nnfw::cker::Shape Class Reference

#include <Shape.h>

Public Member Functions
Shape &	operator= (Shape const &)=delete
	Shape ()
	Shape (int dimensions_count)
	Shape (int shape_size, int32_t value)
	Shape (int dimensions_count, const int32_t *dims_data)
	Shape (const std::initializer_list< int > init_list)
	Shape (const Shape &other)
	Shape (Shape &&other)=default
bool	operator== (const Shape &comp) const
	~Shape ()=default
int32_t	DimensionsCount () const
int32_t	Dims (int i) const
void	SetDim (int i, int32_t val)
int32_t *	DimsData ()
const int32_t *	DimsData () const
const int32_t *	DimsDataUpTo6D () const
void	Resize (int dimensions_count)
void	ReplaceWith (int dimensions_count, const int32_t *dims_data)
void	ReplaceWith (const Shape &other)
void	ReplaceWith (Shape &&other)
template<typename Iterable >
void	BuildFrom (const Iterable &src_iterable)
void	BuildFrom (const std::initializer_list< int > init_list)
int	FlatSize () const
bool	operator!= (const Shape &comp) const

Static Public Member Functions
static Shape	ExtendedShape (int new_shape_size, const Shape &shape)

Static Public Attributes
static constexpr int	kMaxSmallSize = 6

Detailed Description

Definition at line 34 of file Shape.h.

Constructor & Destructor Documentation

Shape() [1/7]

nnfw::cker::Shape::Shape ( )

inline

Definition at line 45 of file Shape.h.

: _size(0), dims_(std::array<int32_t, kMaxSmallSize>{}) {}

Referenced by ExtendedShape().

Shape() [2/7]

nnfw::cker::Shape::Shape ( int  dimensions_count )

inlineexplicit

Definition at line 50 of file Shape.h.

: _size(dimensions_count) { initStorage(dimensions_count); }

Shape() [3/7]

nnfw::cker::Shape::Shape ( int  shape_size, int32_t  value  )

inline

Definition at line 53 of file Shape.h.

                                       : _size(shape_size)
  {
    initStorage(shape_size);
    for (int i = 0; i < shape_size; ++i)
    {
      SetDim(i, value);
    }
  }

References SetDim().

Shape() [4/7]

nnfw::cker::Shape::Shape ( int  dimensions_count, const int32_t *  dims_data  )

inline

Definition at line 63 of file Shape.h.

                                                        : _size(dimensions_count)
  {
    initStorage(dimensions_count);
    ReplaceWith(dimensions_count, dims_data);
  }

References ReplaceWith().

Shape() [5/7]

nnfw::cker::Shape::Shape ( const std::initializer_list< int >  init_list )

inline

Definition at line 71 of file Shape.h.

                                                  : _size(0)
  {
    const auto size = static_cast<int>(std::distance(init_list.begin(), init_list.end()));
    initStorage(size);
    BuildFrom(init_list);
  }

References BuildFrom(), and size.

Shape() [6/7]

nnfw::cker::Shape::Shape ( const Shape &  other )

inline

Definition at line 79 of file Shape.h.

                            : _size(other._size)
  {
    if (_size <= kMaxSmallSize)
    {
      // When the number of dimensions is small, copy the fixed array.
      dims_ = std::get<std::array<int32_t, kMaxSmallSize>>(other.dims_);
    }
    else
    {
      // Otherwise, copy the dynamically allocated vector.
      dims_ = std::get<std::vector<int32_t>>(other.dims_);
    }
  }

References kMaxSmallSize.

Shape() [7/7]

nnfw::cker::Shape::Shape ( Shape &&  other )

default

~Shape()

nnfw::cker::Shape::~Shape ( )

default

Member Function Documentation

BuildFrom() [1/2]

template<typename Iterable >

void nnfw::cker::Shape::BuildFrom ( const Iterable &  src_iterable )

inline

Definition at line 230 of file Shape.h.

  {
    const int dimensions_count =
      static_cast<int>(std::distance(src_iterable.begin(), src_iterable.end()));
    Resize(dimensions_count);
    int32_t *data = DimsData();
    for (auto it = src_iterable.begin(); it != src_iterable.end(); ++it)
    {
      *data++ = static_cast<int32_t>(*it);
    }
  }

References DimsData(), and Resize().

Referenced by Shape().

BuildFrom() [2/2]

void nnfw::cker::Shape::BuildFrom ( const std::initializer_list< int >  init_list )

inline

Definition at line 250 of file Shape.h.

  {
    BuildFrom<const std::initializer_list<int>>(init_list);
  }

DimensionsCount()

int32_t nnfw::cker::Shape::DimensionsCount ( ) const

inline

Definition at line 103 of file Shape.h.

{ return _size; }

Referenced by nnfw::cker::train::Adam(), nnfw::cker::ArgMinMax(), nnfw::cker::AveragePool16(), nnfw::cker::train::AveragePool2DGrad(), nnfw::cker::AveragePool32(), nnfw::cker::AveragePool< float >(), nnfw::cker::AveragePool< int8_t >(), nnfw::cker::BatchToSpaceND(), nnfw::cker::bias_op::biasHelper(), nnfw::cker::functor::biasReductionHelper(), nnfw::cker::BroadcastComparison4DSlowImpl(), nnfw::cker::BroadcastComparison4DSlowWithScaling(), nnfw::cker::BroadcastSelect4DSlow(), nnfw::cker::BroadcastTo(), nnfw::cker::train::CategoricalCrossEntropyWithLogits(), nnfw::cker::checkMatching(), nnfw::cker::reference::Conv(), nnfw::cker::multithreaded::Conv(), nnfw::cker::reference::Conv(), nnfw::cker::reference::Conv(), nnfw::cker::optimized::Conv(), nnfw::cker::Tensor::copyFrom(), nnfw::cker::train::Depad(), nnfw::cker::DepthToSpace(), nnfw::cker::DepthwiseConv(), nnfw::cker::reference_integer_ops::DepthwiseConvHybridPerChannel(), nnfw::cker::optimized::DepthwiseConvImpl(), nnfw::cker::optimized_integer_ops::DepthwiseConvPerChannel(), nnfw::cker::reference_integer_ops::DepthwiseConvPerChannel(), nnfw::cker::optimized_integer_ops::DepthwiseConvWithRounding(), nnfw::cker::optimized::DepthwiseConvWithRounding(), nnfw::cker::optimized::DilatedIm2col(), nnfw::cker::optimized::ExtractPatchIntoBufferColumn(), nnfw::cker::FlatSizeSkipDim(), nnfw::cker::FloorDivBroadcast(), nnfw::cker::FloorModBroadcast(), nnfw::cker::BCast::FromShape(), nnfw::cker::FullyConnected(), nnfw::cker::train::FullyConnectedBiasGrad(), nnfw::cker::FullyConnectedSparseWeight16x1(), nnfw::cker::FullyConnectedSparseWeightRandom(), nnfw::cker::Gather(), nnfw::cker::train::GradientDescent(), nnfw::cker::reference::HybridConvPerChannel(), nnfw::cker::optimized::Im2col(), nnfw::cker::InitTensorDataForReduce(), nnfw::cker::L2NormalizeFloat32(), nnfw::cker::L2NormalizeQuant8(), nnfw::cker::LogicalAndBroadcast(), nnfw::cker::LogicalOrBroadcast(), nnfw::cker::LogSoftmax(), nnfw::cker::LogSoftmax(), nnfw::cker::MapAsMatrixWithLastDimAsRows(), nnfw::cker::MatchingFlatSizeSkipDim(), nnfw::cker::MatchingFlatSizeSkipDim(), nnfw::cker::MaximumMinimumBroadcast4DSlow(), nnfw::cker::train::MaxPool2D(), nnfw::cker::train::MaxPool2DGrad(), nnfw::cker::MaxPool< float >(), nnfw::cker::MaxPool< uint8_t >(), nnfw::cker::Mean(), nnfw::cker::MeanAxis1And2(), nnfw::cker::MeanQ8Asymm(), nnfw::cker::Offset(), nnfw::cker::Offset(), nnfw::cker::Offset(), nnfw::cker::OneHot(), nnfw::cker::DynamicUpdateSlice::operator()(), nnfw::cker::Pad(), nnfw::cker::FCTempArena::prepare(), nnfw::cker::BatchMatMul::prepare(), nnfw::cker::ReduceMean::PrepareforReduce(), nnfw::cker::ProcessBroadcastShapes(), nnfw::cker::Reduce::QuantizedMeanOrSum(), nnfw::cker::Reduce::ReduceGeneric(), nnfw::cker::ReduceImpl(), nnfw::cker::ReduceMeanImpl(), nnfw::cker::ReduceSumQuantImpl(), ReplaceWith(), nnfw::cker::ResizeBilinear(), nnfw::cker::Reverse(), nnfw::cker::RmsNorm(), nnfw::cker::reference::Softmax(), nnfw::cker::Softmax(), nnfw::cker::train::SoftMaxGrad(), nnfw::cker::SpaceToBatchND(), nnfw::cker::SpaceToDepth(), nnfw::cker::Split(), nnfw::cker::SplitV(), nnfw::cker::SqDiff(), nnfw::cker::StatelessRandomUniform(), nnfw::cker::StridedSlice(), nnfw::cker::TileOneDimension(), nnfw::cker::TopKV2(), nnfw::cker::Transpose(), nnfw::cker::Transpose2D(), nnfw::cker::TransposeConv(), nnfw::cker::TransposeImpl(), nnfw::cker::reference::TransposeImpl(), and nnfw::cker::Unpack().

