deephyper.search.nas.NeuralArchitectureSearch#

class deephyper.search.nas.NeuralArchitectureSearch(problem, evaluator, random_state=None, log_dir='.', verbose=0, **kwargs)[source]#

Bases: Search

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.