TensorInfo Class Reference

#include <Tensor.hpp>

Public Member Functions
	TensorInfo ()
	Empty (invalid) constructor. More...
	TensorInfo (const TensorShape &shape, DataType dataType, float quantizationScale=0.0f, int32_t quantizationOffset=0, bool isConstant=false)
	TensorInfo (unsigned int numDimensions, const unsigned int *dimensionSizes, DataType dataType, float quantizationScale=0.0f, 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. More...
bool	IsTypeSpaceMatch (const TensorInfo &other) const
	Check that the types are the same and, if quantize, that the quantization parameters are the same. More...
unsigned int	GetNumBytes () const

Detailed Description

Examples:

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

Definition at line 152 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)
{
}

TensorInfo() [2/6]

TensorInfo	(	const TensorShape &	shape,
		DataType	dataType,
		float	quantizationScale = 0.0f,
		int32_t	quantizationOffset = 0,
		bool	isConstant = false
	)

Definition at line 346 of file Tensor.cpp.

References TensorInfo::SetQuantizationOffset(), and TensorInfo::SetQuantizationScale().

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

TensorInfo() [3/6]

TensorInfo	(	unsigned int	numDimensions,
		const unsigned int *	dimensionSizes,
		DataType	dataType,
		float	quantizationScale = 0.0f,
		int32_t	quantizationOffset = 0,
		bool	isConstant = false
	)

Definition at line 359 of file Tensor.cpp.

References TensorInfo::SetQuantizationOffset(), and TensorInfo::SetQuantizationScale().

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

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.

References TensorInfo::SetQuantizationDim(), and TensorInfo::SetQuantizationScales().

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

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.

References TensorInfo::SetQuantizationDim(), and TensorInfo::SetQuantizationScales().

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

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)
{}

Member Function Documentation

GetDataType()

DataType GetDataType ( ) const

inline

Definition at line 198 of file Tensor.hpp.

Referenced by armnnTfLiteParser::AsFloatArray(), BiasAndWeightsTypesCompatible::BiasAndWeightsTypesCompatible(), BiasAndWeightsTypesMatch::BiasAndWeightsTypesMatch(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), RefTensorHandle::CanBeImported(), TosaRefTensorHandle::CanBeImported(), armnn::CheckScaleSetOnQuantizedType(), armnn::ClConvertFp16ToFp32WorkloadValidate(), armnn::ClConvertFp32ToFp16WorkloadValidate(), armnnTfLiteParser::ComputeWrappedIndex(), armnn::ConvertBf16ToFp32Weight(), Converter::ConvertOperation(), armnn_driver::ConvertToLayerInputHandle(), armnn::optimizations::ConvertWeight(), RefDepthToSpaceWorkload::ExecuteAsync(), RefStridedSliceWorkload::ExecuteAsync(), RefArgMinMaxWorkload::ExecuteAsync(), RefSliceWorkload::ExecuteAsync(), RefShapeWorkload::ExecuteAsync(), BFloat16ToFloat32::Func(), Float16ToFloat32::Func(), Float32ToBFloat16::Func(), Float32ToFloat16::Func(), armnn::GetBiasDataType(), TfLiteParserImpl::GetBuffer(), Layer::GetDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnn::optimizations::pad_fold::GetLowestElement(), TfLiteParserImpl::GetOutputTensorIds(), armnnUtils::GetPerAxisParams(), armnn::GetUnpaddedTensorStrides(), armnn::InitializeArmComputeTensorData(), armnn::InsertConvertBf16ToFp32LayersBefore(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToBf16LayersAfter(), armnn::InsertConvertFp32ToBf16LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), SampleDynamicLayerSupport::IsAdditionSupported(), RefLayerSupport::IsConvertFp16ToFp32Supported(), RefLayerSupport::IsConvertFp32ToFp16Supported(), RefLayerSupport::IsConvolution2dSupported(), RefLayerSupport::IsConvolution3dSupported(), RefLayerSupport::IsDepthwiseConvolutionSupported(), NeonLayerSupport::IsFloorSupported(), RefLayerSupport::IsFullyConnectedSupported(), ClLayerSupport::IsQLstmSupported(), NeonLayerSupport::IsQLstmSupported(), RefLayerSupport::IsTransposeConvolution2dSupported(), NeonLayerSupport::IsUnidirectionalSequenceLstmSupported(), armnn::LstmImpl(), armnn::MakeDecoder(), armnn::MakeEncoder(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::PermuteTensor(), ConvertFp32NetworkToFp16Impl::Run(), ConvertConstPermuteLayersToConstLayers::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), armnn_driver::SwizzleAndroidNn4dTensorToArmNn(), TypeAnyOf::TypeAnyOf(), TypeIs::TypeIs(), ArgMinMaxQueueDescriptor::Validate(), FullyConnectedQueueDescriptor::Validate(), Convolution2dQueueDescriptor::Validate(), Convolution3dQueueDescriptor::Validate(), DepthwiseConvolution2dQueueDescriptor::Validate(), QuantizeQueueDescriptor::Validate(), EqualQueueDescriptor::Validate(), ConvertBf16ToFp32QueueDescriptor::Validate(), ConvertFp32ToBf16QueueDescriptor::Validate(), ConvertFp16ToFp32QueueDescriptor::Validate(), ConvertFp32ToFp16QueueDescriptor::Validate(), GreaterQueueDescriptor::Validate(), GatherNdQueueDescriptor::Validate(), GatherQueueDescriptor::Validate(), TransposeConvolution2dQueueDescriptor::Validate(), ComparisonQueueDescriptor::Validate(), LogicalBinaryQueueDescriptor::Validate(), and armnn::VerifyTensorInfoDataType().

{ return m_DataType; }

GetNumBytes()

unsigned int GetNumBytes

(

)

const

Definition at line 427 of file Tensor.cpp.

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

Referenced by RefTensorHandle::Allocate(), TosaRefTensorHandle::Allocate(), SampleTensorHandle::Allocate(), ScopedTensorHandle::Allocate(), ArmnnPreparedModel::ArmnnPreparedModel(), armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), ConstTensor::ConstTensor(), ConstTensorPin::ConstTensorPin(), armnnOnnxParser::CreateConstTensorImpl(), RefReshapeWorkload::ExecuteAsync(), ArmnnPreparedModel::ExecuteWithDummyInputs(), IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo(), TfLiteParserImpl::GetOutputTensorIds(), SampleTensorHandle::Import(), SampleTensorHandle::Manage(), RefTensorHandle::Manage(), TosaRefTensorHandle::Manage(), RefTensorHandle::Map(), TosaRefTensorHandle::Map(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::PermuteTensor(), armnn::ReorderWeightChannelsForAcl(), and ScopedTensorHandle::ScopedTensorHandle().

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

GetNumDimensions()

unsigned int GetNumDimensions ( ) const

inline

Definition at line 195 of file Tensor.hpp.

Referenced by armnn::ArgMinMax(), armnnTfLiteParser::AsFloatArray(), BatchMatMul::BatchMatMul(), armnn::CalculateGatherNdKeyIndices(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), armnn::ComputeAclAxis(), armnn::ComputePositiveAxis(), armnn::ComputeReductionTensorShape(), armnn::ComputeSoftmaxAclAxis(), armnnTfLiteParser::ComputeWrappedIndex(), armnn::Concatenate(), Converter::ConvertOperation(), armnn_driver::ConvertReduce(), RefShapeWorkload::ExecuteAsync(), RefRankWorkload::ExecuteAsync(), armnn::Gather(), armnn::GetBiasDataType(), armnn::GetNumActivations(), RefLayerSupport::IsBatchToSpaceNdSupported(), armnn_driver::IsDynamicTensor(), RefLayerSupport::IsMeanSupported(), armnn::LogSoftmax(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::PrintOutput(), armnnUtils::ProcessConcatInputTensorInfo(), armnn::Reduce(), PermuteAndBatchToSpaceAsDepthToSpaceImpl< PermuteType >::Run(), AddBroadcastReshapeLayerImpl::Run(), armnn::Softmax(), armnn::Split(), armnn::Splitter(), armnn::Stack(), armnn_driver::SwizzleAndroidNn4dTensorToArmNn(), TensorNumDimensionsAreCorrect::TensorNumDimensionsAreCorrect(), TensorNumDimensionsAreGreaterOrEqualTo::TensorNumDimensionsAreGreaterOrEqualTo(), FullyConnectedQueueDescriptor::Validate(), MeanQueueDescriptor::Validate(), PadQueueDescriptor::Validate(), InstanceNormalizationQueueDescriptor::Validate(), L2NormalizationQueueDescriptor::Validate(), StridedSliceQueueDescriptor::Validate(), GatherNdQueueDescriptor::Validate(), GatherQueueDescriptor::Validate(), SliceQueueDescriptor::Validate(), BatchMatMulQueueDescriptor::Validate(), QueueDescriptor::ValidateTensorNumDimensions(), FillLayer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), and MeanLayer::ValidateTensorShapesFromInputs().

