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"""Base class for optimizer.""" |
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from skbase.base import BaseObject |
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class BaseOptimizer(BaseObject): |
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"""Base class for optimizer.""" |
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_search_config_names = [] |
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def __init__(self): |
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super().__init__() |
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assert hasattr(self, "experiment"), "Optimizer must have an experiment." |
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search_config = self.get_params() |
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self._experiment = search_config.pop("experiment", None) |
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def add_search(self, experiment, **search_config): |
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"""Add a new optimization search process with specified parameters. |
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Parameters |
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---------- |
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experiment : BaseExperiment |
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The experiment to optimize parameters for. |
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search_config : dict with str keys |
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The search configuration dictionary. |
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""" |
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self._experiment = experiment |
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if not hasattr(self, "_search_config_update"): |
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self._search_config_update = search_config |
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else: |
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self._search_config_update.update(search_config) |
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def get_search_config(self): |
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"""Get the search configuration. |
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Returns |
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------- |
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dict with str keys |
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The search configuration dictionary. |
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""" |
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search_config = self.get_params(deep=False) |
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search_config.pop("experiment", None) |
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if hasattr(self, "_search_config_update"): |
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search_config.update(self._search_config_update) |
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return search_config |
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def get_experiment(self): |
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"""Get the experiment. |
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Returns |
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------- |
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BaseExperiment |
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The experiment to optimize parameters for. |
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""" |
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return self._experiment |
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def run(self): |
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"""Run the optimization search process. |
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Returns |
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------- |
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best_params : dict |
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The best parameters found during the optimization process. |
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""" |
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experiment = self.get_experiment() |
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search_config = self.get_search_config() |
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return self._run(experiment, **search_config) |
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SimonBlanke /
Hyperactive
