TensorInfo Class Reference

#include <Tensor.hpp>

Public Types
using	DifferenceType = std::vector<TensorInfo>::difference_type

Public Member Functions
	TensorInfo ()
	Empty (invalid) constructor.
	TensorInfo (const TensorShape &shape, DataType dataType, float quantizationScale=1.0f, int32_t quantizationOffset=0, bool isConstant=false)
	TensorInfo (unsigned int numDimensions, const unsigned int *dimensionSizes, DataType dataType, float quantizationScale=1.0f, int32_t quantizationOffset=0, bool isConstant=false)
	TensorInfo (const TensorShape &shape, DataType dataType, const std::vector< float > &quantizationScales, unsigned int quantizationDim, bool isConstant=false)
	TensorInfo (unsigned int numDimensions, const unsigned int *dimensionSizes, DataType dataType, const std::vector< float > &quantizationScales, unsigned int quantizationDim, bool isConstant=false)
	TensorInfo (const TensorInfo &other)
TensorInfo &	operator= (const TensorInfo &other)
bool	operator== (const TensorInfo &other) const
bool	operator!= (const TensorInfo &other) const
const TensorShape &	GetShape () const
TensorShape &	GetShape ()
void	SetShape (const TensorShape &newShape)
unsigned int	GetNumDimensions () const
unsigned int	GetNumElements () const
DataType	GetDataType () const
void	SetDataType (DataType type)
bool	HasMultipleQuantizationScales () const
bool	HasPerAxisQuantization () const
std::vector< float >	GetQuantizationScales () const
void	SetQuantizationScales (const std::vector< float > &scales)
float	GetQuantizationScale () const
void	SetQuantizationScale (float scale)
int32_t	GetQuantizationOffset () const
void	SetQuantizationOffset (int32_t offset)
Optional< unsigned int >	GetQuantizationDim () const
void	SetQuantizationDim (const Optional< unsigned int > &quantizationDim)
bool	IsQuantized () const
bool	IsConstant () const
void	SetConstant (const bool IsConstant=true)
	Marks the data corresponding to this tensor info as constant.
bool	IsTypeSpaceMatch (const TensorInfo &other) const
	Check that the types are the same and, if quantize, that the quantization parameters are the same.
unsigned int	GetNumBytes () const

Detailed Description

Examples

CustomMemoryAllocatorSample.cpp, DynamicSample.cpp, and SimpleSample.cpp.

Definition at line 152 of file Tensor.hpp.

Member Typedef Documentation

DifferenceType

using DifferenceType = std::vector<TensorInfo>::difference_type

Definition at line 191 of file Tensor.hpp.

Constructor & Destructor Documentation

TensorInfo() [1/6]

TensorInfo

(

)

Empty (invalid) constructor.

Definition at line 341 of file Tensor.cpp.

: m_DataType(DataType::Float32), m_IsConstant(false)
{
}

References armnn::Float32.

Referenced by IsTypeSpaceMatch(), operator!=(), operator=(), operator==(), and TensorInfo().

TensorInfo() [2/6]

TensorInfo	(	const TensorShape &	shape,
		DataType	dataType,
		float	quantizationScale = 1.0f,
		int32_t	quantizationOffset = 0,
		bool	isConstant = false )

Definition at line 346 of file Tensor.cpp.

    : m_Shape(shape)
    , m_DataType(dataType)
    , m_IsConstant(isConstant)
{
    SetQuantizationScale(quantizationScale);
    SetQuantizationOffset(quantizationOffset);
}

References SetQuantizationOffset(), and SetQuantizationScale().

TensorInfo() [3/6]

TensorInfo	(	unsigned int	numDimensions,
		const unsigned int *	dimensionSizes,
		DataType	dataType,
		float	quantizationScale = 1.0f,
		int32_t	quantizationOffset = 0,
		bool	isConstant = false )

Definition at line 359 of file Tensor.cpp.

    : m_Shape(numDimensions, dimensionSizes), m_DataType(dataType), m_IsConstant(isConstant)
{
    SetQuantizationScale(quantizationScale);
    SetQuantizationOffset(quantizationOffset);
}

References SetQuantizationOffset(), and SetQuantizationScale().