{ return m_Shape.GetNumDimensions(); }

GetNumElements()

unsigned int GetNumElements ( ) const

inline

Examples:

CustomMemoryAllocatorSample.cpp.

Definition at line 196 of file Tensor.hpp.

Referenced by armnn::Activation(), armnnTfLiteParser::AsFloatArray(), armnnTfLiteParser::ComputeWrappedIndex(), armnn::ConvertBf16ToFp32Weight(), armnn::optimizations::ConvertWeight(), armnnOnnxParser::CreateConstTensorImpl(), armnn::Dequantize(), armnn::DetectionPostProcess(), SampleDynamicAdditionWorkload::Execute(), RefGatherNdWorkload::ExecuteAsync(), RefConvertFp32ToBf16Workload::ExecuteAsync(), RefConvertFp32ToFp16Workload::ExecuteAsync(), RefFakeQuantizationFloat32Workload::ExecuteAsync(), RefFloorWorkload::ExecuteAsync(), RefConvertBf16ToFp32Workload::ExecuteAsync(), RefConvertFp16ToFp32Workload::ExecuteAsync(), RefCastWorkload::ExecuteAsync(), RefUnidirectionalSequenceLstmWorkload::ExecuteAsync(), RefDebugWorkload< DataType >::ExecuteAsync(), BFloat16ToFloat32::Func(), Float16ToFloat32::Func(), Float32ToBFloat16::Func(), Float32ToFloat16::Func(), armnn::Gather(), armnn::GetBiasDataType(), TensorInfo::GetNumBytes(), armnn::MirrorPad(), IDeserializer::DeserializerImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::Pad(), armnn::PrintOutput(), armnn::Quantize(), armnn::Reduce(), FuseConvertFp32ToBf16IntoConstLayers::Run(), ConvertConstPermuteLayersToConstLayers::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), ShapesAreSameTotalSize::ShapesAreSameTotalSize(), armnn::Splitter(), armnn::Stack(), armnnDeserializer::ToConstTensor(), and SpaceToBatchNdQueueDescriptor::Validate().

{ return m_Shape.GetNumElements(); }

GetQuantizationDim()

Optional< unsigned int > GetQuantizationDim

(

)

const

Definition at line 494 of file Tensor.cpp.

Referenced by armnnTfLiteParser::AsFloatArray(), Converter::ConvertOperation(), armnn::GetBiasDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnnUtils::GetPerAxisParams(), and armnnUtils::Permuted().

{
    return m_Quantization.m_QuantizationDim;
}

GetQuantizationOffset()

int32_t GetQuantizationOffset

(

)

const

Definition at line 478 of file Tensor.cpp.

Referenced by armnnTfLiteParser::AsFloatArray(), armnn::CheckScaleSetOnQuantizedType(), Converter::ConvertOperation(), armnn::Dequantize(), armnn::GetBiasDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnn::optimizations::pad_fold::GetLowestElement(), armnn::optimizations::pad_fold::GetZeroElement(), TensorInfo::IsTypeSpaceMatch(), armnn::MakeDecoder(), armnn::MakeEncoder(), TfLiteParserImpl::OutputShapeOfReshape(), QuantizationParametersAreEqual::QuantizationParametersAreEqual(), armnn::Quantize(), and ConvertConstDequantisationLayersToConstLayersImpl::Run().

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

    return m_Quantization.m_Offset.value();
}

GetQuantizationScale()

float GetQuantizationScale

(

)

const

Definition at line 461 of file Tensor.cpp.

References ARMNN_ASSERT, and TensorInfo::HasMultipleQuantizationScales().

Referenced by armnnTfLiteParser::AsFloatArray(), armnn::CheckScaleSetOnQuantizedType(), Converter::ConvertOperation(), armnn::Dequantize(), armnn::GetBiasDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnn::optimizations::pad_fold::GetLowestElement(), TensorInfo::IsTypeSpaceMatch(), armnn::MakeDecoder(), armnn::MakeEncoder(), TfLiteParserImpl::OutputShapeOfReshape(), QuantizationParametersAreEqual::QuantizationParametersAreEqual(), armnn::Quantize(), and ConvertConstDequantisationLayersToConstLayersImpl::Run().

{
    if (m_Quantization.m_Scales.empty())
    {
        // NOTE: old default for backward compatibility
        return 1.0f;
    }

    ARMNN_ASSERT(!HasMultipleQuantizationScales());
    return m_Quantization.m_Scales[0];
}

GetQuantizationScales()

std::vector< float > GetQuantizationScales

(

)

const

Definition at line 451 of file Tensor.cpp.

Referenced by armnnTfLiteParser::AsFloatArray(), Converter::ConvertOperation(), armnn::GetBiasDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), and armnnUtils::GetPerAxisParams().

{
    return m_Quantization.m_Scales;
}

GetShape() [1/2]

const TensorShape& GetShape ( ) const

inline

Definition at line 191 of file Tensor.hpp.

Referenced by armnn::ArgMinMax(), ArmnnPreparedModel::ArmnnPreparedModel(), armnnTfLiteParser::AsFloatArray(), BatchMatMul::BatchMatMul(), armnn::BatchNormImpl(), armnn::BatchToSpaceNd(), armnn::CalculateGatherNdKeyIndices(), armnnUtils::CalculateReducedOutputTensoInfo(), armnnUtils::CalculateStridedSliceOutputTensorInfo(), armnn::ClUnidirectionalSequenceLstmFloatWorkloadValidate(), armnn_driver::ComputeShape(), armnnTfLiteParser::ComputeWrappedIndex(), armnn::Concatenate(), armnn::Convert1HWOTensorInfoToAcl(), armnn::Convert1HWOTensorToAcl(), armnn::Convert1HWOtoMIHW(), armnn::ConvertBf16ToFp32Weight(), Converter::ConvertOperation(), armnn_driver::ConvertPooling2d(), armnn::ConvertWeightTensorFromArmnnToAcl(), armnn::CreateAclNormalizationLayerInfoForL2Normalization(), armnnOnnxParser::CreateConstTensorImpl(), OnnxParserImpl::CreateNetworkFromString(), ConcatLayer::CreateWorkload(), SplitterLayer::CreateWorkload(), armnn::DepthToSpace(), armnn::DetectionPostProcess(), RefChannelShuffleWorkload::ExecuteAsync(), RefDepthwiseConvolution2dWorkload::ExecuteAsync(), RefLstmWorkload::ExecuteAsync(), RefQLstmWorkload::ExecuteAsync(), RefConvolution3dWorkload::ExecuteAsync(), RefElementwiseUnaryWorkload::ExecuteAsync(), RefLogicalUnaryWorkload::ExecuteAsync(), RefLogicalBinaryWorkload::ExecuteAsync(), RefShapeWorkload::ExecuteAsync(), RefComparisonWorkload::ExecuteAsync(), RefElementwiseWorkload< Functor, ParentDescriptor, DebugString >::ExecuteAsync(), RefUnidirectionalSequenceLstmWorkload::ExecuteAsync(), BFloat16ToFloat32::Func(), Float16ToFloat32::Func(), Float32ToBFloat16::Func(), Float32ToFloat16::Func(), armnn::Gather(), armnn::GetBiasDataType(), TfLiteParserImpl::GetBuffer(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnn::GetNumActivations(), armnnUtils::GetPerAxisParams(), IDeserializer::DeserializerImpl::GetQLstmDescriptor(), RefTensorHandle::GetShape(), TosaRefTensorHandle::GetShape(), SampleTensorHandle::GetShape(), ConstTensorHandle::GetShape(), armnn::GetUnpaddedTensorStrides(), armnn::InstanceNorm(), armnn_driver::IsDynamicTensor(), ClLayerSupport::IsSplitterSupported(), NeonLayerSupport::IsSplitterSupported(), armnn::LogSoftmax(), armnn::LstmImpl(), armnn::MirrorPad(), armnn::NeonUnidirectionalSequenceLstmFloatWorkloadValidate(), armnn::NeonUnidirectionalSequenceLstmWorkloadValidate(), IDeserializer::DeserializerImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnn::Pad(), armnnUtils::Permuted(), armnn::PermuteTensor(), armnn::Pooling2d(), armnn::Pooling3d(), armnn::PreluImpl(), armnn::PrintOutput(), armnnUtils::ProcessConcatInputTensorInfo(), armnn::Reduce(), armnn::ReshapeWeightsForAcl(), armnn::Resize(), TransposeAsReshapeImpl::Run(), PermuteAsReshapeImpl::Run(), OptimizeConsecutiveReshapesImpl::Run(), ConvertConstPermuteLayersToConstLayers::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), AddBroadcastReshapeLayerImpl::Run(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), Convolution3dLayer::SerializeLayerParameters(), DepthwiseConvolution2dLayer::SerializeLayerParameters(), Convolution2dLayer::SerializeLayerParameters(), Graph::SerializeToDot(), ShapesAreBroadcastCompatible::ShapesAreBroadcastCompatible(), ShapesAreSameRank::ShapesAreSameRank(), armnn::Slice(), armnn::Softmax(), armnn::SpaceToBatchNd(), armnn::SpaceToDepth(), armnn::Split