#include <Tensor.h>

Collaboration diagram for onert::backend::train::Tensor:

[legend]

Public Member Functions
	Tensor ()=delete

	Tensor (const ir::OperandInfo &info)

bool	applyShape (const ir::Shape &) override
	Set the shape to `shape` and possibly re-allocate the buffer.

Public Member Functions inherited from onert::backend::basic::Tensor
	Tensor ()=delete

virtual	~Tensor ()

	Tensor (const ir::OperandInfo &info, DynamicMemoryManager *dynamic_mem_mgr)

void	setBuffer (uint8_t *buffer)
	Set the Buffer object. This method is called for static and non-const tensor.

void	setBuffer (const std::shared_ptr< Allocator > &alloc)
	Set the Buffer object. This method is called for dynamic or const tensor.

void	deallocBuffer () override
	Reset the buffer and deallocate the allocation if it is managed by itself.

uint8_t *	buffer () const override

void	set_dynamic () override
	set this tensor dynamic

virtual void	increase_ref ()

virtual void	decrease_ref ()

virtual void	reset_ref ()
	Reset reference count to zero and release data.

virtual int32_t	num_references ()

void	setShape (const ir::Shape &new_shape) override
	Set the shape of tenser to new_shape.

Public Member Functions inherited from onert::backend::IPortableTensor
	IPortableTensor (const ir::OperandInfo &info)

virtual	~IPortableTensor ()

const ir::OperandInfo &	get_info () const

const ir::Sparsity *	sparsity () const

size_t	total_size () const override final

size_t	calcOffset (const ir::Coordinates &coords) const override final

ir::DataType	data_type () const override final

float	data_scale () const override final

int32_t	data_zero_point () const override final

const std::vector< float > &	data_scales () const override final

const std::vector< int32_t > &	data_zero_points () const override

bool	is_constant () const override final
	Return true if the tensor is constant.

bool	is_dynamic () const override final
	Return true if the tensor needs dynamic allocation, meaning that during compile-time the outpus shape cannot be known and the output shape is calculated during kernel execution-time.

ir::Shape	getShape () const override final
	Get ir::Shape of tensor.

bool	has_padding () const final

void	access (const std::function< void(ITensor &tensor)> &fn) final

Public Member Functions inherited from onert::backend::ITensor
virtual	~ITensor ()

virtual bool	is_subtensor () const

virtual bool	needMemoryMap () const

virtual void	enqueueWriteBuffer (const void *, bool)

virtual void	enqueueReadBuffer (void *, bool)

Additional Inherited Members
Protected Attributes inherited from onert::backend::basic::Tensor
uint8_t *	_buffer

size_t	_size

int32_t	_num_references

DynamicMemoryManager *	_dynamic_mem_mgr

Protected Attributes inherited from onert::backend::IPortableTensor
ir::OperandInfo	_info

Detailed Description

Definition at line 27 of file Tensor.h.

Constructor & Destructor Documentation

◆ Tensor() [1/2]

onert::backend::train::Tensor::Tensor ( )

delete

◆ Tensor() [2/2]

onert::backend::train::Tensor::Tensor ( const ir::OperandInfo & info )

inline

Definition at line 33 of file Tensor.h.

                                    : basic::Tensor{info, nullptr}
  {
    // DO NOTHING
  }

Member Function Documentation

◆ applyShape()

bool onert::backend::train::Tensor::applyShape ( const ir::Shape & )

inlineoverridevirtual

Set the shape to shape and possibly re-allocate the buffer.

If a tensor is dynamic tensor and previously allocated memory exists, it will be deallocated. If a tensor is static tensor (with previously allocated memory by StaticTensorManager), buffer() will be overwriten

Parameters

shape tensor's new shape. While allocating memory for this new_shape, tensor's shape is set to new_shape

Returns: true If applying shape is successful; false If not applying shape is not supported (it throws for other errors)

Reimplemented from onert::backend::basic::Tensor.

Definition at line 39 of file Tensor.h.

39{ return false; }

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

runtime/onert/backend/train/Tensor.h