tvm
Public Member Functions | Static Public Member Functions | List of all members
tvm::meta_schedule::FeatureExtractor Class Reference

Managed reference to FeatureExtractorNode. More...

#include <feature_extractor.h>

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 Objectget () const
 
const Objectoperator-> () const
 
bool unique () const
 
int use_count () const
 
template<typename ObjectType , typename = std::enable_if_t<std::is_base_of_v<Object, ObjectType>>>
const ObjectType * as () const
 Try to downcast the internal Object to a raw pointer of a corresponding type. More...
 
template<typename ObjectRefType , typename = std::enable_if_t<std::is_base_of_v<ObjectRef, ObjectRefType>>>
Optional< ObjectRefType > as () const
 Try to downcast the ObjectRef to a Optional<T> of the requested 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
Objectget_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< Objectdata_
 Internal pointer that backs the reference. More...
 

Detailed Description

Managed reference to FeatureExtractorNode.

See also
FeatureExtractorNode

Member Function Documentation

◆ PerStoreFeature()

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_storeThe number of buffers in each BufferStore; Pad or truncate if necessary.
arith_intensity_curve_num_samplesThe number of samples used in the arithmetic intensity curve.
cache_line_bytesThe number of bytes in a cache line.
extract_workloadWhether to extract features in the workload in tuning context or not.
Returns
The feature extractor created.

◆ PyFeatureExtractor()

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_fromThe packed function of ExtractFrom.
f_as_stringThe packed function of AsString.
Returns
The feature extractor created.

◆ TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS()

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

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