(), armnn::Splitter(), armnn::Stack(), armnn::StridedSlice(), armnn_driver::SwizzleAndroidNn4dTensorToArmNn(), armnnUtils::TransposeTensorShape(), ArgMinMaxQueueDescriptor::Validate(), PermuteQueueDescriptor::Validate(), DepthwiseConvolution2dQueueDescriptor::Validate(), DetectionPostProcessQueueDescriptor::Validate(), ResizeQueueDescriptor::Validate(), SpaceToBatchNdQueueDescriptor::Validate(), SpaceToDepthQueueDescriptor::Validate(), TransposeQueueDescriptor::Validate(), SliceQueueDescriptor::Validate(), DepthToSpaceQueueDescriptor::Validate(), BatchMatMulQueueDescriptor::Validate(), QueueDescriptor::ValidateTensorNumDimensions(), ElementwiseBaseLayer::ValidateTensorShapesFromInputs(), RankLayer::ValidateTensorShapesFromInputs(), QuantizeLayer::ValidateTensorShapesFromInputs(), ChannelShuffleLayer::ValidateTensorShapesFromInputs(), ActivationLayer::ValidateTensorShapesFromInputs(), FillLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToFp16Layer::ValidateTensorShapesFromInputs(), ReduceLayer::ValidateTensorShapesFromInputs(), DequantizeLayer::ValidateTensorShapesFromInputs(), RsqrtLayer::ValidateTensorShapesFromInputs(), FakeQuantizationLayer::ValidateTensorShapesFromInputs(), DebugLayer::ValidateTensorShapesFromInputs(), BatchToSpaceNdLayer::ValidateTensorShapesFromInputs(), Pooling2dLayer::ValidateTensorShapesFromInputs(), InstanceNormalizationLayer::ValidateTensorShapesFromInputs(), StackLayer::ValidateTensorShapesFromInputs(), SwitchLayer::ValidateTensorShapesFromInputs(), ConvertFp32ToBf16Layer::ValidateTensorShapesFromInputs(), MemImportLayer::ValidateTensorShapesFromInputs(), SliceLayer::ValidateTensorShapesFromInputs(), L2NormalizationLayer::ValidateTensorShapesFromInputs(), ConvertFp16ToFp32Layer::ValidateTensorShapesFromInputs(), AbsLayer::ValidateTensorShapesFromInputs(), ResizeLayer::ValidateTensorShapesFromInputs(), ShapeLayer::ValidateTensorShapesFromInputs(), MemCopyLayer::ValidateTensorShapesFromInputs(), Pooling3dLayer::ValidateTensorShapesFromInputs(), MergeLayer::ValidateTensorShapesFromInputs(), ConvertBf16ToFp32Layer::ValidateTensorShapesFromInputs(), CastLayer::ValidateTensorShapesFromInputs(), FloorLayer::ValidateTensorShapesFromInputs(), SoftmaxLayer::ValidateTensorShapesFromInputs(), NormalizationLayer::ValidateTensorShapesFromInputs(), LogSoftmaxLayer::ValidateTensorShapesFromInputs(), PadLayer::ValidateTensorShapesFromInputs(), MeanLayer::ValidateTensorShapesFromInputs(), TransposeLayer::ValidateTensorShapesFromInputs(), ConstantLayer::ValidateTensorShapesFromInputs(), PermuteLayer::ValidateTensorShapesFromInputs(), ReshapeLayer::ValidateTensorShapesFromInputs(), Convolution3dLayer::ValidateTensorShapesFromInputs(), GatherNdLayer::ValidateTensorShapesFromInputs(), BatchMatMulLayer::ValidateTensorShapesFromInputs(), StridedSliceLayer::ValidateTensorShapesFromInputs(), GatherLayer::ValidateTensorShapesFromInputs(), DetectionPostProcessLayer::ValidateTensorShapesFromInputs(), ElementwiseUnaryLayer::ValidateTensorShapesFromInputs(), ArgMinMaxLayer::ValidateTensorShapesFromInputs(), DepthToSpaceLayer::ValidateTensorShapesFromInputs(), SpaceToBatchNdLayer::ValidateTensorShapesFromInputs(), SpaceToDepthLayer::ValidateTensorShapesFromInputs(), TransposeConvolution2dLayer::ValidateTensorShapesFromInputs(), PreluLayer::ValidateTensorShapesFromInputs(), LogicalBinaryLayer::ValidateTensorShapesFromInputs(), ComparisonLayer::ValidateTensorShapesFromInputs(), FullyConnectedLayer::ValidateTensorShapesFromInputs(), SplitterLayer::ValidateTensorShapesFromInputs(), DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs(), ConcatLayer::ValidateTensorShapesFromInputs(), LstmLayer::ValidateTensorShapesFromInputs(), UnidirectionalSequenceLstmLayer::ValidateTensorShapesFromInputs(), Convolution2dLayer::ValidateTensorShapesFromInputs(), BatchNormalizationLayer::ValidateTensorShapesFromInputs(), QuantizedLstmLayer::ValidateTensorShapesFromInputs(), QLstmLayer::ValidateTensorShapesFromInputs(), and armnn::VerifyTensorInfoDataType().

