#include <tensor.h>

Public Member Functions
	Tensor ()=default

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

	Tensor (MLDataType p_type, const TensorShape &shape, std::shared_ptr< IAllocator > allocator, gsl::span< const int64_t > strides={})

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

	~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)

size_t	SizeInBytes () const

Static Public Member Functions
static void	InitOrtValue (MLDataType p_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 using the appropriate __ctor and initializes OrtValue with it. More...

static void	InitOrtValue (MLDataType p_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 who own the pre-allocated buffer. More...

static size_t	CalculateTensorStorageSize (MLDataType p_type, const TensorShape &shape, gsl::span< const int64_t > strides={})

static void	InitOrtValue (MLDataType elt_type, const TensorShape &shape, std::shared_ptr< IAllocator > allocator, OrtValue &ort_value, gsl::span< const int64_t > strides={})
	Creates an instance of Tensor on the heap using the appropriate __ctor and initializes OrtValue with it. More...

static void	InitOrtValue (Tensor &&tensor, OrtValue &ort_value)
	Creates an instance of Tensor on the heap using the appropriate __ctor and initializes OrtValue with it. More...

Detailed Description

Definition at line 38 of file tensor.h.

Constructor & Destructor Documentation

onnxruntime::Tensor::Tensor ( )

default

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

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

Parameters

p_type	Data type of the tensor
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
alloc	Where the buffer('p_data') was allocated from
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	p_type,
		const TensorShape &	shape,
		std::shared_ptr< IAllocator >	allocator,
		gsl::span< const int64_t >	strides = `{}`
	)

Deprecated. The original design is this Tensor class won't do any allocation / release. However, this function will allocate the buffer for the shape, and do placement new if p_type is string tensor.

onnxruntime::Tensor::Tensor	(	MLDataType	p_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. This function won't check if the preallocated buffer(p_data) has enough room for the shape. However, this function will de-allocate the buffer upon the tensor getting destructed.

Parameters

p_type	Data type of the tensor
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 ( )

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 261 of file tensor.h.

static size_t onnxruntime::Tensor::CalculateTensorStorageSize	(	MLDataType	p_type,
		const TensorShape &	shape,
		gsl::span< const int64_t >	strides = `{}`
	)

static

template<typename T >

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

inline

Definition at line 206 of file tensor.h.

template<typename T >

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

inline

Definition at line 214 of file tensor.h.

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

inline

Definition at line 227 of file tensor.h.

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

inlinenoexcept

Definition at line 236 of file tensor.h.

MLDataType onnxruntime::Tensor::DataType ( ) const

inline

Returns the data type.

Definition at line 150 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 156 of file tensor.h.

static void onnxruntime::Tensor::InitOrtValue	(	MLDataType	p_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 using the appropriate __ctor and initializes OrtValue with it.

Parameters

p_type
shape
p_data
info
offset
strides

static void onnxruntime::Tensor::InitOrtValue	(	MLDataType	p_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 who own the pre-allocated buffer.

Parameters

p_type
shape
p_data
allocator
offset
strides

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

static

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

Parameters

elt_type
shape
allocator
ort_value
strides

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

static

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

Parameters

tensor
ort_value

template<class T >

bool onnxruntime::Tensor::IsDataType ( ) const

inline

Definition at line 168 of file tensor.h.

bool onnxruntime::Tensor::IsDataTypeString ( ) const

inline

Definition at line 162 of file tensor.h.

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

inline

Returns the location of the tensor's memory

Definition at line 180 of file tensor.h.

template<typename T >

T* onnxruntime::Tensor::MutableData ( )

inline

May return nullptr if tensor size is zero

Definition at line 186 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 197 of file tensor.h.

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

inline

Definition at line 222 of file tensor.h.

void* onnxruntime::Tensor::MutableDataRaw ( )

inlinenoexcept

Definition at line 232 of file tensor.h.

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

noexcept

onnxruntime::Tensor::ORT_DISALLOW_COPY_AND_ASSIGNMENT ( Tensor )

bool onnxruntime::Tensor::OwnsBuffer ( ) const

inlinenoexcept

Definition at line 240 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 249 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 269 of file tensor.h.

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

inlinenoexcept

Returns the shape of the tensor.

Definition at line 175 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