Dims()

int32_t nnfw::cker::Shape::Dims ( int  i ) const

inline

Definition at line 106 of file Shape.h.

  {
    assert(i >= 0 && i < _size);
    if (_size <= kMaxSmallSize)
    {
      return std::get<std::array<int32_t, kMaxSmallSize>>(dims_)[i];
    }
    else
    {
      return std::get<std::vector<int32_t>>(dims_)[i];
    }
  }

References kMaxSmallSize.

Referenced by nnfw::cker::ArgMinMax(), nnfw::cker::AveragePool16(), nnfw::cker::train::AveragePool2DGrad(), nnfw::cker::AveragePool32(), nnfw::cker::AveragePool< float >(), nnfw::cker::AveragePool< int8_t >(), nnfw::cker::train::backpropFilter(), nnfw::cker::train::backpropInput(), nnfw::cker::BatchMatMulParams::BatchMatMulParams(), nnfw::cker::BatchToSpaceND(), nnfw::cker::bias_op::biasHelper(), nnfw::cker::functor::biasReductionHelper(), nnfw::cker::reference::BroadcastBinaryArithmeticOpSlow(), nnfw::cker::reference::BroadcastBinaryArithmeticOpSlow(), nnfw::cker::reference::BroadcastBinaryArithmeticOpSlow(), nnfw::cker::reference::BroadcastBinaryArithmeticOpSlow(), nnfw::cker::reference::BroadcastBinaryArithmeticOpSlow(), nnfw::cker::BroadcastSelect4DSlow(), nnfw::cker::train::CategoricalCrossEntropy(), nnfw::cker::train::CategoricalCrossEntropyGrad(), nnfw::cker::train::CategoricalCrossEntropyWithLogits(), nnfw::cker::checkMatching(), nnfw::cker::Concatenation(), nnfw::cker::ConcatenationWithScaling(), nnfw::cker::reference::Conv(), nnfw::cker::multithreaded::Conv(), nnfw::cker::reference::Conv(), nnfw::cker::reference::Conv(), nnfw::cker::optimized::Conv(), nnfw::cker::train::ConvFilterGrad(), nnfw::cker::train::ConvInputGrad(), nnfw::cker::CopyDimsToDesc(), nnfw::cker::train::Depad(), nnfw::cker::DepthToSpace(), nnfw::cker::optimized_integer_ops::depthwise_conv::DepthwiseConvGeneral(), nnfw::cker::optimized::depthwise_conv::DepthwiseConvGeneral(), nnfw::cker::reference_integer_ops::DepthwiseConvHybridPerChannel(), nnfw::cker::optimized::DepthwiseConvImpl(), nnfw::cker::DepthwiseConvOp(), nnfw::cker::reference_integer_ops::DepthwiseConvPerChannel(), nnfw::cker::optimized_integer_ops::DepthwiseConvWithRounding(), nnfw::cker::optimized::DepthwiseConvWithRounding(), nnfw::cker::optimized::DilatedIm2col(), nnfw::cker::BCast::FromShape(), nnfw::cker::FullyConnected(), nnfw::cker::FullyConnected(), nnfw::cker::train::FullyConnectedBiasGrad(), nnfw::cker::FullyConnectedHybrid(), nnfw::cker::FullyConnectedSparseWeight16x1(), nnfw::cker::FullyConnectedSparseWeightRandom(), nnfw::cker::Gather(), nnfw::cker::HowManyConvThreads(), nnfw::cker::optimized_integer_ops::HowManyConvThreads(), nnfw::cker::reference::HybridConvPerChannel(), nnfw::cker::optimized::Im2col(), nnfw::cker::LogSoftmax(), nnfw::cker::LogSoftmax(), nnfw::cker::MapAsMatrixWithLastDimAsRows(), nnfw::cker::MatchingDim(), nnfw::cker::MatchingDim(), nnfw::cker::MatchingFlatSizeSkipDim(), nnfw::cker::MatchingFlatSizeSkipDim(), nnfw::cker::train::MaxPool2D(), nnfw::cker::MaxPool< float >(), nnfw::cker::MaxPool< uint8_t >(), nnfw::cker::MeanAxis1And2(), nnfw::cker::train::MSE(), nnfw::cker::train::MSEGrad(), nnfw::cker::OneHot(), nnfw::cker::DynamicUpdateSlice::operator()(), nnfw::cker::ShapeIterator::operator*(), nnfw::cker::Pad(), onert::backend::cpu::ops::ConvolutionLayer::prepare(), onert::backend::cpu::ops::FullyConnectedLayer::prepare(), nnfw::cker::FCTempArena::prepare(), nnfw::cker::BatchMatMul::prepare(), nnfw::cker::ProcessBroadcastShapes(), nnfw::cker::Reduce::QuantizedMeanOrSum(), nnfw::cker::ResizeBilinear(), nnfw::cker::ResizeBilinear(), nnfw::cker::ResizeBilinear(), nnfw::cker::ResizeBilinearKernel2x2(), nnfw::cker::Reverse(), nnfw::cker::RmsNorm(), nnfw::cker::RoPE(), nnfw::cker::Tensor::shaped(), nnfw::cker::Slice(), nnfw::cker::train::SoftMaxGrad(), nnfw::cker::SpaceToBatchND(), nnfw::cker::SpaceToDepth(), nnfw::cker::Split(), nnfw::cker::SplitV(), nnfw::cker::StartForAxis(), nnfw::cker::StopForAxis(), nnfw::cker::StridedSlice(), nnfw::cker::TileOneDimension(), nnfw::cker::TopKV2(), nnfw::cker::Transpose3D(), nnfw::cker::TransposeConv(), nnfw::cker::Unpack(), and nnfw::cker::DynamicUpdateSlice::~DynamicUpdateSlice().

DimsData() [1/2]

int32_t * nnfw::cker::Shape::DimsData ( )

inline

Definition at line 134 of file Shape.h.

  {
    if (_size <= kMaxSmallSize)
    {
      return std::get<std::array<int32_t, kMaxSmallSize>>(dims_).data();
    }
    else
    {
      return std::get<std::vector<int32_t>>(dims_).data();
    }
  }

References kMaxSmallSize.

Referenced by nnfw::cker::train::Adam(), nnfw::cker::BroadcastTo(), BuildFrom(), nnfw::cker::train::CategoricalCrossEntropyWithLogits(), nnfw::cker::Tensor::copyFrom(), FlatSize(), nnfw::cker::FlatSizeSkipDim(), onert::backend::cpu::ops::getShape(), onert::backend::train::ops::getShape(), nnfw::cker::train::GradientDescent(), nnfw::cker::InitTensorDataForReduce(), operator==(), nnfw::cker::ReduceMean::PrepareforReduce(), nnfw::cker::ReduceImpl(), nnfw::cker::ReduceMeanImpl(), nnfw::cker::ReduceSumQuantImpl(), ReplaceWith(), ReplaceWith(), nnfw::cker::StatelessRandomUniform(), and nnfw::cker::Transpose2D().

