Inheritance diagram for tvm::meta_schedule::FeatureExtractor:

Collaboration diagram for tvm::meta_schedule::FeatureExtractor:

Public Member Functions
	TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS (FeatureExtractor, ObjectRef, FeatureExtractorNode)

Public Member Functions inherited from tvm::runtime::ObjectRef
	ObjectRef ()=default
	default constructor More...

	ObjectRef (ObjectPtr< Object > data)
	Constructor from existing object ptr. More...

bool	same_as (const ObjectRef &other) const
	Comparator. More...

bool	operator== (const ObjectRef &other) const
	Comparator. More...

bool	operator!= (const ObjectRef &other) const
	Comparator. More...

bool	operator< (const ObjectRef &other) const
	Comparator. More...

bool	defined () const

const Object *	get () const

const Object *	operator-> () const

bool	unique () const

int	use_count () const

template<typename ObjectType >
const ObjectType *	as () const
	Try to downcast the internal Object to a raw pointer of a corresponding type. More...

Static Public Member Functions
static FeatureExtractor	PerStoreFeature (int buffers_per_store=5, int arith_intensity_curve_num_samples=10, int cache_line_bytes=64, bool extract_workload=false)
	Create a feature extractor that extracts features from each BufferStore. More...

static FeatureExtractor	PyFeatureExtractor (PyFeatureExtractorNode::FExtractFrom f_extract_from, PyFeatureExtractorNode::FAsString f_as_string)
	Create a feature extractor with customized methods on the python-side. More...

Additional Inherited Members
Public Types inherited from tvm::runtime::ObjectRef
using	ContainerType = Object
	type indicate the container type. More...

Static Public Attributes inherited from tvm::runtime::ObjectRef
static constexpr bool	_type_is_nullable = true

Protected Member Functions inherited from tvm::runtime::ObjectRef
Object *	get_mutable () const

Static Protected Member Functions inherited from tvm::runtime::ObjectRef
template<typename T >
static T	DowncastNoCheck (ObjectRef ref)
	Internal helper function downcast a ref without check. More...

static void	FFIClearAfterMove (ObjectRef *ref)
	Clear the object ref data field without DecRef after we successfully moved the field. More...

template<typename ObjectType >
static ObjectPtr< ObjectType >	GetDataPtr (const ObjectRef &ref)
	Internal helper function get data_ as ObjectPtr of ObjectType. More...

Protected Attributes inherited from tvm::runtime::ObjectRef
ObjectPtr< Object >	data_
	Internal pointer that backs the reference. More...

Detailed Description

Managed reference to FeatureExtractorNode.

Member Function Documentation

static FeatureExtractor tvm::meta_schedule::FeatureExtractor::PerStoreFeature	(	int	buffers_per_store = `5`,
		int	arith_intensity_curve_num_samples = `10`,
		int	cache_line_bytes = `64`,
		bool	extract_workload = `false`
	)

static

Create a feature extractor that extracts features from each BufferStore.

Parameters

buffers_per_store	The number of buffers in each BufferStore; Pad or truncate if necessary.
arith_intensity_curve_num_samples	The number of samples used in the arithmetic intensity curve.
cache_line_bytes	The number of bytes in a cache line.
extract_workload	Whether to extract features in the workload in tuning context or not.

static FeatureExtractor tvm::meta_schedule::FeatureExtractor::PyFeatureExtractor	(	PyFeatureExtractorNode::FExtractFrom	f_extract_from,
		PyFeatureExtractorNode::FAsString	f_as_string
	)

static

Create a feature extractor with customized methods on the python-side.

Parameters

f_extract_from	The packed function of `ExtractFrom`.
f_as_string	The packed function of `AsString`.

tvm::meta_schedule::FeatureExtractor::TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS	(	FeatureExtractor	,
		ObjectRef	,
		FeatureExtractorNode
	)

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