deephyper.search.Search

class deephyper.search.Search(problem, evaluator, random_state=None, log_dir='.', verbose=0, **kwargs)

Bases: 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.

Methods

check_evaluator
dump_context	Dumps the context in the log folder.
search	Execute the search algorithm.
to_json	Returns a json version of the search object.

Attributes

search_id

The identifier of the search used by the evaluator.

dump_context()

Dumps the context in the log folder.

search(max_evals: int = -1, timeout: int | None = None)

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 (in seconds) of the search before stopping. Defaults to None, will not impose a time budget.

Returns:

a pandas DataFrame containing the evaluations performed or None if the search could not evaluate any configuration.

Return type:

DataFrame

property search_id

The identifier of the search used by the evaluator.

to_json()

Returns a json version of the search object.