TensorInfo() [4/6]

TensorInfo	(	const TensorShape &	shape,
		DataType	dataType,
		const std::vector< float > &	quantizationScales,
		unsigned int	quantizationDim,
		bool	isConstant = false )

Definition at line 371 of file Tensor.cpp.

    : m_Shape(shape)
    , m_DataType(dataType)
    , m_IsConstant(isConstant)
{
    SetQuantizationScales(quantizationScales);
    SetQuantizationDim(MakeOptional<unsigned int>(quantizationDim));
}

References armnn::MakeOptional(), SetQuantizationDim(), and SetQuantizationScales().

TensorInfo() [5/6]

TensorInfo	(	unsigned int	numDimensions,
		const unsigned int *	dimensionSizes,
		DataType	dataType,
		const std::vector< float > &	quantizationScales,
		unsigned int	quantizationDim,
		bool	isConstant = false )

Definition at line 384 of file Tensor.cpp.

    : m_Shape(numDimensions, dimensionSizes)
    , m_DataType(dataType)
    , m_IsConstant(isConstant)
{
    SetQuantizationScales(quantizationScales);
    SetQuantizationDim(MakeOptional<unsigned int>(quantizationDim));
}

References armnn::MakeOptional(), SetQuantizationDim(), and SetQuantizationScales().

TensorInfo() [6/6]

TensorInfo

(

const TensorInfo &

other

)

Definition at line 398 of file Tensor.cpp.

: m_Shape(other.m_Shape)
, m_DataType(other.m_DataType)
, m_IsConstant(other.m_IsConstant)
, m_Quantization(other.m_Quantization)
{}

References TensorInfo().

Member Function Documentation

GetDataType()

DataType GetDataType ( ) const

inline

Definition at line 200 of file Tensor.hpp.

{ return m_DataType; }

Referenced by BiasAndWeightsTypesMatch::BiasAndWeightsTypesMatch(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), armnn::ClCastValidate(), armnn::ClConvertFp16ToFp32WorkloadValidate(), armnn::ClConvertFp32ToFp16WorkloadValidate(), armnn::ClMultiplicationWorkloadValidate(), armnn::ClTileWorkloadValidate(), armnn::ClUnidirectionalSequenceLstmFloatWorkloadValidate(), ConvertQuantizeToTosaOperator(), ConvertSoftmaxToTosaOperator(), RefGatherWorkload::Execute(), RefTileWorkload::Execute(), Layer::GetDataType(), armnn::GetLayerInOutDatatype(), armnn::optimizations::pad_fold::GetLowestElement(), armnn::GetUnpaddedTensorStrides(), armnn::InitializeArmComputeClTensorData(), armnn::InitializeArmComputeTensorData(), armnn::InitializeArmComputeTensorData(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), SampleDynamicLayerSupport::IsAdditionSupported(), RefLayerSupport::IsConvertFp16ToFp32Supported(), RefLayerSupport::IsConvertFp32ToFp16Supported(), RefLayerSupport::IsConvolution2dSupported(), RefLayerSupport::IsConvolution3dSupported(), RefLayerSupport::IsDepthwiseConvolutionSupported(), NeonLayerSupport::IsFloorSupported(), armnn::IsLayerSequence(), ClLayerSupport::IsQLstmSupported(), NeonLayerSupport::IsQLstmSupported(), RefLayerSupport::IsTransposeConvolution2dSupported(), NeonLayerSupport::IsUnidirectionalSequenceLstmSupported(), armnn::LstmImpl(), armnn::NeonCastValidate(), armnn::NeonMultiplicationWorkloadValidate(), armnn::NeonTileWorkloadValidate(), armnn::NeonUnidirectionalSequenceLstmFloatWorkloadValidate(), armnn::NeonUnidirectionalSequenceLstmWorkloadValidate(), armnn::Pad(), armnn::PermuteTensor(), ConvertFp32NetworkToFp16Impl::Run(), armnnUtils::ToFloatArray(), ArgMinMaxQueueDescriptor::Validate(), ComparisonQueueDescriptor::Validate(), ConvertFp16ToFp32QueueDescriptor::Validate(), ConvertFp32ToFp16QueueDescriptor::Validate(), Convolution2dQueueDescriptor::Validate(), Convolution3dQueueDescriptor::Validate(), DepthwiseConvolution2dQueueDescriptor::Validate(), EqualQueueDescriptor::Validate(), FullyConnectedQueueDescriptor::Validate(), GatherNdQueueDescriptor::Validate(), GatherQueueDescriptor::Validate(), GreaterQueueDescriptor::Validate(), LogicalBinaryQueueDescriptor::Validate(), QuantizeQueueDescriptor::Validate(), TransposeConvolution2dQueueDescriptor::Validate(), ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl(), ConvertConstPermuteLayersToConstLayers::~ConvertConstPermuteLayersToConstLayers(), and TurboConvertConstDequantisationLayersToConstLayersImpl::~TurboConvertConstDequantisationLayersToConstLayersImpl().

