#include <tensor.h>

Public Member Functions
	Tensor ()=default

	Tensor (MLDataType elt_type, const TensorShape &shape, void *p_data, const OrtMemoryInfo &location, ptrdiff_t offset=0, gsl::span< const int64_t > strides={})

	Tensor (MLDataType elt_type, const TensorShape &shape, void *p_data, std::shared_ptr< IAllocator > deleter, ptrdiff_t offset=0, gsl::span< const int64_t > strides={})

	Tensor (MLDataType elt_type, const TensorShape &shape, std::shared_ptr< IAllocator > allocator)
	Create a Tensor that allocates and owns the buffer required for the specified shape. More...

	~Tensor ()

	ORT_DISALLOW_COPY_AND_ASSIGNMENT (Tensor)

	Tensor (Tensor &&other) noexcept

Tensor &	operator= (Tensor &&other) noexcept

MLDataType	DataType () const

int32_t	GetElementType () const

bool	IsDataTypeString () const

template<class T >
bool	IsDataType () const

const TensorShape &	Shape () const noexcept

const OrtMemoryInfo &	Location () const

template<typename T >
T *	MutableData ()

template<typename T >
gsl::span< T >	MutableDataAsSpan ()

template<typename T >
const T *	Data () const

template<typename T >
gsl::span< const T >	DataAsSpan () const

void *	MutableDataRaw (MLDataType type)

const void *	DataRaw (MLDataType type) const

void *	MutableDataRaw () noexcept

const void *	DataRaw () const noexcept

bool	OwnsBuffer () const noexcept

void	Reshape (const TensorShape &new_shape)

ptrdiff_t	ByteOffset () const

void	SetByteOffset (ptrdiff_t byte_offset)

int64_t	NumStorageElements () const
	The number of Tensor "storage" elements. A single storage element may contain multiple sub-elements for sub-byte data types (e.g., int4). More...

size_t	SizeInBytes () const

Static Public Member Functions
static void	InitOrtValue (MLDataType elt_type, const TensorShape &shape, void *p_data, const OrtMemoryInfo &location, OrtValue &ort_value, ptrdiff_t offset=0, gsl::span< const int64_t > strides={})
	Creates an instance of Tensor on the heap and initializes OrtValue with it. More...

static void	InitOrtValue (MLDataType elt_type, const TensorShape &shape, void *p_data, std::shared_ptr< IAllocator > allocator, OrtValue &ort_value, ptrdiff_t offset=0, gsl::span< const int64_t > strides={})
	Creates an instance of Tensor on the heap which will take over ownership of the pre-allocated buffer. More...

static void	InitOrtValue (MLDataType elt_type, const TensorShape &shape, std::shared_ptr< IAllocator > allocator, OrtValue &ort_value)
	Creates an instance of Tensor on the heap and initializes OrtValue with it. The Tensor instance will allocate and own the data required for `shape`. More...

static void	InitOrtValue (Tensor &&tensor, OrtValue &ort_value)
	Initializes OrtValue with an existing Tensor. More...

static size_t	CalculateTensorStorageSize (MLDataType elt_type, const TensorShape &shape)
	Calculate the required storage for the tensor. More...

static Status	CalculateTensorStorageSize (MLDataType elt_type, const TensorShape &shape, size_t alignment, size_t &storage_size)
	Calculate the required storage for the tensor. More...

Detailed Description

Definition at line 39 of file tensor.h.

Constructor & Destructor Documentation

onnxruntime::Tensor::Tensor ( )

default

onnxruntime::Tensor::Tensor	(	MLDataType	elt_type,
		const TensorShape &	shape,
		void *	p_data,
		const OrtMemoryInfo &	location,
		ptrdiff_t	offset = `0`,
		gsl::span< const int64_t >	strides = `{}`
	)

Create tensor with given type, shape, pre-allocated memory and allocator info. This function does not check if the preallocated buffer(p_data) has enough room for the shape.

