hyperparameter_hunter.callbacks package

Subpackages

• hyperparameter_hunter.callbacks.wranglers package
  • Submodules
  • hyperparameter_hunter.callbacks.wranglers.input_wranglers module
  • hyperparameter_hunter.callbacks.wranglers.predictors module
  • hyperparameter_hunter.callbacks.wranglers.target_wranglers module
  • Module contents
    • Related

Submodules

hyperparameter_hunter.callbacks.aggregators module

class hyperparameter_hunter.callbacks.aggregators.AggregatorTimes

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

stat_aggregates: dict

on_exp_start()

Perform tasks when an Experiment is started

on_rep_start()

Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme

on_fold_start()

Perform tasks on fold start in an Experiment’s cross-validation scheme

on_run_start()

Perform tasks on run start in an Experiment’s multiple-run-averaging phase

on_run_end()

Perform tasks on run end in an Experiment’s multiple-run-averaging phase

on_fold_end()

Perform tasks on fold end in an Experiment’s cross-validation scheme

on_rep_end()

Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme

on_exp_end()

Perform tasks when an Experiment ends

class hyperparameter_hunter.callbacks.aggregators.AggregatorEvaluations

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

stat_aggregates: dict

last_evaluation_results: dict

on_run_end()

Perform tasks on run end in an Experiment’s multiple-run-averaging phase

on_fold_end()

Perform tasks on fold end in an Experiment’s cross-validation scheme

on_rep_end()

Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme

on_exp_end()

Perform tasks when an Experiment ends

class hyperparameter_hunter.callbacks.aggregators.AggregatorOOF

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.aggregators.AggregatorHoldout

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.aggregators.AggregatorTest

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.aggregators.AggregatorLosses

Bases: hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

hyperparameter_hunter.callbacks.bases module

This module defines the base callback classes, from which all other callback classes in hyperparameter_hunter.callbacks are descendants. Importantly, the specific base callback classes contained herein are all descendants of hyperparameter_hunter.callbacks.bases.BaseCallback, ensuring all callbacks descend from the same base class. This module also defines hyperparameter_hunter.callbacks.bases.lambda_callback(), which can be used to define custom callbacks to be executed during Experiments when passed to hyperparameter_hunter.environment.Environment.__init__() via the experiment_callbacks argument

Related

hyperparameter_hunter.callbacks

The rest of the submodules within this module should define classes which all descend from the base callback classes defined in hyperparameter_hunter.callbacks.bases

hyperparameter_hunter.experiment_core

This is where callback classes are added as bases inherited by hyperparameter_hunter.experiments.BaseExperiment. This module is the path that links hyperparameter_hunter.callbacks to hyperparameter_hunter.experiments

hyperparameter_hunter.environment

This module provides the means to use custom callbacks made by hyperparameter_hunter.callbacks.bases.lambda_callback() through the experiment_callbacks argument of hyperparameter_hunter.environment.Environment.__init__()

class hyperparameter_hunter.callbacks.bases.BaseCallback

Bases: object

The base class from which all callbacks and all intermediate base callbacks are descendants. Callback classes’ __init__() will not be called, so any tasks that must be performed at the onset of an experiment should be placed in on_exp_start()

Notes

__init__(): Some classes that inherit BaseCallback may implement __init__(); however, callback classes are NEVER INITIALIZED. Callback classes should be regarded as extensions to the Experiment class that is inheriting them. Because they are inherited, callback classes have access to all attributes of the inheriting Experiment class. If any callback class does implement __init__(), it is simply a convention to clearly declare the attributes required by the other methods of that callback class. Again, __init__() of classes that inherit BaseCallback will not be called

The methods below each call settings.G.debug() to signal that the dynamic callback inheritance organized in experiment_core.ExperimentMeta has proceeded at least partially successfully. If all callback methods end by executing the method of the same name in their parent classes, then the below debug messages should be visible in the “Heartbeat.log” file. Conversely, if any of the below debug messages are not printed to “Heartbeat.log”, it is likely that a callback class’s implementation of the corresponding method does not end with “super().<method_name>()”. Such cases should be remedied immediately, as the callback stream could be skipping any number of other callbacks

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

on_exp_start()

Perform tasks when an Experiment is started

on_exp_end()

Perform tasks when an Experiment ends

on_rep_start()

Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme

on_rep_end()

Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme

on_fold_start()

Perform tasks on fold start in an Experiment’s cross-validation scheme

on_fold_end()

Perform tasks on fold end in an Experiment’s cross-validation scheme

on_run_start()

Perform tasks on run start in an Experiment’s multiple-run-averaging phase

on_run_end()