GetNumBytes()

unsigned int GetNumBytes

(

)

const

Definition at line 427 of file Tensor.cpp.

{
    return GetDataTypeSize(m_DataType) * GetNumElements();
}

References armnn::GetDataTypeSize(), and GetNumElements().

Referenced by armnnOnnxParser::CreateConstTensorImpl(), armnn::PermuteTensor(), armnn::ReorderWeightChannelsForAcl(), and ScopedTensorHandle::ScopedTensorHandle().

GetNumDimensions()

unsigned int GetNumDimensions ( ) const

inline

Definition at line 197 of file Tensor.hpp.

{ return m_Shape.GetNumDimensions(); }

Referenced by armnn::ArgMinMax(), armnn::BatchToSpaceNd(), armnn::BuildAddMulAddTensorInfoLists(), armnn::CalculateGatherNdKeyIndices(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), armnn::ClArgMinMaxWorkloadValidate(), armnn::ClBatchToSpaceNdWorkloadValidate(), armnn::ClChannelShuffleValidate(), ClGatherNdWorkload::ClGatherNdWorkload(), armnn::ClGatherNdWorkloadValidate(), armnn::ClMeanValidate(), armnn::ClReduceWorkloadValidate(), armnn::ClSpaceToBatchNdWorkloadValidate(), armnn::ClSplitterWorkloadValidate(), armnn::ClStridedSliceWorkloadValidate(), armnn::CollapseLeadingUnitDimensions(), armnn::ComputeAclAxis(), armnn::ComputeReductionTensorShape(), armnn::ComputeSoftmaxAclAxis(), armnn::Concatenate(), armnn::ConnectedToLayerType(), ConvertSoftmaxToTosaOperator(), armnn::Gather(), armnn::GetNumActivations(), RefLayerSupport::IsMeanSupported(), armnn::LogSoftmax(), armnn::NeonArgMinMaxWorkloadValidate(), armnn::NeonBatchToSpaceNdWorkloadValidate(), armnn::NeonChannelShuffleValidate(), NeonGatherNdWorkload::NeonGatherNdWorkload(), armnn::NeonGatherNdWorkloadValidate(), armnn::NeonMeanWorkloadValidate(), armnn::NeonReduceWorkloadValidate(), armnn::NeonSpaceToBatchNdWorkloadValidate(), armnn::NeonSplitterWorkloadValidate(), armnn::NeonStridedSliceWorkloadValidate(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::PrintOutput(), armnnUtils::ProcessConcatInputTensorInfo(), armnn::Reduce(), armnn::ReverseV2(), AddBroadcastReshapeLayerImpl::Run(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), armnn::ScatterNd(), armnn::ScatterNd(), armnn::Softmax(), armnn::SpaceToBatchNd(), armnn::Split(), armnn::Splitter(), armnn::Stack(), armnn::Tile(), BatchMatMulQueueDescriptor::Validate(), FullyConnectedQueueDescriptor::Validate(), GatherNdQueueDescriptor::Validate(), GatherQueueDescriptor::Validate(), InstanceNormalizationQueueDescriptor::Validate(), L2NormalizationQueueDescriptor::Validate(), MeanQueueDescriptor::Validate(), PadQueueDescriptor::Validate(), ReverseV2QueueDescriptor::Validate(), SliceQueueDescriptor::Validate(), SpaceToBatchNdQueueDescriptor::Validate(), StridedSliceQueueDescriptor::Validate(), TileQueueDescriptor::Validate(), QueueDescriptor::ValidateTensorNumDimensions(), ReduceLayer::ValidateTensorShapesFromInputs(), and ScatterNdLayer::ValidateTensorShapesFromInputs().