{ return m_Shape; }

GetShape() [2/2]

TensorShape& GetShape ( )

inline

Definition at line 192 of file Tensor.hpp.

{ return m_Shape; }

HasMultipleQuantizationScales()

bool HasMultipleQuantizationScales ( ) const

inline

Definition at line 201 of file Tensor.hpp.

References TensorShape::operator=(), and TensorShape::operator==().

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

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

HasPerAxisQuantization()

bool HasPerAxisQuantization

(

)

const

Definition at line 446 of file Tensor.cpp.

References TensorInfo::HasMultipleQuantizationScales().

Referenced by armnnTfLiteParser::AsFloatArray(), armnn::Convert1HWOtoMIHW(), Converter::ConvertOperation(), armnn::GetBiasDataType(), armnnSerializer::GetFlatBufferArgMinMaxFunction(), armnnUtils::GetPerAxisParams(), armnn::MakeDecoder(), armnn::MakeEncoder(), and TypeNotPerAxisQuantized::TypeNotPerAxisQuantized().

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

IsConstant()

bool IsConstant

(

)

const

Definition at line 509 of file Tensor.cpp.

Referenced by LayerWithParameters< Pooling3dDescriptor >::GetConnectedConstantAsInputTensors(), LayerSupportHandle::IsConvolution2dSupported(), LayerSupportHandle::IsDepthwiseConvolutionSupported(), LayerSupportHandle::IsDilatedDepthwiseConvolutionSupported(), LayerSupportHandle::IsFullyConnectedSupported(), FuseConvertFp32ToBf16IntoConstLayers::Run(), ConvertConstPermuteLayersToConstLayers::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), and TensorInfo::SetConstant().

{
    return m_IsConstant;
}

IsQuantized()

bool IsQuantized

(

)

const

Definition at line 504 of file Tensor.cpp.

References armnn::IsQuantizedType().

Referenced by RefCastWorkload::ExecuteAsync(), armnn::GetBiasDataType(), armnn::optimizations::pad_fold::GetZeroElement(), TensorInfo::IsTypeSpaceMatch(), armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d(), and TypeNotPerAxisQuantized::TypeNotPerAxisQuantized().

{
    return IsQuantizedType(m_DataType);
}

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.

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

Referenced by ConcatLayer::CreateWorkload(), SplitterLayer::CreateWorkload(), armnn::GetBiasDataType(), ClLayerSupport::IsConcatSupported(), NeonLayerSupport::IsConcatSupported(), ClLayerSupport::IsSplitterSupported(), and NeonLayerSupport::IsSplitterSupported().

