deephyper.search
The search module brings a modular way to implement new search algorithms and two sub modules. One is for hyperparameter search deephyper.search.hps and one is for neural architecture search deephyper.search.nas.
The Search class is abstract and has different subclasses such as: deephyper.search.ambs and deephyper.search.ga.
-
class
deephyper.search.Search(problem, evaluator, random_state=None, log_dir='.', verbose=0, **kwargs)[source]
Bases: abc.ABC
Abstract class which represents a search algorithm.
- Parameters
problem ([type]) – [description]
evaluator ([type]) – [description]
random_state ([type], optional) – [description]. Defaults to None.
log_dir (str, optional) – [description]. Defaults to “.”.
verbose (int, optional) – [description]. Defaults to 0.
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search(max_evals: int = - 1, timeout: Optional[int] = None)[source]
Execute the search algorithm.
- Parameters
max_evals (int, optional) – The maximum number of evaluations of the run function to perform before stopping the search. Defaults to -1, will run indefinitely.
timeout (int, optional) – The time budget of the search before stopping.Defaults to None, will not impose a time budget.
- Returns
a pandas DataFrame containing the evaluations performed.
- Return type
DataFrame
-
terminate()[source]
Terminate the search.
- Raises
SearchTerminationError – raised when the search is terminated with SIGALARM