GetNumElements()

unsigned int GetNumElements ( ) const

inline

Examples

CustomMemoryAllocatorSample.cpp.

Definition at line 198 of file Tensor.hpp.

{ return m_Shape.GetNumElements(); }

Referenced by armnn::Activation(), armnnUtils::CheckSizes(), armnn::Concatenate(), armnnOnnxParser::CreateConstTensorImpl(), armnn::Dequantize(), armnn::DetectionPostProcess(), armnn::Gather(), GetNumBytes(), armnn::MirrorPad(), IDeserializer::DeserializerImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfReshape(), armnn::Pad(), armnn::PrintOutput(), armnn::Reduce(), armnn::ReverseV2(), armnn::ScatterNd(), armnn::ScatterNd(), ShapesAreSameTotalSize::ShapesAreSameTotalSize(), armnn::Split(), armnn::Splitter(), armnn::Stack(), armnn::Tile(), armnnDeserializer::ToConstTensor(), armnnUtils::ToFloatArray(), armnnUtils::ToFloatArray(), SpaceToBatchNdQueueDescriptor::Validate(), ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl(), ConvertConstPermuteLayersToConstLayers::~ConvertConstPermuteLayersToConstLayers(), and TurboConvertConstDequantisationLayersToConstLayersImpl::~TurboConvertConstDequantisationLayersToConstLayersImpl().

GetQuantizationDim()

Optional< unsigned int > GetQuantizationDim

(

)

const

Definition at line 498 of file Tensor.cpp.

{
    return m_Quantization.m_QuantizationDim;
}

Referenced by armnnUtils::ToFloatArray().

GetQuantizationOffset()

int32_t GetQuantizationOffset

(

)

const

Definition at line 482 of file Tensor.cpp.

{
    if (!m_Quantization.m_Offset.has_value())
    {
        // NOTE: old default for backward compatibility
        return 0;
    }
 
    return m_Quantization.m_Offset.value();
}

Referenced by ConvertQuantizeToTosaOperator(), ConvertSoftmaxToTosaOperator(), armnn::optimizations::pad_fold::GetLowestElement(), armnn::optimizations::pad_fold::GetZeroElement(), armnn::IsMultiAxesReduceSupported(), IsTypeSpaceMatch(), QuantizationParametersAreEqual::QuantizationParametersAreEqual(), armnnUtils::ToFloatArray(), QLstmQueueDescriptor::Validate(), and ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl().

GetQuantizationScale()

float GetQuantizationScale

(

)

const

Definition at line 461 of file Tensor.cpp.

{
    if (m_Quantization.m_Scales.empty())
    {
        // NOTE: old default for backward compatibility
        return 1.0f;
    }
 
    if (HasMultipleQuantizationScales())
    {
        throw RuntimeException("Invalid call to GetQuantizationScale on a tensor with multiple scale values. Use "
                               "GetQuantizationScales instead.");
    }
    return m_Quantization.m_Scales[0];
}

References HasMultipleQuantizationScales().

Referenced by ConvertQuantizeToTosaOperator(), ConvertSoftmaxToTosaOperator(), armnn::optimizations::pad_fold::GetLowestElement(), armnn::IsMultiAxesReduceSupported(), IsTypeSpaceMatch(), QuantizationParametersAreEqual::QuantizationParametersAreEqual(), armnnUtils::ToFloatArray(), QLstmQueueDescriptor::Validate(), and ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl().

GetQuantizationScales()

std::vector< float > GetQuantizationScales

(

)

const

Definition at line 451 of file Tensor.cpp.

{
    return m_Quantization.m_Scales;
}

Referenced by armnn::IsMultiAxesReduceSupported(), and armnnUtils::ToFloatArray().

GetShape() [1/2]

TensorShape & GetShape ( )

inline

Definition at line 194 of file Tensor.hpp.

