s) will lead to a valid configuration of StridedSliceLayer.
void	ExecuteStrategy (IStrategy &strategy) const override
	Apply a visitor to this layer.
Public Member Functions inherited from LayerWithParameters< StridedSliceDescriptor >
const StridedSliceDescriptor &	GetParameters () const override
	If the layer has a descriptor return it.
void	SerializeLayerParameters (ParameterStringifyFunction &fn) const override
	Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
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
bool	GetAllowExpandedDims () 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 override
	Returns the armnn::LayerType of this layer.
DataType	GetDataType () const
const BackendId &	GetBackendId () const
void	SetBackendId (const BackendId &id) override
	Set the backend of the IConnectableLayer.
virtual void	CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
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.
unsigned int	GetNumInputSlots () const override
	Returns the number of connectable input slots.
unsigned int	GetNumOutputSlots () const override
	Returns the number of connectable output slots.
const InputSlot &	GetInputSlot (unsigned int index) const override
	Get a const input slot handle by slot index.
InputSlot &	GetInputSlot (unsigned int index) override
	Get the input slot handle by slot index.
const OutputSlot &	GetOutputSlot (unsigned int index=0) const override
	Get the const output slot handle by slot index.
OutputSlot &	GetOutputSlot (unsigned int index=0) override
	Get the output slot handle by slot index.
void	SetGuid (LayerGuid guid)
LayerGuid	GetGuid () const final
	Returns the unique id of the layer.
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.
Optional< BackendId >	GetBackendHint () const
void	SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)
void	SetAllowExpandedDims (bool allowExpandedDims)
template<typename T>
std::shared_ptr< T >	GetAdditionalInformation () const
void	SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)

Protected Member Functions
	StridedSliceLayer (const StridedSliceDescriptor &param, const char *name)
	Constructor to create a StridedSliceLayer.
	~StridedSliceLayer ()=default
	Default destructor.
Protected Member Functions inherited from LayerWithParameters< StridedSliceDescriptor >
	LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const StridedSliceDescriptor &param, const char *name)
	~LayerWithParameters ()=default
WorkloadInfo	PrepInfoAndDesc (QueueDescriptor &descriptor) const
	Helper function to reduce duplication in *LayerCreateWorkload.
Layer::ImmutableConstantTensors	GetConnectedConstantAsInputTensors () const
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.
template<typename LayerType, typename ... Params>
LayerType *	CloneBase (Graph &graph, Params &&... params) const
virtual ConstantTensors	GetConstantTensorsByRef () override final
virtual ImmutableConstantTensors	GetConstantTensorsByRef () const override
void	SetAdditionalInfo (QueueDescriptor &descriptor) const
Protected Member Functions inherited from IConnectableLayer
	~IConnectableLayer ()
	Objects are not deletable via the handle.

Additional Inherited Members
Public Types inherited from LayerWithParameters< StridedSliceDescriptor >
using	DescriptorType
Public Types inherited from IConnectableLayer
using	ConstantTensors = std::vector<std::reference_wrapper<std::shared_ptr<ConstTensorHandle>>>
using	ImmutableConstantTensors = std::vector<std::reference_wrapper<const std::shared_ptr<ConstTensorHandle>>>
Protected Attributes inherited from LayerWithParameters< StridedSliceDescriptor >
StridedSliceDescriptor	m_Param
	The parameters for the layer (not including tensor-valued weights etc.).
Protected Attributes inherited from Layer
AdditionalInfoObjectPtr	m_AdditionalInfoObject
std::vector< OutputHandler >	m_OutputHandlers
ShapeInferenceMethod	m_ShapeInferenceMethod

Detailed Description

This layer represents a strided slice operation.

Definition at line 13 of file StridedSliceLayer.hpp.

Constructor & Destructor Documentation

◆ StridedSliceLayer()

StridedSliceLayer	(	const StridedSliceDescriptor &	param,
		const char *	name )

protected

Constructor to create a StridedSliceLayer.

Parameters

[in]	param	StridedSliceDescriptor to configure the strided slice layer.
[in]	name	Optional name for the layer.

Definition at line 20 of file StridedSliceLayer.cpp.

    : LayerWithParameters(1, 1, LayerType::StridedSlice, param, name)
{
}

References LayerWithParameters< StridedSliceDescriptor >::LayerWithParameters(), and armnn::StridedSlice().

Referenced by Clone().

◆ ~StridedSliceLayer()

~StridedSliceLayer ( )

protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

StridedSliceLayer * 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 45 of file StridedSliceLayer.cpp.

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

References Layer::CloneBase(), Layer::GetName(), LayerWithParameters< StridedSliceDescriptor >::m_Param, and StridedSliceLayer().

◆ CreateWorkload()

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

overridevirtual

Makes a workload for the StridedSlice 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 25 of file StridedSliceLayer.cpp.

{
    StridedSliceQueueDescriptor descriptor;
 
    descriptor.m_Parameters.m_Begin  = m_Param.m_Begin;
    descriptor.m_Parameters.m_End    = m_Param.m_End;
    descriptor.m_Parameters.m_Stride = m_Param.m_Stride;
 
    // Optional parameters
    descriptor.m_Parameters.m_BeginMask      = m_Param.m_BeginMask;
    descriptor.m_Parameters.m_EndMask        = m_Param.m_EndMask;
    descriptor.m_Parameters.m_EllipsisMask   = m_Param.m_EllipsisMask;
    descriptor.m_Parameters.m_NewAxisMask    = m_Param.m_NewAxisMask;
    descriptor.m_Parameters.m_ShrinkAxisMask = m_Param.m_ShrinkAxisMask;
 
    SetAdditionalInfo(descriptor);
 
    return factory.CreateWorkload(LayerType::StridedSlice, descriptor, PrepInfoAndDesc(descriptor));
}

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy ) const

overridevirtual

Apply a visitor to this layer.

Reimplemented from LayerWithParameters< StridedSliceDescriptor >.

Definition at line 203 of file StridedSliceLayer.cpp.

{
    strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< StridedSliceDescriptor >::GetParameters().

◆ 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 52 of file StridedSliceLayer.cpp.

{
    if (inputShapes.size() != 1)
    {
        throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
                               "\" - should be \"1\".");
    }
 
    TensorShape inputShape = inputShapes[0];
    std::vector<unsigned int> outputShape;
    unsigned int amountDimShrunk{0};
 
    // Getting the actual number of output dimensions, including axes added with the NewAxisMask
    unsigned int outputDims = inputShape.GetNumDimensions();
    for(unsigned int i = 0; i < m_Param.m_Begin.size(); ++i)
    {
        // Adding to dimension count for every set bit of NewAxisMask not covered by the EllipsisMask
        if(m_Param.m_NewAxisMask & (1 << i) && !(m_Param.m_EllipsisMask & (1 << i)))
        {
            ++outputDims;
        }
    }
 
    // Modifying the EllipsisMask based on the NewAxisMask (expand for any newly added axes)
    // and the NewAxisMask based on the EllipsisMask (offset based on the expanded ellipsis)
    int realEllipsisMask = 0, realNewAxisMask = 0;
    // The number of bits the ellipsis mask was expanded by
    unsigned int ellipsisExpandedBy = 0;
    for(unsigned int i = 0; i < outputDims; ++i)
    {
        if(m_Param.m_EllipsisMask & (1 << i))
        {
            // The end index of the expanded ellipsis mask (start is at i)
            // End Index calculation - i+1 (for non-expanded ellipsis) + outputDims-inputDims (number of added dims)
            unsigned int endIdx = std::min(i + 1u + outputDims - inputShape.GetNumDimensions(), outputDims);
 
            // Calculation: the total size of the mask -1 for the already existing bit in the original mask
            ellipsisExpandedBy = endIdx - i - 1;
 
            // Setting mask bit to 1 for the entire expanded ellipsis
            for(; i < endIdx; ++i)
            {
                realEllipsisMask |= (1 << i);
            }
        }
 
        // Setting the real NewAxisMask based on the expanded ellipsis size
        if(m_Param.m_NewAxisMask & (1 << (i - ellipsisExpandedBy)))
        {
            realNewAxisMask |= (1 << i);
        }
    }
 
