deephyper.stopper.ConstantStopper#

class deephyper.stopper.ConstantStopper(max_steps: int, stop_step: int)[source]#

Bases: deephyper.stopper._stopper.Stopper

Constant stopping policy which will stop the evaluation of a configuration at a fixed step.

Parameters

max_steps (int) – the maximum number of steps which should be performed to evaluate the configuration fully.
stop_step (int) – the step at which to stop the evaluation.

Methods

`observe`	Observe a new objective value.
`stop`	Returns `True` if the evaluation should be stopped and `False` otherwise.
`to_json`	Returns a dict version of the stopper which can be saved as JSON.
`transform_objective`	Replaces the currently observed objective by the maximum objective observed from the start.

Attributes

`objective`	Last observed objective.
`observations`	Returns a copy of the list of observations with 0-index the budgets and 1-index the objectives.
`step`	Last observed step.

property observations#: Returns a copy of the list of observations with 0-index the budgets and 1-index the objectives.

observe(budget: float, objective: float) → None #

Observe a new objective value.

Parameters

budget (float) – the budget used to obtain the objective (e.g., the number of epochs).
objective (float) – the objective value to observe (e.g, the accuracy).

stop() → bool [source]#

Returns True if the evaluation should be stopped and False otherwise.

to_json()#: Returns a dict version of the stopper which can be saved as JSON.

transform_objective(objective: float)#: Replaces the currently observed objective by the maximum objective observed from the start. Identity transformation by default.