{ return m_Shape; }

GetShape() [2/2]

const TensorShape & GetShape ( ) const

inline

Definition at line 193 of file Tensor.hpp.

{ return m_Shape; }

Referenced by armnn::ArgMinMax(), armnn::BatchNormImpl(), armnn::BatchToSpaceNd(), armnn::CalculateGatherNdKeyIndices(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), ClGatherNdWorkload::ClGatherNdWorkload(), ClLstmFloatWorkload::ClLstmFloatWorkload(), armnn::ClUnidirectionalSequenceLstmFloatWorkloadValidate(), armnn::CollapseLeadingUnitDimensions(), armnn::Concatenate(), armnn::Convert1HWOTensorInfoToAcl(), armnn::Convert1HWOTensorToAcl(), armnn::Convert1HWOtoMIHW(), ConvertConstantToTosaOperator(), ConvertQuantizeToTosaOperator(), ConvertSoftmaxToTosaOperator(), armnn::ConvertWeightTensorFromArmnnToAcl(), armnn::CreateAclNormalizationLayerInfoForL2Normalization(), armnnOnnxParser::CreateConstTensorImpl(), armnn::DepthToSpace(), armnn::DetectionPostProcess(), armnn::ExecuteFunction(), armnn::Gather(), armnn::GetNumActivations(), armnn::GetUnpaddedTensorStrides(), armnn::InstanceNorm(), armnn::IsMultiAxesReduceSupported(), ClLayerSupport::IsSplitterSupported(), NeonLayerSupport::IsSplitterSupported(), armnn::LogSoftmax(), armnn::LstmImpl(), armnn::MirrorPad(), NeonGatherNdWorkload::NeonGatherNdWorkload(), NeonLstmFloatWorkload::NeonLstmFloatWorkload(), armnn::NeonUnidirectionalSequenceLstmFloatWorkloadValidate(), armnn::NeonUnidirectionalSequenceLstmWorkloadValidate(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::Pad(), armnn::PermuteTensor(), armnn::Pooling2d(), armnn::Pooling3d(), armnn::PreluImpl(), armnn::PrintOutput(), armnnUtils::ProcessConcatInputTensorInfo(), armnn::Reduce(), armnnUtils::ReduceDims(), RefTransposeConvolution2dWorkload::RefTransposeConvolution2dWorkload(), armnn::ReshapeWeightsForAcl(), armnn::Resize(), armnn::ReverseV2(), AddBroadcastReshapeLayerImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), OptimizeConsecutiveReshapesImpl::Run(), PermuteAsReshapeImpl::Run(), TransposeAsReshapeImpl::Run(), armnn::ScatterNd(), armnn::ScatterNd(), Convolution2dLayer::SerializeLayerParameters(), Convolution3dLayer::SerializeLayerParameters(), DepthwiseConvolution2dLayer::SerializeLayerParameters(), Graph::SerializeToDot(), ShapesAreBroadcastCompatible::ShapesAreBroadcastCompatible(), ShapesAreSameRank::ShapesAreSameRank(), armnn::Slice(), armnn::Softmax(), armnn::SpaceToBatchNd(), armnn::SpaceToDepth(), armnn::Split(), armnn::Splitter(), armnn::Stack(), armnn::StridedSlice(), armnn::Tile(), armnnUtils::ToFloatArray(), ArgMinMaxQueueDescriptor::Validate(), BatchMatMulQueueDescriptor::Validate(), BatchToSpaceNdQueueDescriptor::Validate(), DepthToSpaceQueueDescriptor::Validate(), DepthwiseConvolution2dQueueDescriptor::Validate(), DetectionPostProcessQueueDescriptor::Validate(), PermuteQueueDescriptor::Validate(), QLstmQueueDescriptor::Validate(), QuantizedLstmQueueDescriptor::Validate(), ResizeQueueDescriptor::Validate(), SliceQueueDescriptor::Validate(), SpaceToBatchNdQueueDescriptor::Validate(), SpaceToDepthQueueDescriptor::Validate(), TransposeQueueDescriptor::Validate(), QueueDescriptor::ValidateTensorNumDimensions(), AbsLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), BroadcastToLayer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), ElementwiseBinaryLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), QLstmLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), ReverseV2Layer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), ScatterNdLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), TileLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl(), ConvertConstPermuteLayersToConstLayers::~ConvertConstPermuteLayersToConstLayers(), PermuteAsReshapeImpl::~PermuteAsReshapeImpl(), TransposeAsReshapeImpl::~TransposeAsReshapeImpl(), and TurboConvertConstDequantisationLayersToConstLayersImpl::~TurboConvertConstDequantisationLayersToConstLayersImpl().