    // The backwards offset by which i is ahead of the actual inputTensor dimension
    unsigned int inputDimOffset = 0;
    // Iterating through the parameters and inferring output shape
    for (unsigned int i = 0; i < outputDims; ++i)
    {
        // Add entire dimension if EllipsisMask is set
        if(realEllipsisMask & (1 << i))
        {
            outputShape.push_back(inputShape[i - inputDimOffset]);
            continue;
        }
        // Add dimension of length 1 if NewAxisMask is set
        if(realNewAxisMask & (1 << i))
        {
            outputShape.push_back(1);
            ++inputDimOffset;
            continue;
        }
        // Fill the rest of the inferred shape (dimensions greater than the input shape)
        if(i >= inputShape.GetNumDimensions())
        {
            // If EllipsisMask was set at any point, the TensorFlow behavior is to fill the rest of the tensor with 1
            // Otherwise, the remaining dimensions from the inputShape (which were skipped over) are used
            if(realEllipsisMask > 0)
            {
                outputShape.push_back(1);
            }
            else
            {
                outputShape.push_back(inputShape[i - inputDimOffset]);
            }
            continue;
        }
 
        int stride = m_Param.m_Stride[i];
        int start = m_Param.GetStartForAxis(inputShape, i);
        int stop = m_Param.GetStopForAxis(inputShape, i, start);
 
        if (m_Param.m_ShrinkAxisMask & (1 << i))
        {
            amountDimShrunk+=1;
 
            // If the difference between the start point and the end point of the slice on an axis being shrunk
            // is greater than 1 then throw an error as the output will not be large enough to hold the slice
            if (((m_Param.m_Begin[i] - m_Param.m_End[i]) > 1) || ((m_Param.m_Begin[i] - m_Param.m_End[i]) < -1))
            {
                throw LayerValidationException(
                    "StridedSlice: Attempting to take a larger slice than can fit in inferred output");
            }
 
            if (stride <= 0)
            {
                // Prevent divide by zero error below
                throw LayerValidationException("StridedSlice: Stride must be 1 or more.");
            }
            continue;
        }
 
        int newSize = stride > 0 ? ((stop - start) + stride - 1) / stride :
                                   ((start - stop) - stride - 1) / -stride;
 
        // Making sure the dimension size doesn't go out of bounds
        newSize = std::max(0, newSize);
        newSize = std::min(newSize, armnn::numeric_cast<int>(inputShape[i - inputDimOffset]));
 
        outputShape.push_back(armnn::numeric_cast<unsigned int>(newSize));
    }
 
    if (outputShape.size() == 0 && (inputShape.GetNumDimensions() - amountDimShrunk) == 0)
    {
        outputShape.push_back(1);
    }
 
    return std::vector<TensorShape>({
        TensorShape(armnn::numeric_cast<unsigned int>(outputShape.size()), &outputShape[0]) });
}

References TensorShape::GetNumDimensions(), LayerWithParameters< StridedSliceDescriptor >::m_Param, and armnn::numeric_cast().

Referenced by ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )

overridevirtual

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

Parameters

[in] shapeInferenceMethod Indicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 183 of file StridedSliceLayer.cpp.

{
    VerifyLayerConnections(1, CHECK_LOCATION());
 
    const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
 
    VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
 
    auto inferredShapes = InferOutputShapes({GetInputSlot(0).GetTensorInfo().GetShape()});
 
    if (inferredShapes.size() != 1)
    {
        throw armnn::LayerValidationException("inferredShapes has "
                                              + std::to_string(inferredShapes.size()) +
                                              " elements - should only have 1.");
    }
 
    ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "StridedSliceLayer");
}

References CHECK_LOCATION, Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), InputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), InferOutputShapes(), Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().

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

src/armnn/layers/StridedSliceLayer.hpp
src/armnn/layers/StridedSliceLayer.cpp

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ StridedSliceLayer()

◆ ~StridedSliceLayer()

Member Function Documentation

◆ Clone()

◆ CreateWorkload()

◆ ExecuteStrategy()

◆ InferOutputShapes()

◆ ValidateTensorShapesFromInputs()