DimsData() [2/2]

const int32_t * nnfw::cker::Shape::DimsData ( ) const

inline

Definition at line 147 of file Shape.h.

  {
    if (_size <= kMaxSmallSize)
    {
      return std::get<std::array<int32_t, kMaxSmallSize>>(dims_).data();
    }
    else
    {
      return std::get<std::vector<int32_t>>(dims_).data();
    }
  }

References kMaxSmallSize.

DimsDataUpTo6D()

const int32_t * nnfw::cker::Shape::DimsDataUpTo6D ( ) const

inline

Definition at line 160 of file Shape.h.

  {
    return std::get<std::array<int32_t, kMaxSmallSize>>(dims_).data();
  }

Referenced by nnfw::cker::Offset(), nnfw::cker::Offset(), and nnfw::cker::Offset().

ExtendedShape()

static Shape nnfw::cker::Shape::ExtendedShape ( int  new_shape_size, const Shape &  shape  )

inlinestatic

Definition at line 244 of file Shape.h.

  {
    return Shape(new_shape_size, shape, 1);
  }

References Shape().

FlatSize()

int nnfw::cker::Shape::FlatSize ( ) const

inline

Definition at line 256 of file Shape.h.

  {
    int buffer_size = 1;
    const int *dims_data = DimsData();
    for (int i = 0; i < _size; i++)
    {
      buffer_size *= dims_data[i];
    }
    return buffer_size;
  }

References DimsData().

Referenced by nnfw::cker::optimized::AddBiasAndEvalActivationFunction(), nnfw::cker::AddN(), nnfw::cker::train::AveragePool2DGrad(), nnfw::cker::BroadcastTo(), nnfw::cker::checkMatching(), nnfw::cker::Tensor::copyFrom(), nnfw::cker::reference_integer_ops::DepthwiseConvHybridPerChannel(), nnfw::cker::optimized_integer_ops::DepthwiseConvWithRounding(), nnfw::cker::optimized::DepthwiseConvWithRounding(), nnfw::cker::Tensor::flat(), nnfw::cker::Tensor::flat(), nnfw::cker::FloorDivElementwise(), nnfw::cker::FloorModElementwise(), nnfw::cker::FullyConnected(), nnfw::cker::train::FullyConnectedBiasGrad(), onert::backend::cpu::ops::FullyConnectedLayer::fullyConnectedHybrid(), nnfw::cker::FullyConnectedHybrid(), nnfw::cker::Gather(), nnfw::cker::LogicalAndElementwise(), nnfw::cker::LogicalOrElementwise(), nnfw::cker::MapAsVector(), nnfw::cker::MatchingElementsSize(), nnfw::cker::MatchingFlatSize(), nnfw::cker::train::MaxPool2DGrad(), nnfw::cker::OneHot(), nnfw::cker::Conv::operator()(), nnfw::cker::DynamicUpdateSlice::operator()(), onert::backend::cpu::ops::FullyConnectedLayer::prepare(), nnfw::cker::FCTempArena::prepare(), nnfw::cker::BatchMatMul::prepare(), nnfw::cker::RankOneSelect(), nnfw::cker::functor::BroadcastTo< Device, T >::ReshapeAndBCast(), and nnfw::cker::Transpose().

operator!=()

bool nnfw::cker::Shape::operator!= ( const Shape &  comp ) const

inline

Definition at line 267 of file Shape.h.

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

operator=()

Shape & nnfw::cker::Shape::operator= ( Shape const &  )

delete

operator==()

bool nnfw::cker::Shape::operator== ( const Shape &  comp ) const

inline

Definition at line 94 of file Shape.h.

  {
    return this->_size == comp._size &&
           std::memcmp(DimsData(), comp.DimsData(), _size * sizeof(int32_t)) == 0;
  }

References DimsData().

