Primary algorithm¶
TODO
Sanitizing wrapper of main algorithm¶
Performs checks and organizes required transformations of points.
- class orion.core.worker.primary_algo.SpaceTransformAlgoWrapper(space: Space, algorithm: AlgoT)[source]¶
Perform checks on points and transformations. Wrap the primary algorithm.
1. Checks requirements on the parameter space from algorithms and create the appropriate transformations. Apply transformations before and after methods of the primary algorithm. 2. Checks whether incoming and outcoming points are compliant with a space.
- Parameters
- algorithm: instance of `BaseAlgorithm`
Algorithm to be wrapped.
- space
orion.algo.space.Space
The original definition of a problem’s parameters space.
- algorithm_configdict
Configuration for the algorithm.
- Attributes
configuration
Return tunable elements of this algorithm in a dictionary form appropriate for saving.
fidelity_index
Compute the index of the space where fidelity is.
is_done
Return True if the wrapper or the wrapped algorithm is done.
n_observed
Number of completed trials observed by the algorithm.
n_suggested
Number of trials suggested by the algorithm
original_space
The original space (before transformations).
space
Domain of problem associated with this algorithm’s instance.
state_dict
Return a state dict that can be used to reset the state of the algorithm.
transformed_space
The transformed space (after transformations).
Methods
has_observed
(trial)Whether the algorithm has observed a given trial.
has_suggested
(trial)Whether the algorithm has suggested a given trial.
judge
(trial, measurements)Inform an algorithm about online measurements of a running trial.
observe
(trials)Observe evaluated trials.
score
(trial)Allow algorithm to evaluate point based on a prediction about this parameter set's performance.
seed_rng
(seed)Seed the state of the algorithm's random number generator.
set_state
(state_dict)Reset the state of the algorithm based on the given state_dict
should_suspend
(trial)Allow algorithm to decide whether a particular running trial is still worth to complete its evaluation, based on information provided by the
judge
method.suggest
(num)Suggest a num of new sets of parameters.
- property configuration: dict¶
Return tunable elements of this algorithm in a dictionary form appropriate for saving.
- property fidelity_index: str | None¶
Compute the index of the space where fidelity is.
Returns None if there is no fidelity dimension.
- judge(trial: Trial, measurements: Any) dict | None [source]¶
Inform an algorithm about online measurements of a running trial.
The algorithm can return a dictionary of data which will be provided as a response to the running environment. Default is None response.
- property original_space: Space¶
The original space (before transformations). This is exposed to the outside, but not to the wrapped algorithm.
- score(trial: Trial) float [source]¶
Allow algorithm to evaluate point based on a prediction about this parameter set’s performance. Return a subjective measure of expected performance.
By default, return the same score any parameter (no preference).
- seed_rng(seed: int | Sequence[int] | None) None [source]¶
Seed the state of the algorithm’s random number generator.
- set_state(state_dict: dict) None [source]¶
Reset the state of the algorithm based on the given state_dict
- Parameters
state_dict – Dictionary representing state of an algorithm
- should_suspend(trial: Trial) bool [source]¶
Allow algorithm to decide whether a particular running trial is still worth to complete its evaluation, based on information provided by the
judge
method.
- property space: Space¶
Domain of problem associated with this algorithm’s instance.
Note
Redefining property here without setter, denies base class’ setter.
- property state_dict: dict¶
Return a state dict that can be used to reset the state of the algorithm.
- suggest(num: int) list[Trial] [source]¶
Suggest a num of new sets of parameters.
- Parameters
- num: int
Number of trials to suggest. The algorithm may return less than the number of trials requested.
- Returns
- list of trials
A list of trials representing values suggested by the algorithm. The algorithm may opt out if it cannot make a good suggestion at the moment (it may be waiting for other trials to complete), in which case it will return an empty list.
Notes
New parameters must be compliant with the problem’s domain
orion.algo.space.Space
.
- property transformed_space: TransformedSpace¶
The transformed space (after transformations). This is only exposed to the wrapped algo, not to classes outside of this.
- orion.core.worker.primary_algo.create_algo(algo_type: type[AlgoT], space: Space, **algo_kwargs) SpaceTransformAlgoWrapper[AlgoT] [source]¶
Creates an algorithm of the given type, taking care of transforming the space if needed.
- orion.core.worker.primary_algo.get_original_parent(registry: Registry, transformed_space: TransformedSpace, trial_parent_id: str) Trial [source]¶
Get the parent trial in original space based on parent id in transformed_space.
If the parent trial also has a parent, then this function is called recursively to set the proper parent id in original space rather than transformed space.