Parameters

elt_type	Data type of the tensor elements.
shape	Shape of the tensor
p_data	A preallocated buffer. Can be NULL if the shape is empty. Tensor does not own the data and will not delete it
location	Memory info for location of p_data.
offset	Offset in bytes to start of Tensor within p_data.
strides	Strides span. Can be empty if the tensor is contiguous.

onnxruntime::Tensor::Tensor	(	MLDataType	elt_type,
		const TensorShape &	shape,
		void *	p_data,
		std::shared_ptr< IAllocator >	deleter,
		ptrdiff_t	offset = `0`,
		gsl::span< const int64_t >	strides = `{}`
	)

Create tensor with given type, shape, pre-allocated memory and allocator which will be used to free the pre-allocated memory. The Tensor will take over ownership of p_data. This function does not check if the preallocated buffer(p_data) has enough room for the shape.

Parameters

elt_type	Data type of the tensor elements.
shape	Shape of the tensor
p_data	A preallocated buffer. Can be NULL if the shape is empty. Tensor will own the memory and will delete it when the tensor instance is destructed.
deleter	Allocator used to free the pre-allocated memory
offset	Offset in bytes to start of Tensor within p_data.
strides	Strides span. Can be empty if the tensor is contiguous.

onnxruntime::Tensor::Tensor	(	MLDataType	elt_type,
		const TensorShape &	shape,
		std::shared_ptr< IAllocator >	allocator
	)

Create a Tensor that allocates and owns the buffer required for the specified shape.

Parameters

elt_type	Data type of the tensor elements.
shape	Tensor shape.
allocator	Allocator to use to create and free buffer.

onnxruntime::Tensor::~Tensor ( )

onnxruntime::Tensor::Tensor ( Tensor && other )

noexcept

Member Function Documentation

ptrdiff_t onnxruntime::Tensor::ByteOffset ( ) const

inline

Get the byte offset with respect to the p_data

Warning: this is a temporary solution for reusing the buffer bigger than needed.; use with caution - make sure you do boundary check before calling this method (see view.cc)

Definition at line 273 of file tensor.h.

static size_t onnxruntime::Tensor::CalculateTensorStorageSize	(	MLDataType	elt_type,
		const TensorShape &	shape
	)

static

Calculate the required storage for the tensor.

Parameters

elt_type	Data type of the tensor elements.
shape	Tensor shape.

Returns: Bytes required.

static Status onnxruntime::Tensor::CalculateTensorStorageSize	(	MLDataType	elt_type,
		const TensorShape &	shape,
		size_t	alignment,
		size_t &	storage_size
	)

static

Calculate the required storage for the tensor.

Parameters

elt_type	Data type of the tensor elements.
shape	Tensor shape.
alignment	Power of 2 alignment to include in calculation. Bumps up result to the nearest multiple of alignment. Set to 0 to ignore.
storage_size	The resulting storage size.

Returns: Status indicating success or failure.

template<typename T >

const T* onnxruntime::Tensor::Data ( ) const

inline

Definition at line 218 of file tensor.h.

template<typename T >

gsl::span<const T> onnxruntime::Tensor::DataAsSpan ( ) const

inline

Definition at line 226 of file tensor.h.

const void* onnxruntime::Tensor::DataRaw ( MLDataType type ) const

inline

Definition at line 239 of file tensor.h.

const void* onnxruntime::Tensor::DataRaw ( ) const

inlinenoexcept

Definition at line 248 of file tensor.h.

MLDataType onnxruntime::Tensor::DataType ( ) const

inline

Returns the data type.

Definition at line 162 of file tensor.h.

int32_t onnxruntime::Tensor::GetElementType ( ) const

inline

Returns the data type enum constant

Remarks: Use utils::ToTensorProtoElementType<T> for comparison.

Definition at line 168 of file tensor.h.

static void onnxruntime::Tensor::InitOrtValue	(	MLDataType	elt_type,
		const TensorShape &	shape,
		void *	p_data,
		const OrtMemoryInfo &	location,
		OrtValue &	ort_value,
		ptrdiff_t	offset = `0`,
		gsl::span< const int64_t >	strides = `{}`
	)

static

Creates an instance of Tensor on the heap and initializes OrtValue with it.

Parameters

elt_type	Data type of the tensor elements.
shape	Tensor shape.
p_data	Tensor data.
location	Memory info for location of p_data.
ort_value	OrtValue to populate with Tensor.
offset	Optional offset if Tensor refers to a subset of p_data.
strides	Optional strides if Tensor refers to a subset of p_data.

static void onnxruntime::Tensor::InitOrtValue	(	MLDataType	elt_type,
		const TensorShape &	shape,
		void *	p_data,
		std::shared_ptr< IAllocator >	allocator,
		OrtValue &	ort_value,
		ptrdiff_t	offset = `0`,
		gsl::span< const int64_t >	strides = `{}`
	)

static

Creates an instance of Tensor on the heap which will take over ownership of the pre-allocated buffer.

