tvm
search_strategy.h
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19 #ifndef TVM_META_SCHEDULE_SEARCH_STRATEGY_H_
20 #define TVM_META_SCHEDULE_SEARCH_STRATEGY_H_
21 
22 #include <tvm/ffi/container/array.h>
23 #include <tvm/ffi/function.h>
24 #include <tvm/ffi/optional.h>
25 #include <tvm/ffi/reflection/registry.h>
31 #include <tvm/runtime/object.h>
33 
34 namespace tvm {
35 namespace meta_schedule {
36 
37 // Forward declaration
38 class TuneContext;
39 class SearchStrategy;
40 
77 class SearchStrategyNode : public runtime::Object {
78  public:
80  virtual ~SearchStrategyNode() = default;
81 
87  virtual void InitializeWithTuneContext(const TuneContext& context) = 0;
88 
100  virtual void PreTuning(int max_trials, int num_trials_per_iter,
101  const Array<tir::Schedule>& design_spaces,
102  const Optional<Database>& database,
103  const Optional<CostModel>& cost_model) = 0;
104 
110  virtual void PostTuning() = 0;
111 
116  virtual Optional<Array<MeasureCandidate>> GenerateMeasureCandidates() = 0;
117 
123  virtual void NotifyRunnerResults(const Array<MeasureCandidate>& measure_candidates,
124  const Array<RunnerResult>& results) = 0;
125 
130  virtual SearchStrategy Clone() const = 0;
131 
132  static constexpr const char* _type_key = "meta_schedule.SearchStrategy";
134 };
135 
140 class SearchStrategy : public runtime::ObjectRef {
141  public:
146  using FInitializeWithTuneContext = ffi::TypedFunction<void(const TuneContext&)>;
150  using FPreTuning =
151  ffi::TypedFunction<void(int max_trials, int num_trials_per_iter, const Array<tir::Schedule>&,
152  const Optional<Database>&, const Optional<CostModel>&)>;
154  using FPostTuning = ffi::TypedFunction<void()>;
159  using FGenerateMeasureCandidates = ffi::TypedFunction<Optional<Array<MeasureCandidate>>()>;
165  ffi::TypedFunction<void(const Array<MeasureCandidate>&, const Array<RunnerResult>&)>;
170  using FClone = ffi::TypedFunction<SearchStrategy()>;
182  FInitializeWithTuneContext f_initialize_with_tune_context, //
183  FPreTuning f_pre_tuning, //
184  FPostTuning f_post_tuning, //
185  FGenerateMeasureCandidates f_generate_measure_candidates, //
186  FNotifyRunnerResults f_notify_runner_results, //
187  FClone f_clone);
188 
193  TVM_DLL static SearchStrategy ReplayTrace(int max_fail_count);
194 
196  TVM_DLL static SearchStrategy ReplayFunc();
197 
209  TVM_DLL static SearchStrategy EvolutionarySearch(int population_size, //
210  double init_measured_ratio, //
211  int init_min_unmeasured, //
212  int max_fail_count, //
213  int genetic_num_iters, //
214  double genetic_mutate_prob, //
215  int genetic_max_fail_count, //
216  double eps_greedy);
217 
219 };
220 
223  public:
230 
243 
244  static void RegisterReflection() {
245  // `f_initialize_with_tune_context` is not registered
246  // `f_pre_tuning` is not registered
247  // `f_post_tuning` is not registered
248  // `f_generate_measure_candidates` is not registered
249  // `f_notify_runner_results` is not registered
250  // `f_clone` is not registered
251  }
252 
253  void InitializeWithTuneContext(const TuneContext& context) final;
254  void PreTuning(int max_trials, int num_trials_per_iter, const Array<tir::Schedule>& design_spaces,
255  const Optional<Database>& database, const Optional<CostModel>& cost_model) final;
256  void PostTuning() final;
257  Optional<Array<MeasureCandidate>> GenerateMeasureCandidates() final;
258  void NotifyRunnerResults(const Array<MeasureCandidate>& measure_candidates,
259  const Array<RunnerResult>& results);
260  SearchStrategy Clone() const final;
261 
262  static constexpr const char* _type_key = "meta_schedule.PySearchStrategy";
264 };
265 
266 } // namespace meta_schedule
267 } // namespace tvm
268 
269 #endif // TVM_META_SCHEDULE_SEARCH_STRATEGY_H_
Managed reference to MeasureCandidateNode.
Definition: measure_candidate.h:55
The python side customizable class for measure candidate generation.
Definition: search_strategy.h:222
TVM_DECLARE_FINAL_OBJECT_INFO(PySearchStrategyNode, SearchStrategyNode)
FClone f_clone
The packed function to the Clone method.
Definition: search_strategy.h:242
void PostTuning() final
Post-tuning for the search strategy.
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.
FPostTuning f_post_tuning
The packed function to the PostTuning method.