{
    bool match = true;

    match &= m_DataType == other.m_DataType;

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

operator!=()

bool operator!=

(

const TensorInfo &

other

)

const

Definition at line 422 of file Tensor.cpp.

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

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;
}

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));
}

SetConstant()

void SetConstant

(

const bool

IsConstant = true

)

Marks the data corresponding to this tensor info as constant.

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

Examples:

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

Definition at line 514 of file Tensor.cpp.

References TensorInfo::IsConstant().

Referenced by ArmnnPreparedModel::ArmnnPreparedModel(), armnn_driver::ConvertOperandToConstTensorPin(), armnnOnnxParser::CreateConstTensorImpl(), OnnxParserImpl::CreateNetworkFromString(), ArmnnPreparedModel::ExecuteWithDummyInputs(), TfLiteParserImpl::GetBuffer(), TfLiteParserImpl::GetNetworkInputBindingInfo(), IDeserializer::DeserializerImpl::GetNetworkOutputBindingInfo(), TfLiteParserImpl::GetOutputTensorIds(), armnnUtils::MakeInputTensors(), armnn::PermuteTensor(), armnn::RevertConstantWeightsToFP32(), ConvertConstPermuteLayersToConstLayers::Run(), FuseConvertFp32ToBf16IntoConstLayers::Run(), ConvertConstDequantisationLayersToConstLayersImpl::Run(), and armnnDeserializer::ToConstTensor().

{
    m_IsConstant = IsConstant;
}

SetDataType()

void SetDataType ( DataType  type )

inline

Definition at line 199 of file Tensor.hpp.

Referenced by armnn_driver::ConvertOperandToConstTensorPin(), ConvertToDataType(), TfLiteParserImpl::GetOutputTensorIds(), armnn::InsertConvertBf16ToFp32LayersBefore(), armnn::InsertConvertFp16ToFp32LayersBefore(), armnn::InsertConvertFp32ToBf16LayersAfter(), armnn::InsertConvertFp32ToBf16LayersBefore(), armnn::InsertConvertFp32ToFp16LayersAfter(), and ConvertFp32NetworkToFp16Impl::Run().

{ m_DataType = type; }

SetQuantizationDim()

void SetQuantizationDim

(

const Optional< unsigned int > &

quantizationDim

)

Definition at line 499 of file Tensor.cpp.

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

{
    m_Quantization.m_QuantizationDim = quantizationDim;
}

SetQuantizationOffset()

void SetQuantizationOffset

(

int32_t

offset

)

Definition at line 489 of file Tensor.cpp.

Referenced by armnn::CheckScaleSetOnQuantizedType(), Converter::ConvertOperation(), RefCastWorkload::ExecuteAsync(), and TensorInfo::TensorInfo().

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

SetQuantizationScale()

void SetQuantizationScale

(

float

scale

)

Definition at line 473 of file Tensor.cpp.

Referenced by armnn::CheckScaleSetOnQuantizedType(), Converter::ConvertOperation(), RefCastWorkload::ExecuteAsync(), and TensorInfo::TensorInfo().

{
    m_Quantization.m_Scales = { scale };
}

SetQuantizationScales()

void SetQuantizationScales

(

const std::vector< float > &

scales

)

Definition at line 456 of file Tensor.cpp.

Referenced by Converter::ConvertOperation(), and TensorInfo::TensorInfo().

{
    m_Quantization.m_Scales = scales;
}

SetShape()

void SetShape ( const TensorShape &  newShape )

inline

Definition at line 193 of file Tensor.hpp.

Referenced by ClGatherNdWorkload::ClGatherNdWorkload(), armnn::ClGatherNdWorkloadValidate(), armnn::Convert1HWOtoMIHW(), armnn_driver::ConvertOperandToConstTensorPin(), Converter::ConvertOperation(), OnnxParserImpl::CreateNetworkFromString(), RefGatherNdWorkload::ExecuteAsync(), RefUnidirectionalSequenceLstmWorkload::ExecuteAsync(), NeonGatherNdWorkload::NeonGatherNdWorkload(), armnn::NeonGatherNdWorkloadValidate(), IDeserializer::DeserializerImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfReshape(), TfLiteParserImpl::OutputShapeOfSqueeze(), armnnUtils::Permuted(), armnn::ReshapeWeightsForAcl(), AddBroadcastReshapeLayerImpl::Run(), and armnnUtils::TransposeTensorShape().

{ m_Shape = newShape; }

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

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