Managed reference to SearchStrategyNode.
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#include <search_strategy.h>
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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. More...
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static SearchStrategy | ReplayTrace (int max_fail_count) |
| Constructor of replay trace search strategy. More...
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static SearchStrategy | ReplayFunc () |
| Constructor of replay func search strategy. More...
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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. More...
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◆ FClone
The function type of Clone
method.
- Returns
- The cloned search strategy.
◆ FGenerateMeasureCandidates
The function type of GenerateMeasureCandidates
method.
- Returns
- The measure candidates generated, nullptr if finished.
◆ FInitializeWithTuneContext
The function type of InitializeWithTuneContext
method.
- Parameters
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context | The tuning context for initialization. |
◆ FNotifyRunnerResults
The function type of NotifyRunnerResults
method.
- Parameters
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results | The measurement results from the runner. |
◆ FPostTuning
The function type of PostTuning
method.
◆ FPreTuning
The function type of PreTuning
method.
◆ EvolutionarySearch()
static SearchStrategy tvm::meta_schedule::SearchStrategy::EvolutionarySearch |
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int |
population_size, |
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double |
init_measured_ratio, |
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int |
init_min_unmeasured, |
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int |
max_fail_count, |
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int |
genetic_num_iters, |
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double |
genetic_mutate_prob, |
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int |
genetic_max_fail_count, |
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double |
eps_greedy |
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Constructor of evolutionary search strategy.
- Parameters
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population_size | The initial sample population. |
init_measured_ratio | The ratio of measures samples in initial population. |
init_min_unmeasured | The minimal size of unmeasured population in the initial sampling. |
max_fail_count | The max number of failure during initial sampling. |
genetic_num_iters | The iterations to run the genetic algorithm. |
genetic_mutate_prob | The probability of mutation. |
genetic_max_fail_count | The maximum number to try evolving the given trace. |
eps_greedy | The ratio to select samples in a greedy fashion via their predicted score. |
◆ PySearchStrategy()
Create a search strategy with customized methods on the python-side.
- Parameters
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f_initialize_with_tune_context | The packed function of InitializeWithTuneContext . |
f_pre_tuning | The packed function of PreTuning . |
f_post_tuning | The packed function of PostTuning . |
f_generate_measure_candidates | The packed function of GenerateMeasureCandidates . |
f_notify_runner_results | The packed function of NotifyRunnerResults . |
f_clone | The packed function of Clone . |
- Returns
- The search strategy created.
◆ ReplayFunc()
static SearchStrategy tvm::meta_schedule::SearchStrategy::ReplayFunc |
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Constructor of replay func search strategy.
◆ ReplayTrace()
static SearchStrategy tvm::meta_schedule::SearchStrategy::ReplayTrace |
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int |
max_fail_count | ) |
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Constructor of replay trace search strategy.
- Parameters
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max_fail_count | The max number of failures during trace replaying. |
◆ TVM_DEFINE_MUTABLE_OBJECT_REF_METHODS()
The documentation for this class was generated from the following file: