new_get_models.py

@task
def get_models():
    space1 = Space(model=LogisticRegression, solver="lbfgs", C=Grid(10,20), penalty=Grid("l2","none"))
    space2 = Space(model=RandomForestClassifier, max_samples=Rand(0.8,1), max_depth=RandInt(3,4)).sample(4)
    space = [x.simple_value for x in list(space1+space2)]
    models = []
    for model_params in space:
        model = model_params.pop("model")
        models.append(model(**model_params))
    return models