Definition: search_strategy.h:236
FInitializeWithTuneContext f_initialize_with_tune_context
The packed function to the InitializeWithTuneContext method.
Definition: search_strategy.h:232
FGenerateMeasureCandidates f_generate_measure_candidates
The packed function to the GenerateMeasureCandidates method.
Definition: search_strategy.h:238
SearchStrategy::FNotifyRunnerResults FNotifyRunnerResults
Definition: search_strategy.h:228
SearchStrategy::FInitializeWithTuneContext FInitializeWithTuneContext
Definition: search_strategy.h:224
void NotifyRunnerResults(const Array< MeasureCandidate > &measure_candidates, const Array< RunnerResult > &results)
Update the search strategy with measurement results.
SearchStrategy::FPreTuning FPreTuning
Definition: search_strategy.h:225
static void RegisterReflection()
Definition: search_strategy.h:244
SearchStrategy::FPostTuning FPostTuning
Definition: search_strategy.h:226
FNotifyRunnerResults f_notify_runner_results
The packed function to the NotifyRunnerResults method.
Definition: search_strategy.h:240
static constexpr const char * _type_key
Definition: search_strategy.h:262
Optional< Array< MeasureCandidate > > GenerateMeasureCandidates() final
Generate measure candidates from design spaces for measurement.
FPreTuning f_pre_tuning
The packed function to the PreTuning method.
Definition: search_strategy.h:234
SearchStrategy Clone() const final
Clone the search strategy.
SearchStrategy::FClone FClone
Definition: search_strategy.h:229
SearchStrategy::FGenerateMeasureCandidates FGenerateMeasureCandidates
Definition: search_strategy.h:227
void InitializeWithTuneContext(const TuneContext &context) final
Initialize the search strategy with tuning context.
Managed reference to RunnerResultNode.
Definition: runner.h:97
The search strategy for measure candidates generation.
Definition: search_strategy.h:77
static constexpr const char * _type_key
Definition: search_strategy.h:132
virtual void NotifyRunnerResults(const Array< MeasureCandidate > &measure_candidates, const Array< RunnerResult > &results)=0
Update the search strategy with measurement results.
TVM_DECLARE_BASE_OBJECT_INFO(SearchStrategyNode, Object)
virtual 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)=0
Pre-tuning for the search strategy.
virtual void InitializeWithTuneContext(const TuneContext &context)=0
Initialize the search strategy with tuning context.
virtual Optional< Array< MeasureCandidate > > GenerateMeasureCandidates()=0
Generate measure candidates from design spaces for measurement.
virtual void PostTuning()=0
Post-tuning for the search strategy.
virtual ~SearchStrategyNode()=default
Virtual destructor.
virtual SearchStrategy Clone() const =0
Clone the search strategy.
Managed reference to SearchStrategyNode.
Definition: search_strategy.h:140
static SearchStrategy ReplayTrace(int max_fail_count)
Constructor of replay trace search strategy.
static SearchStrategy ReplayFunc()
Constructor of replay func search strategy.
TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS(SearchStrategy, ObjectRef, SearchStrategyNode)
static SearchStrategy PySearchStrategy(FInitializeWithTuneContext f_initialize_with_tune_context, FPreTuning f_pre_tuning, FPostTuning f_post_tuning, FGenerateMeasureCandidates f_generate_measure_candidates, FNotifyRunnerResults f_notify_runner_results, FClone f_clone)
Create a search strategy with customized methods on the python-side.
ffi::TypedFunction< SearchStrategy()> FClone
The function type of Clone method.
Definition: search_strategy.h:170
ffi::TypedFunction< void(const TuneContext &)> FInitializeWithTuneContext
The function type of InitializeWithTuneContext method.
Definition: search_strategy.h:146
static SearchStrategy EvolutionarySearch(int population_size, double init_measured_ratio, int init_min_unmeasured, int max_fail_count, int genetic_num_iters, double genetic_mutate_prob, int genetic_max_fail_count, double eps_greedy)
Constructor of evolutionary search strategy.
ffi::TypedFunction< void(const Array< MeasureCandidate > &, const Array< RunnerResult > &)> FNotifyRunnerResults
The function type of NotifyRunnerResults method.
Definition: search_strategy.h:165
ffi::TypedFunction< Optional< Array< MeasureCandidate > >()> FGenerateMeasureCandidates
The function type of GenerateMeasureCandidates method.
Definition: search_strategy.h:159
ffi::TypedFunction< void()> FPostTuning
The function type of PostTuning method.
Definition: search_strategy.h:154
ffi::TypedFunction< void(int max_trials, int num_trials_per_iter, const Array< tir::Schedule > &, const Optional< Database > &, const Optional< CostModel > &)> FPreTuning
The function type of PreTuning method.
Definition: search_strategy.h:152
Managed reference to TuneContextNode.
Definition: tune_context.h:98
Performance counters for profiling via the PAPI library.
Definition: analyzer.h:37
A managed object in the TVM runtime.