HasMultipleQuantizationScales()

bool HasMultipleQuantizationScales ( ) const

inline

Definition at line 203 of file Tensor.hpp.

{ return m_Quantization.m_Scales.size() > 1; }

Referenced by GetQuantizationScale(), HasPerAxisQuantization(), armnn::IsMultiAxesReduceSupported(), and IsTypeSpaceMatch().

HasPerAxisQuantization()

bool HasPerAxisQuantization

(

)

const

Definition at line 446 of file Tensor.cpp.

{
    return HasMultipleQuantizationScales() || m_Quantization.m_QuantizationDim.has_value();
}

References HasMultipleQuantizationScales().

Referenced by armnn::Convert1HWOtoMIHW(), and armnnUtils::ToFloatArray().

IsConstant()

bool IsConstant

(

)

const

Definition at line 513 of file Tensor.cpp.

{
    return m_IsConstant;
}

Referenced by armnn::ClConvolution2dWorkloadValidate(), armnn::ClDepthwiseConvolutionWorkloadValidate(), armnn::ClFullyConnectedWorkloadValidate(), LayerSupportHandle::IsConvolution2dSupported(), LayerSupportHandle::IsDepthwiseConvolutionSupported(), LayerSupportHandle::IsDilatedDepthwiseConvolutionSupported(), LayerSupportHandle::IsFullyConnectedSupported(), armnn::NeonConvolution2dWorkloadValidate(), armnn::NeonDepthwiseConvolutionWorkloadValidate(), armnn::NeonFullyConnectedWorkloadValidate(), SetConstant(), ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl(), ConvertConstPermuteLayersToConstLayers::~ConvertConstPermuteLayersToConstLayers(), and TurboConvertConstDequantisationLayersToConstLayersImpl::~TurboConvertConstDequantisationLayersToConstLayersImpl().

IsQuantized()

bool IsQuantized

(

)

const

Definition at line 508 of file Tensor.cpp.

{
    return IsQuantizedType(m_DataType);
}

References armnn::IsQuantizedType().

Referenced by armnn::optimizations::pad_fold::GetZeroElement(), IsTypeSpaceMatch(), armnn::Pad(), and armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d().

IsTypeSpaceMatch()

bool IsTypeSpaceMatch

(

const TensorInfo &

other

)

const

Check that the types are the same and, if quantize, that the quantization parameters are the same.

Definition at line 432 of file Tensor.cpp.

{
    bool match = true;
 
    match &= m_DataType == other.m_DataType;
 
    if (IsQuantized() && !HasMultipleQuantizationScales())
    {
        match &= GetQuantizationScale() == other.GetQuantizationScale() &&
                 GetQuantizationOffset() == other.GetQuantizationOffset();
    }
    return match;
}

References GetQuantizationOffset(), GetQuantizationScale(), HasMultipleQuantizationScales(), IsQuantized(), and TensorInfo().

Referenced by ClLayerSupport::IsConcatSupported(), NeonLayerSupport::IsConcatSupported(), ClLayerSupport::IsSplitterSupported(), and NeonLayerSupport::IsSplitterSupported().

operator!=()

bool operator!=

(

const TensorInfo &

other

)

const

Definition at line 422 of file Tensor.cpp.

{
    return !(*this == other);
}

References TensorInfo().

operator=()

TensorInfo & operator=

(

const TensorInfo &

other

)

Definition at line 405 of file Tensor.cpp.

{
    m_Shape = other.m_Shape;
    m_DataType = other.m_DataType;
    m_Quantization = other.m_Quantization;
    m_IsConstant = other.m_IsConstant;
    return *this;
}

References TensorInfo().

operator==()

bool operator==

(

const TensorInfo &

other

)

const

Definition at line 414 of file Tensor.cpp.