Parameters

elt_type Data type of the tensor elements.

<param name="shape"Tensor shape.

Parameters

p_data	Tensor data.
allocator	Allocator that was used to create p_data and will be used to free it.
ort_value	OrtValue to populate with Tensor.
offset	Optional offset if Tensor refers to a subset of p_data.
strides	Optional strides if Tensor refers to a subset of p_data.

static void onnxruntime::Tensor::InitOrtValue	(	MLDataType	elt_type,
		const TensorShape &	shape,
		std::shared_ptr< IAllocator >	allocator,
		OrtValue &	ort_value
	)

static

Creates an instance of Tensor on the heap and initializes OrtValue with it. The Tensor instance will allocate and own the data required for shape.

Parameters

elt_type	Data type of the tensor elements.
shape	Tensor shape.
allocator	Allocator that was used to create p_data and will be used to free it.
ort_value	OrtValue to populate with Tensor.

static void onnxruntime::Tensor::InitOrtValue	(	Tensor &&	tensor,
		OrtValue &	ort_value
	)

static

Initializes OrtValue with an existing Tensor.

Parameters

tensor	Tensor.
ort_value	OrtValue to populate with Tensor.

template<class T >

bool onnxruntime::Tensor::IsDataType ( ) const

inline

Definition at line 180 of file tensor.h.

bool onnxruntime::Tensor::IsDataTypeString ( ) const

inline

Definition at line 174 of file tensor.h.

const OrtMemoryInfo& onnxruntime::Tensor::Location ( ) const

inline

Returns the location of the tensor's memory

Definition at line 192 of file tensor.h.

template<typename T >

T* onnxruntime::Tensor::MutableData ( )

inline

May return nullptr if tensor size is zero

Definition at line 198 of file tensor.h.

template<typename T >

gsl::span<T> onnxruntime::Tensor::MutableDataAsSpan ( )

inline

May return nullptr if tensor size is zero

Definition at line 209 of file tensor.h.

void* onnxruntime::Tensor::MutableDataRaw ( MLDataType type )

inline

Definition at line 234 of file tensor.h.

void* onnxruntime::Tensor::MutableDataRaw ( )

inlinenoexcept

Definition at line 244 of file tensor.h.

int64_t onnxruntime::Tensor::NumStorageElements ( ) const

The number of Tensor "storage" elements. A single storage element may contain multiple sub-elements for sub-byte data types (e.g., int4).

For element types smaller than 1 byte (e.g., int4), a single storage element stores multiple sub-byte elements. Example: Tensor<int4> of shape (4,) has 2 storage elements.

For element types >= 1 byte, this function returns the product of the shape. Example: Tensor<int8> of shape (4,) has 4 storage elements.

Returns: Number of tensor storage elements

Tensor& onnxruntime::Tensor::operator= ( Tensor && other )

noexcept

onnxruntime::Tensor::ORT_DISALLOW_COPY_AND_ASSIGNMENT ( Tensor )

bool onnxruntime::Tensor::OwnsBuffer ( ) const

inlinenoexcept

Definition at line 252 of file tensor.h.

void onnxruntime::Tensor::Reshape ( const TensorShape & new_shape )

inline

Resizes the tensor without touching underlying storage. This requires the total size of the tensor to remains constant.

Warning: this function is NOT thread-safe.

Definition at line 261 of file tensor.h.

void onnxruntime::Tensor::SetByteOffset ( ptrdiff_t byte_offset )

inline

Set the byte offset with respect to the p_data

Warning: this is a temporary solution for reusing the buffer bigger than needed.

Definition at line 281 of file tensor.h.

const TensorShape& onnxruntime::Tensor::Shape ( ) const

inlinenoexcept

Returns the shape of the tensor.

Definition at line 187 of file tensor.h.

size_t onnxruntime::Tensor::SizeInBytes ( ) const

The number of bytes of data.

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

onnxruntime/core/framework/tensor.h

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation