mlos_bench.storage.base_tunable_config_trial_group_data

Base interface for accessing the stored benchmark config trial group data.

Since a single config may be used by multiple trials, we can group them together for easier analysis.

Classes

TunableConfigTrialGroupData

Base interface for accessing the stored experiment benchmark tunable config trial

Module Contents

class mlos_bench.storage.base_tunable_config_trial_group_data.TunableConfigTrialGroupData(*, experiment_id: str, tunable_config_id: int, tunable_config_trial_group_id: int | None = None)[source]

Base interface for accessing the stored experiment benchmark tunable config trial group data.

A (tunable) config is used to define an instance of values for a set of tunable parameters for a given experiment and can be used by one or more trial instances (e.g., for repeats), which we call a (tunable) config trial group.

Parameters:

experiment_id (str)
tunable_config_id (int)
tunable_config_trial_group_id (Optional[int])

__eq__(other: Any) → bool[source]

Parameters:: other (Any)
Return type:: bool

__repr__() → str[source]

Return type:: str

property experiment_id: str[source]

ID of the experiment.

Return type:: str

property results_df: pandas.DataFrame[source]

Abstractmethod:
Return type:: pandas.DataFrame

Retrieve all results for this (tunable) config trial group as a single DataFrame.

Returns:: results – A DataFrame with configurations and results from all trials of the experiment. Has columns [trial_id, config_id, ts_start, ts_end, status] followed by tunable config parameters (prefixed with “config.”) and trial results (prefixed with “result.”). The latter can be NULLs if the trial was not successful.
Return type:: pandas.DataFrame