The python side customizable class for measure candidate generation. More...

#include <search_strategy.h>

Inheritance diagram for tvm::meta_schedule::PySearchStrategyNode:

Collaboration diagram for tvm::meta_schedule::PySearchStrategyNode:

Public Types
using	FInitializeWithTuneContext = SearchStrategy::FInitializeWithTuneContext

using	FPreTuning = SearchStrategy::FPreTuning

using	FPostTuning = SearchStrategy::FPostTuning

using	FGenerateMeasureCandidates = SearchStrategy::FGenerateMeasureCandidates

using	FNotifyRunnerResults = SearchStrategy::FNotifyRunnerResults

using	FClone = SearchStrategy::FClone

Public Member Functions
void	InitializeWithTuneContext (const TuneContext &context) final
	Initialize the search strategy with tuning context. More...

void	PreTuning (int max_trials, int num_trials_per_iter, const Array< tir::Schedule > &design_spaces, const Optional< Database > &database, const Optional< CostModel > &cost_model) final
	Pre-tuning for the search strategy. More...

void	PostTuning () final
	Post-tuning for the search strategy. More...

Optional< Array< MeasureCandidate > >	GenerateMeasureCandidates () final
	Generate measure candidates from design spaces for measurement. More...

void	NotifyRunnerResults (const Array< MeasureCandidate > &measure_candidates, const Array< RunnerResult > &results)
	Update the search strategy with measurement results. More...

SearchStrategy	Clone () const final
	Clone the search strategy. More...

	TVM_DECLARE_FINAL_OBJECT_INFO (PySearchStrategyNode, SearchStrategyNode)

Public Member Functions inherited from tvm::meta_schedule::SearchStrategyNode
virtual	~SearchStrategyNode ()=default
	Virtual destructor. More...

	TVM_DECLARE_BASE_OBJECT_INFO (SearchStrategyNode, Object)

Static Public Member Functions
static void	RegisterReflection ()

Public Attributes
FInitializeWithTuneContext	f_initialize_with_tune_context
	The packed function to the `InitializeWithTuneContext` method. More...

FPreTuning	f_pre_tuning
	The packed function to the `PreTuning` method. More...

FPostTuning	f_post_tuning
	The packed function to the `PostTuning` method. More...

FGenerateMeasureCandidates	f_generate_measure_candidates
	The packed function to the `GenerateMeasureCandidates` method. More...

FNotifyRunnerResults	f_notify_runner_results
	The packed function to the `NotifyRunnerResults` method. More...

FClone	f_clone
	The packed function to the `Clone` method. More...

Static Public Attributes
static constexpr const char *	_type_key = "meta_schedule.PySearchStrategy"

Static Public Attributes inherited from tvm::meta_schedule::SearchStrategyNode
static constexpr const char *	_type_key = "meta_schedule.SearchStrategy"

Detailed Description

The python side customizable class for measure candidate generation.

Member Typedef Documentation

◆ FClone

using tvm::meta_schedule::PySearchStrategyNode::FClone = SearchStrategy::FClone

◆ FGenerateMeasureCandidates

using tvm::meta_schedule::PySearchStrategyNode::FGenerateMeasureCandidates = SearchStrategy::FGenerateMeasureCandidates

◆ FInitializeWithTuneContext

using tvm::meta_schedule::PySearchStrategyNode::FInitializeWithTuneContext = SearchStrategy::FInitializeWithTuneContext

◆ FNotifyRunnerResults

using tvm::meta_schedule::PySearchStrategyNode::FNotifyRunnerResults = SearchStrategy::FNotifyRunnerResults

◆ FPostTuning

using tvm::meta_schedule::PySearchStrategyNode::FPostTuning = SearchStrategy::FPostTuning

◆ FPreTuning

using tvm::meta_schedule::PySearchStrategyNode::FPreTuning = SearchStrategy::FPreTuning

Member Function Documentation

◆ Clone()

SearchStrategy tvm::meta_schedule::PySearchStrategyNode::Clone ( ) const

finalvirtual

Clone the search strategy.

Returns: The cloned search strategy.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ GenerateMeasureCandidates()

Optional<Array<MeasureCandidate> > tvm::meta_schedule::PySearchStrategyNode::GenerateMeasureCandidates ( )

finalvirtual

Generate measure candidates from design spaces for measurement.