{
    return ((m_Shape == other.m_Shape) &&
            (m_DataType == other.m_DataType) &&
            (m_Quantization == other.m_Quantization) &&
            (m_IsConstant == other.m_IsConstant));
}

References TensorInfo().

SetConstant()

void SetConstant

(

const bool

IsConstant = true

)

Marks the data corresponding to this tensor info as constant.

: This can allow further optimization on execution @Note: The user has to ensure that the underlying data actually is constant.

Examples

CustomMemoryAllocatorSample.cpp, DynamicSample.cpp, and SimpleSample.cpp.

Definition at line 518 of file Tensor.cpp.

{
    m_IsConstant = IsConstant;
}

References IsConstant().

Referenced by ConstTensor::ConstTensor(), TfLiteParserImpl::GetNetworkInputBindingInfo(), armnnUtils::MakeInputTensors(), armnn::PermuteTensor(), armnnDeserializer::ToConstTensor(), ConvertConstDequantisationLayersToConstLayersImpl::~ConvertConstDequantisationLayersToConstLayersImpl(), ConvertConstPermuteLayersToConstLayers::~ConvertConstPermuteLayersToConstLayers(), and TurboConvertConstDequantisationLayersToConstLayersImpl::~TurboConvertConstDequantisationLayersToConstLayersImpl().

SetDataType()

void SetDataType ( DataType type )

inline

Definition at line 201 of file Tensor.hpp.

{ m_DataType = type; }

Referenced by armnn::AttemptBackendAssignment(), armnn::ConvertTensorToFloat32(), ConvertToDataType(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), and ConvertFp32NetworkToFp16Impl::Run().

SetQuantizationDim()

void SetQuantizationDim

(

const Optional< unsigned int > &

quantizationDim

)

Definition at line 503 of file Tensor.cpp.

{
    m_Quantization.m_QuantizationDim = quantizationDim;
}

Referenced by armnnUtils::Permuted(), TensorInfo(), and TensorInfo().

SetQuantizationOffset()

void SetQuantizationOffset

(

int32_t

offset

)

Definition at line 493 of file Tensor.cpp.

{
    m_Quantization.m_Offset = MakeOptional<int32_t>(offset);
}

References armnn::MakeOptional().

Referenced by armnn::IsMultiAxesReduceSupported(), TensorInfo(), and TensorInfo().

SetQuantizationScale()

void SetQuantizationScale

(

float

scale

)

Definition at line 477 of file Tensor.cpp.

{
    m_Quantization.m_Scales = { scale };
}

Referenced by armnn::IsMultiAxesReduceSupported(), TensorInfo(), and TensorInfo().

SetQuantizationScales()

void SetQuantizationScales

(

const std::vector< float > &

scales

)

Definition at line 456 of file Tensor.cpp.

{
    m_Quantization.m_Scales = scales;
}

Referenced by armnn::IsMultiAxesReduceSupported(), TensorInfo(), and TensorInfo().

SetShape()

void SetShape ( const TensorShape & newShape )

inline

Definition at line 195 of file Tensor.hpp.

{ m_Shape = newShape; }

Referenced by ClGatherNdWorkload::ClGatherNdWorkload(), armnn::ClGatherNdWorkloadValidate(), ClUnidirectionalSequenceLstmFloatWorkload::ClUnidirectionalSequenceLstmFloatWorkload(), armnn::CollapseLeadingUnitDimensions(), armnn::Convert1HWOtoMIHW(), NeonGatherNdWorkload::NeonGatherNdWorkload(), armnn::NeonGatherNdWorkloadValidate(), NeonUnidirectionalSequenceLstmFloatWorkload::NeonUnidirectionalSequenceLstmFloatWorkload(), NeonUnidirectionalSequenceLstmWorkload::NeonUnidirectionalSequenceLstmWorkload(), IDeserializer::DeserializerImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnnUtils::Permuted(), armnnUtils::ReduceDims(), armnn::RemoveReshapeLayer(), armnn::ReshapeWeightsForAcl(), AddBroadcastReshapeLayerImpl::Run(), and armnnUtils::TransposeTensorShape().

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

• include/armnn/Tensor.hpp
• src/armnn/Tensor.cpp