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"""Loads a hyperparameter optimization object from the getML engine into Python."""
from getml.data import Placeholder
from getml.pipeline import Pipeline
from getml.predictors import LinearRegression
from .hyperopt import (
_get_json_obj,
GaussianHyperparameterSearch,
LatinHypercubeSearch,
RandomSearch
)
[docs]def load_hyperopt(name):
"""Loads a hyperparameter optimization object from the getML engine into Python.
Args:
name: The name of the hyperopt to be loaded.
Returns:
A `~getml.hyperopt.GaussianHyperparameterSearch` that is a handler
for the pipeline signified by name.
"""
# This will be overwritten by .refresh(...) anyway
dummy = Placeholder(name="dummy")
dummy2 = Placeholder(name="dummy2")
dummy.join(dummy2, join_key="join_key")
dummy_pipeline = Pipeline(
population=dummy,
peripheral=dummy2,
predictors=[LinearRegression()]
)
dummy_param_space = {'predictors': [{"reg_lambda": [0.0, 1.0]}]}
json_obj = _get_json_obj(name)
if json_obj["type_"] == "GaussianHyperparameterSearch":
return GaussianHyperparameterSearch(
param_space=dummy_param_space,
pipeline=dummy_pipeline
)._parse_json_obj(json_obj)
if json_obj["type_"] == "LatinHypercubeSearch":
return LatinHypercubeSearch(
param_space=dummy_param_space,
pipeline=dummy_pipeline
)._parse_json_obj(json_obj)
if json_obj["type_"] == "RandomSearch":
return RandomSearch(
param_space=dummy_param_space,
pipeline=dummy_pipeline
)._parse_json_obj(json_obj)
raise ValueError("Unknown type: '" + json_obj["type_"] + "'!")