Perform tasks on run end in an Experiment’s multiple-run-averaging phase

hyperparameter_hunter.callbacks.bases.lambda_callback(on_exp_start=None, on_exp_end=None, on_rep_start=None, on_rep_end=None, on_fold_start=None, on_fold_end=None, on_run_start=None, on_run_end=None, agg_name=None, do_reshape_aggs=True, method_agg_keys=False, on_experiment_start=<object object>, on_experiment_end=<object object>, on_repetition_start=<object object>, on_repetition_end=<object object>)

Utility for creating custom callbacks to be declared by Environment and used by Experiments. The callable “on_<…>_<start/end>” parameters provided will receive as input whichever attributes of the Experiment are included in the signature of the given callable. If **kwargs is given in the callable’s signature, a dict of all of the Experiment’s attributes will be provided. This can be helpful for trying to figure out how to build a custom callback, but should not be used unless absolutely necessary. If the Experiment does not have an attribute specified in the callable’s signature, the following placeholder will be given: “INVALID KWARG”

Parameters

on_exp_start: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at Experiment start

on_exp_end: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at Experiment end

on_rep_start: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at repetition start

on_rep_end: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at repetition end

on_fold_start: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at fold start

on_fold_end: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at fold end

on_run_start: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at run start

on_run_end: Callable, or None, default=None

Callable that receives Experiment’s values for parameters in the signature at run end

agg_name: Str, default=uuid.uuid4

This parameter is only used if the callables are behaving like AggregatorCallbacks by returning values (see the “Notes” section below for details on this). If the callables do return values, they will be stored under a key named (“_” + agg_name) in a dict in hyperparameter_hunter.experiments.BaseExperiment.stat_aggregates. The purpose of this parameter is to make it easier to understand an Experiment’s description file, as agg_name will default to a UUID if it is not given

do_reshape_aggs: Boolean, default=True

Whether to reshape the aggregated values to reflect the nested repetitions/folds/runs structure used for other aggregated values. If False, lists of aggregated values are left in their original shapes. This parameter is only used if the callables are behaving like AggregatorCallbacks (see the “Notes” section below and agg_name for details on this)

method_agg_keys: Boolean, default=False

If True, the aggregate keys for the items added to the dict at agg_name are equivalent to the names of the “on_<…>_<start/end>” pseudo-methods whose values are being aggregated. In other words, the pool of all possible aggregate keys goes from [“runs”, “folds”, “reps”, “final”] to the names of the eight “on_<…>_<start/end>” kwargs of lambda_callback(). See the “Notes” section below for further details and a rough outline

on_experiment_start: …

Deprecated since version 3.0.0: Renamed to on_exp_start. Will be removed in 3.2.0

on_experiment_end: …

Deprecated since version 3.0.0: Renamed to on_exp_end. Will be removed in 3.2.0

on_repetition_start: …

Deprecated since version 3.0.0: Renamed to on_rep_start. Will be removed in 3.2.0

on_repetition_end: …

Deprecated since version 3.0.0: Renamed to on_rep_end. Will be removed in 3.2.0

Returns

LambdaCallback: LambdaCallback

Uninitialized class, whose methods are the callables of the corresponding “on…” kwarg

Notes

For all of the “on_<…>_<start/end>” callables provided as input to lambda_callback, consider the following guidelines (for example function “f”, which can represent any of the callables):

• All input parameters in the signature of “f” are attributes of the Experiment being executed

  • If “**kwargs” is a parameter, a dict of all the Experiment’s attributes will be provided

• “f” will be treated as a method of a parent class of the Experiment

  • Take care when modifying attributes, as changes are reflected in the Experiment itself

• If “f” returns something, it will automatically behave like an AggregatorCallback (see hyperparameter_hunter.callbacks.aggregators). Specifically, the following will occur:

  • A new key (named by agg_name if given, else a UUID) with a dict value is added to hyperparameter_hunter.experiments.BaseExperiment.stat_aggregates

    • This new dict can have up to four keys: “runs” (list), “folds” (list), “reps” (list), and “final” (object)

  • If “f” is an “on_run…” function, the returned value is appended to the “runs” list in the new dict

  • Similarly, if “f” is an “on_fold…” or “on_rep…” function, the returned value is appended to the “folds”, or “reps” list, respectively

  • If “f” is an “on_exp…” function, the “final” key in the new dict is set to the returned value

  • If values were aggregated in the aforementioned manner, the lists of collected values will be reshaped according to runs/folds/reps on Experiment end

  • The aggregated values will be saved in the Experiment’s description file

    • This is because hyperparameter_hunter.experiments.BaseExperiment.stat_aggregates is saved in its entirety

What follows is a rough outline of the structure produced when using an aggregator-like callback that automatically populates experiments.BaseExperiment.stat_aggregates with results of the functions used as arguments to lambda_callback():