Returns: The measure candidates generated, nullptr if finished.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ InitializeWithTuneContext()

void tvm::meta_schedule::PySearchStrategyNode::InitializeWithTuneContext ( const TuneContext & context )

finalvirtual

Initialize the search strategy with tuning context.

Parameters

context The tuning context for initialization.

Note: This method is supposed to be called only once before every other method.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ NotifyRunnerResults()

void tvm::meta_schedule::PySearchStrategyNode::NotifyRunnerResults	(	const Array< MeasureCandidate > &	measure_candidates,
		const Array< RunnerResult > &	results
	)

virtual

Update the search strategy with measurement results.

Parameters

measure_candidates	The candidates to be measured.
results	The measurement results from the runner.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ PostTuning()

void tvm::meta_schedule::PySearchStrategyNode::PostTuning ( )

finalvirtual

Post-tuning for the search strategy.

Note: Post-tuning is supposed to be called after the tuning process and before we reset the search strategy with another pre-tuning. Post-tuning can be empty.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ PreTuning()

void tvm::meta_schedule::PySearchStrategyNode::PreTuning	(	int	max_trials,
		int	num_trials_per_iter,
		const Array< tir::Schedule > &	design_spaces,
		const Optional< Database > &	database,
		const Optional< CostModel > &	cost_model
	)

finalvirtual

Pre-tuning for the search strategy.

Parameters

max_trials	The maximum number of trials.
num_trials_per_iter	The number of trials per iteration.
design_spaces	The design spaces used during tuning process.
database	The database used during tuning process.
cost_model	The cost model used during tuning process.

Note: Pre-tuning is supposed to be called before the tuning process and after the initialization. Because the search strategy is stateful, we can always call pretuning and reset the search strategy.

Implements tvm::meta_schedule::SearchStrategyNode.

◆ RegisterReflection()

static void tvm::meta_schedule::PySearchStrategyNode::RegisterReflection ( )

inlinestatic

◆ TVM_DECLARE_FINAL_OBJECT_INFO()

tvm::meta_schedule::PySearchStrategyNode::TVM_DECLARE_FINAL_OBJECT_INFO	(	PySearchStrategyNode	,
		SearchStrategyNode
	)

Member Data Documentation

◆ _type_key

constexpr const char* tvm::meta_schedule::PySearchStrategyNode::_type_key = "meta_schedule.PySearchStrategy"

staticconstexpr

◆ f_clone

FClone tvm::meta_schedule::PySearchStrategyNode::f_clone

The packed function to the Clone method.

◆ f_generate_measure_candidates

FGenerateMeasureCandidates tvm::meta_schedule::PySearchStrategyNode::f_generate_measure_candidates

The packed function to the GenerateMeasureCandidates method.

◆ f_initialize_with_tune_context

FInitializeWithTuneContext tvm::meta_schedule::PySearchStrategyNode::f_initialize_with_tune_context

The packed function to the InitializeWithTuneContext method.

◆ f_notify_runner_results

FNotifyRunnerResults tvm::meta_schedule::PySearchStrategyNode::f_notify_runner_results

The packed function to the NotifyRunnerResults method.

◆ f_post_tuning

FPostTuning tvm::meta_schedule::PySearchStrategyNode::f_post_tuning

The packed function to the PostTuning method.

◆ f_pre_tuning

FPreTuning tvm::meta_schedule::PySearchStrategyNode::f_pre_tuning

The packed function to the PreTuning method.

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

include/tvm/meta_schedule/search_strategy.h

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Detailed Description

Member Typedef Documentation

◆ FClone

◆ FGenerateMeasureCandidates

◆ FInitializeWithTuneContext

◆ FNotifyRunnerResults

◆ FPostTuning

◆ FPreTuning

Member Function Documentation

◆ Clone()

◆ GenerateMeasureCandidates()

◆ InitializeWithTuneContext()

◆ NotifyRunnerResults()

◆ PostTuning()

◆ PreTuning()

◆ RegisterReflection()

◆ TVM_DECLARE_FINAL_OBJECT_INFO()

Member Data Documentation

◆ _type_key

◆ f_clone

◆ f_generate_measure_candidates

◆ f_initialize_with_tune_context

◆ f_notify_runner_results

◆ f_post_tuning

◆ f_pre_tuning