Caffe2 - C++ API: caffe2::TileGradientOp< T, Context

Inheritance diagram for caffe2::TileGradientOp< T, Context >:

Public Member Functions
	TileGradientOp (const OperatorDef &operator_def, Workspace *ws)

bool	RunOnDevice () override

Public Member Functions inherited from caffe2::Operator< Context >
	Operator (const OperatorDef &operator_def, Workspace *ws)

const Tensor< Context > &	Input (int idx)

Tensor< Context > *	Output (int idx)

void	WaitEvent (const Event &ev, int stream_id=-1) final

void	WaitEvents (const std::vector< const Event * > &events, int stream_id=-1) final

bool	Run (int stream_id=0) final

bool	RunAsync (int stream_id=0) final

bool	IsStreamFree (int stream_id) const override

bool	HasAsyncPart () const override

bool	SupportsAsyncScheduling () const override

const Context *	getContext () const

Public Member Functions inherited from caffe2::OperatorBase
	OperatorBase (const OperatorDef &operator_def, Workspace *ws)

bool	HasArgument (const string &name) const
	Checks if the operator has an argument of the given name.

template<typename T >
T	GetSingleArgument (const string &name, const T &default_value) const

template<typename T >
bool	HasSingleArgumentOfType (const string &name) const

template<typename T >
vector< T >	GetRepeatedArgument (const string &name, const vector< T > &default_value={}) const

template<typename T >
const T &	Input (int idx)

template<typename T >
T *	Output (int idx)

template<typename T >
T *	Output (int idx, T *allocated)

const Blob &	InputBlob (int idx)

Blob *	OutputBlob (int idx)

template<typename T >
bool	InputIsType (int idx)

template<typename T >
bool	OutputIsType (int idx)

int	InputSize () const

int	OutputSize () const

const vector< const Blob * > &	Inputs () const

const vector< Blob * > &	Outputs ()

vector< TensorShape >	InputTensorShapes ()

void	Wait (const OperatorBase &other, int stream_id=-1)

virtual void	Finish ()

virtual void	AddRelatedBlobInfo (EnforceNotMet *err)

const OperatorDef &	debug_def () const

void	set_debug_def (const std::shared_ptr< const OperatorDef > &operator_def)

bool	has_debug_def () const

void	RecordLastFailedOpNetPosition ()

int	net_position () const

void	set_net_position (int idx)

const DeviceOption &	device_option () const

const Event &	event () const

Event &	event ()

void	ResetEvent ()

void	DisableEvent ()

bool	IsEventDisabled () const

const std::string &	type () const

void	annotate_engine (const std::string &engine)

const std::string &	engine () const

Public Member Functions inherited from caffe2::Observable< OperatorBase >
const Observer *	AttachObserver (std::unique_ptr< Observer > observer)

std::unique_ptr< Observer >	DetachObserver (const Observer *observer_ptr)
	Returns a unique_ptr to the removed observer. More...

virtual size_t	NumObservers ()

void	StartAllObservers ()

void	StopAllObservers ()

Data Fields
	USE_OPERATOR_CONTEXT_FUNCTIONS

Additional Inherited Members
Public Types inherited from caffe2::Observable< OperatorBase >
using	Observer = ObserverBase< OperatorBase >

Static Public Attributes inherited from caffe2::OperatorBase
static constexpr int	kNoNetPositionSet = -1

Protected Member Functions inherited from caffe2::Operator< Context >
void	RecordEvent (const char *err_msg=nullptr) final

std::string	getErrorMsg ()

Protected Member Functions inherited from caffe2::OperatorBase
	DISABLE_COPY_AND_ASSIGN (OperatorBase)

Protected Attributes inherited from caffe2::Operator< Context >
Context	context_

Protected Attributes inherited from caffe2::OperatorBase
std::unique_ptr< Event >	event_

Protected Attributes inherited from caffe2::Observable< OperatorBase >
std::vector< std::unique_ptr< Observer > >	observers_list_

Detailed Description

template<typename T, class Context>
class caffe2::TileGradientOp< T, Context >

Definition at line 130 of file tile_op.h.

Member Function Documentation

template<typename T , class Context >

bool caffe2::TileGradientOp< T, Context >::RunOnDevice ( )

inlineoverridevirtual

How this works: Imagine a 2D tensor (matrix) of size 3x10, tiled 2 times along axis 1 (column). This is equivalent to multiplying by a vector of 1s transposed. The gradient of this is all 1s in the shape of the input matrix (call it X). So the output gradient should be the matrix multipication result of input gradient (gradient of tiled tensor output) and X.

Implements caffe2::Operator< Context >.

Definition at line 139 of file tile_op.h.

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

caffe2/operators/tile_op.h

Public Member Functions

Data Fields

Additional Inherited Members

Detailed Description

template<typename T, class Context> class caffe2::TileGradientOp< T, Context >

Member Function Documentation

Facebook Open Source

template<typename T, class Context>
class caffe2::TileGradientOp< T, Context >