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add autosampler support

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This commit is contained in:
Joseph Hopfmüller
2024-11-20 23:10:14 +01:00
parent 8d4d0468bd
commit 80e9a3379e
1 changed files with 5 additions and 0 deletions
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5
src/single-core-regen/hypertraining/hypertraining.py
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@@ -6,6 +6,7 @@ import matplotlib.pyplot as plt
import numpy as np import numpy as np
import optuna import optuna
import optunahub
import warnings import warnings
import torch import torch
@@ -110,14 +111,18 @@ class HyperTraining:
return optuna.get_all_study_summaries(storage=self.optuna_settings.storage) return optuna.get_all_study_summaries(storage=self.optuna_settings.storage)
def setup_study(self): def setup_study(self):
module = optunahub.load_module(package="samplers/auto_sampler")
self.study = optuna.create_study( self.study = optuna.create_study(
study_name=self.optuna_settings.study_name, study_name=self.optuna_settings.study_name,
storage=self.optuna_settings.storage, storage=self.optuna_settings.storage,
load_if_exists=True, load_if_exists=True,
direction=self.optuna_settings.direction, direction=self.optuna_settings.direction,
directions=self.optuna_settings.directions, directions=self.optuna_settings.directions,
sampler=module.AutoSampler(),
) )
print("using sampler:", self.study.sampler)
with warnings.catch_warnings(action="ignore"): with warnings.catch_warnings(action="ignore"):
self.study.set_metric_names(self.optuna_settings.metrics_names) self.study.set_metric_names(self.optuna_settings.metrics_names)