ReplaceWith() [1/3]

void nnfw::cker::Shape::ReplaceWith ( const Shape &  other )

inline

Definition at line 217 of file Shape.h.

  {
    ReplaceWith(other.DimensionsCount(), other.DimsData());
  }

References DimensionsCount(), DimsData(), and ReplaceWith().

ReplaceWith() [2/3]

void nnfw::cker::Shape::ReplaceWith ( int  dimensions_count, const int32_t *  dims_data  )

inline

Definition at line 206 of file Shape.h.

  {
    // Allow dims_data to be nullptr when dimensions_count is 0,
    // because there are no dimensions to copy. For any non-zero dimensions_count,
    // dims_data must not be nullptr to ensure valid shape data is provided.
    assert(dimensions_count == 0 || dims_data != nullptr);
    Resize(dimensions_count);
    std::memcpy(DimsData(), dims_data, dimensions_count * sizeof(int32_t));
  }

References DimsData(), and Resize().

Referenced by nnfw::cker::train::Adam(), onert::backend::train::ops::MeanLayer::backward(), nnfw::cker::BroadcastTo(), nnfw::cker::train::CategoricalCrossEntropyWithLogits(), nnfw::cker::FusedBatchNorm::copyFrom(), nnfw::cker::Tensor::copyFrom(), nnfw::cker::train::GradientDescent(), ReplaceWith(), Shape(), and nnfw::cker::StatelessRandomUniform().

ReplaceWith() [3/3]

void nnfw::cker::Shape::ReplaceWith ( Shape &&  other )

inline

Definition at line 223 of file Shape.h.

  {
    std::swap(_size, other._size);
    dims_ = std::move(other.dims_);
  }

Resize()

void nnfw::cker::Shape::Resize ( int  dimensions_count )

inline

Definition at line 166 of file Shape.h.

  {
    // If dims_ is in a valueless state (i.e. not yet initialized or lost due to an exception),
    // initialize dims_ explicitly based on dimensions_count to ensure it is in a valid state.
    if (dims_.valueless_by_exception())
    {
      initStorage(dimensions_count);
    }
 
    std::vector<int32_t> oldDims;
    oldDims.reserve(_size);
    if (_size <= kMaxSmallSize)
    {
      const auto &arr = std::get<std::array<int32_t, kMaxSmallSize>>(dims_);
      oldDims.assign(arr.begin(), arr.begin() + _size);
    }
    else
    {
      oldDims = std::get<std::vector<int32_t>>(dims_);
    }
 
    int count = std::min(_size, dimensions_count);
 
    if (dimensions_count <= kMaxSmallSize)
    {
      std::array<int32_t, kMaxSmallSize> dims = {};
      std::copy_n(oldDims.begin(), count, dims.begin());
      dims_ = dims;
    }
    else
    {
      std::vector<int32_t> dims(dimensions_count, 0);
      std::copy_n(oldDims.begin(), count, dims.begin());
      dims_ = dims;
    }
 
    _size = dimensions_count;
  }

References kMaxSmallSize.

Referenced by BuildFrom(), nnfw::cker::BatchMatMul::prepare(), and ReplaceWith().

SetDim()

void nnfw::cker::Shape::SetDim ( int  i, int32_t  val  )

inline

Definition at line 120 of file Shape.h.

  {
    assert(i >= 0 && i < _size);
    if (_size <= kMaxSmallSize)
    {
      std::get<std::array<int32_t, kMaxSmallSize>>(dims_)[i] = val;
    }
    else
    {
      std::get<std::vector<int32_t>>(dims_)[i] = val;
    }
  }

References kMaxSmallSize.

Referenced by onert::backend::train::ops::MeanLayer::backward(), nnfw::cker::BatchToSpaceND(), nnfw::cker::BatchMatMul::prepare(), Shape(), and nnfw::cker::BCast::ToShape().

Field Documentation

kMaxSmallSize

constexpr int nnfw::cker::Shape::kMaxSmallSize = 6

staticconstexpr

Definition at line 39 of file Shape.h.

Referenced by Dims(), DimsData(), DimsData(), Resize(), SetDim(), and Shape().

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

• runtime/compute/cker/include/cker/Shape.h