caffe2::AbstractUnsortedSegmentOp< T, SIndex, Context, Reducer, SparseFused, InputAccessor > Class Template Reference

Unsorted segment reduction op with optional fused embedding lookup. More...

#include <segment_reduction_op.h>

Inheritance diagram for caffe2::AbstractUnsortedSegmentOp< T, SIndex, Context, Reducer, SparseFused, InputAccessor >:

Public Types
enum	{ INDICES = Reducer::kInputCount, SEGMENT_IDS = Reducer::kInputCount + (SparseFused ? 1 : 0) }
Public Types inherited from caffe2::Observable< OperatorBase >
using	Observer = ObserverBase< OperatorBase >

Public Member Functions
template<class... Args>
	AbstractUnsortedSegmentOp (Args &&...args)
bool	RunOnDevice () override
template<typename IndexType >
bool	DoRunWithType ()
template<typename IndexType , int FixedSize>
bool	DoRunWithValue ()
Public Member Functions inherited from caffe2::Operator< Context >
	Operator (const OperatorDef &operator_def, Workspace *ws)
	Operator (const c10::FunctionSchema &fn_schema, std::vector< c10::IValue > inputs, std::vector< at::Tensor > outputs)
const Tensor &	Input (int idx, DeviceType type=Context::GetDeviceType())
	Retrieve a non-owning reference to the input at position 'idx' for this operator. More...
Tensor	XOutput (int idx, at::IntArrayRef dims, at::TensorOptions options)
	XOutput is a modernized version of Output which returns a Tensor rather than a Tensor* (the raw pointer in the latter case is useless, as Tensor is a pointer type.)
Public Member Functions inherited from caffe2::OperatorBase
	OperatorBase (const OperatorDef &operator_def, Workspace *ws)
	OperatorBase (const c10::FunctionSchema &schema, std::vector< c10::IValue > inputs, std::vector< at::Tensor > outputs)
bool	isLegacyOperator () const
	Return true if the operator was instantiated with OperatorDef New operators should be instantiated with FunctionSchema.
const c10::FunctionSchema &	getFunctionSchema () const
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 >	GetVectorFromIValueList (const c10::IValue &value) 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 >
const T &	Input (int idx, DeviceType type)
template<typename T >
T *	Output (int idx)
template<typename T >
T *	Output (int idx, DeviceType type)
Tensor	XOutputTensor (int idx, at::IntArrayRef dims, at::TensorOptions options)
void	SetOutputTensor (int idx, Tensor tensor)
Tensor	OutputTensorOrUndefined (int idx)
Tensor *	OutputTensor (int idx, at::IntArrayRef dims, at::TensorOptions options)
Tensor *	OutputTensorCopyFrom (int idx, at::TensorOptions options, const Tensor &src, bool async=false)
Tensor *	OutputTensorAlias (int idx, const Tensor &src)
template<typename T >
T *	Output (int idx, T *allocated)
const Blob &	InputBlob (int idx)
Blob *	OutputBlob (int idx)
bool	IsInputOutputAlias (int i, int j)
template<typename T >
bool	InputIsType (int idx)
bool	InputIsTensorType (int idx, DeviceType device_type)
template<typename T >
bool	OutputIsType (int idx)
bool	OutputIsTensorType (int idx, DeviceType type)
int	InputSize () const
int	OutputSize () const
const vector< const Blob * > &	Inputs () const
const vector< Blob * > &	Outputs ()
vector< TensorShape >	InputTensorShapes () const
virtual void	WaitEvent (const Event &ev, int=-1)
void	Wait (const OperatorBase &other, int stream_id=-1)
virtual void	WaitEvents (const std::vector< const Event * > &events, int=-1)
virtual void	Finish ()
virtual bool	Run (int=0)
virtual bool	HasAsyncPart () const
virtual bool	SupportsAsyncScheduling () const
virtual bool	RunAsync (int stream_id=0)
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
virtual void	SyncDeviceBarrierForObservers ()
virtual bool	IsStreamFree (int) const
const std::string &	type () const
void	annotate_engine (const std::string &engine)
const std::string &	engine () const
void	SetExecutorHelper (ExecutorHelper *helper)
ExecutorHelper *	GetExecutorHelper () const
std::vector< at::Tensor >	move_newstyle_outputs ()&&
template<>
NetDef	GetSingleArgument (const std::string &name, const NetDef &default_value) const
template<>
vector< int >	GetVectorFromIValueList (const c10::IValue &value) const
template<>
vector< float >	GetVectorFromIValueList (const c10::IValue &value) const
template<>
vector< string >	GetVectorFromIValueList (const c10::IValue &value) const
Public Member Functions inherited from caffe2::Observable< OperatorBase >
	Observable (Observable &&)=default
Observable &	operator= (Observable &&)=default
	C10_DISABLE_COPY_AND_ASSIGN (Observable)
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

Static Public Attributes
static constexpr int	kSelfInputs = SparseFused ? 2 : 1
static constexpr int	kNumInputs = Reducer::kInputCount + kSelfInputs
Static Public Attributes inherited from caffe2::OperatorBase
static const int	kNoNetPositionSet = -1

Additional Inherited Members
Protected Member Functions inherited from caffe2::OperatorBase
virtual void	RecordEvent (const char *=nullptr)
void	SetEventFinished (const char *err_msg=nullptr)
void	SetEventFinishedWithException (const char *err_msg=nullptr)
std::string	getErrorMsg ()
	C10_DISABLE_COPY_AND_ASSIGN (OperatorBase)
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, typename SIndex, class Context, class Reducer, bool SparseFused = true, class InputAccessor = BaseInputAccessor<T>>
class caffe2::AbstractUnsortedSegmentOp< T, SIndex, Context, Reducer, SparseFused, InputAccessor >

Unsorted segment reduction op with optional fused embedding lookup.

Base implementation for UnsortedSegmentXXX and UnsparseSortedSegmentXXX depending on SparseFused static argument.

Unlike the sorted version it allows to have "gaps" in segment ids.

Inputs: 0: DATA - input embedding to do lookups in 1..P: AUX_ARG_ - optional additional arguments to be passed to the reducer, should have the same first dimension as SEGMENT_IDS (e.g. scalars in WeightedSum)

if SparseFused == true:

P+1: INDICES - 1-D vector with indices to look up in DATA. Should have the same dimension as SEGMENT_IDS

P+1 if SparseFused == false:

P+1 or P+2: SEGMENT_IDS - unsorted segment ids 1-D vector

Args: num_segments - allows to override the dimension of the output. If not set it would be inferred from segment_ids tensor.

Output: Tensor with first dimension of K, where K is the max segment id + 1. Rest of dimensions are decided by reducer but usually are the same size as extra dimensions of DATA

Definition at line 987 of file segment_reduction_op.h.

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

• caffe2/operators/segment_reduction_op.h