BaseExperiment.stat_aggregates = dict(
    ...,
    <`agg_name`>=dict(
        <agg_key "runs">  = [...],
        <agg_key "folds"> = [...],
        <agg_key "reps">  = [...],
        <agg_key "final"> = object(),
        ...
    ),
    ...
)

In the above outline, the actual agg_key`s included in the dict at `agg_name depend on which “on_<…>_<start/end>” callables are behaving like aggregators. For example, if neither on_run_start nor on_run_end explicitly returns something, then the “runs” agg_key is not included in the agg_name dict. Similarly, if, for example, neither on_exp_start nor on_exp_end is provided, then the “final” agg_key is not included. If method_agg_keys=True, then the agg keys used in the dict are modified to be named after the method called. For example, if method_agg_keys=True and on_fold_start and on_fold_end are both callables returning values to be aggregated, then the agg_key`s used for each will be “on_fold_start” and “on_fold_end”, respectively. In this example, if `method_agg_keys=False (default) and do_reshape_aggs=False, then the single “folds” agg_key would contain the combined contents returned by both methods in the order in which they were returned

For examples using lambda_callback to create custom callbacks, see hyperparameter_hunter.callbacks.recipes

Examples

>>> from hyperparameter_hunter.environment import Environment
>>> def printer_helper(_rep, _fold, _run, last_evaluation_results):
...     print(f"{_rep}.{_fold}.{_run}   {last_evaluation_results}")
>>> my_lambda_callback = lambda_callback(
...     on_exp_end=printer_helper,
...     on_rep_end=printer_helper,
...     on_fold_end=printer_helper,
...     on_run_end=printer_helper,
... )
... # env = Environment(
... #     train_dataset="i am a dataset",
... #     results_path="path/to/HyperparameterHunterAssets",
... #     metrics=["roc_auc_score"],
... #     experiment_callbacks=[my_lambda_callback]
... # )
... # ... Now execute an Experiment, or an Optimization Protocol...

See hyperparameter_hunter.examples.lambda_callback_example for more information

class hyperparameter_hunter.callbacks.bases.BaseWranglerCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseCallback

Base class from which all callbacks in hyperparameter_hunter.callbacks.wranglers are descendants

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BaseInputWranglerCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseWranglerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BaseTargetWranglerCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseWranglerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BasePredictorCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseWranglerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseCallback

Base class from which all callbacks in hyperparameter_hunter.callbacks.loggers are descendants

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BaseAggregatorCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseCallback

Base class from which all callbacks in hyperparameter_hunter.callbacks.aggregators are descendants

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.bases.BaseEvaluatorCallback

Bases: hyperparameter_hunter.callbacks.bases.BaseCallback

Base class from which all callbacks in hyperparameter_hunter.callbacks.evaluators are descendants

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

hyperparameter_hunter.callbacks.evaluators module

hyperparameter_hunter.callbacks.loggers module

class hyperparameter_hunter.callbacks.loggers.LoggerFitStatus

Bases: hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

stat_aggregates: dict

last_evaluation_results: dict

current_seed: int

float_format = '{:.5f}'

log_separator = ' | '

on_exp_start()

Perform tasks when an Experiment is started

on_rep_start()

Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme

on_fold_start()

Perform tasks on fold start in an Experiment’s cross-validation scheme

on_run_start()

Perform tasks on run start in an Experiment’s multiple-run-averaging phase

on_run_end()

Perform tasks on run end in an Experiment’s multiple-run-averaging phase

on_fold_end()

Perform tasks on fold end in an Experiment’s cross-validation scheme

on_rep_end()

Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme

on_exp_end()

Perform tasks when an Experiment ends

class hyperparameter_hunter.callbacks.loggers.LoggerOOF

Bases: hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.loggers.LoggerHoldout

Bases: hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.loggers.LoggerTest

Bases: hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

class hyperparameter_hunter.callbacks.loggers.LoggerEvaluation

Bases: hyperparameter_hunter.callbacks.bases.BaseLoggerCallback

Methods

on_exp_end()	Perform tasks when an Experiment ends
on_exp_start()	Perform tasks when an Experiment is started
on_fold_end()	Perform tasks on fold end in an Experiment’s cross-validation scheme
on_fold_start()	Perform tasks on fold start in an Experiment’s cross-validation scheme
on_rep_end()	Perform tasks on repetition end in an Experiment’s repeated cross-validation scheme
on_rep_start()	Perform tasks on repetition start in an Experiment’s repeated cross-validation scheme
on_run_end()	Perform tasks on run end in an Experiment’s multiple-run-averaging phase
on_run_start()	Perform tasks on run start in an Experiment’s multiple-run-averaging phase

hyperparameter_hunter.callbacks.recipes module

Module contents