def test_autoai_libs_t_no_op(self): from lightgbm import LGBMClassifier from lale.lib.autoai_libs import TNoOp from lale.operators import make_pipeline t_no_op = TNoOp( fun="fun", name="no_action", datatypes="x", feat_constraints=[], tgraph="tgraph", ) lgbm_classifier = LGBMClassifier(class_weight="balanced", learning_rate=0.18) pipeline = make_pipeline(t_no_op, lgbm_classifier) expected = """from autoai_libs.cognito.transforms.transform_utils import TNoOp from lightgbm import LGBMClassifier from lale.operators import make_pipeline t_no_op = TNoOp( fun="fun", name="no_action", datatypes="x", feat_constraints=[], tgraph="tgraph", ) lgbm_classifier = LGBMClassifier( class_weight="balanced", learning_rate=0.18, n_estimators=100 ) pipeline = make_pipeline(t_no_op, lgbm_classifier)""" self._roundtrip( expected, lale.pretty_print.to_string(pipeline, combinators=False) )
def test_autoai_libs_t_no_op(self): from lale.lib.autoai_libs import TNoOp from lightgbm import LGBMClassifier from lale.operators import make_pipeline t_no_op = TNoOp(name='no_action', datatypes='x', feat_constraints=[]) lgbm_classifier = LGBMClassifier(class_weight='balanced', learning_rate=0.18) pipeline = make_pipeline(t_no_op, lgbm_classifier) expected = \ """from lale.lib.autoai_libs import TNoOp from lightgbm import LGBMClassifier from lale.operators import make_pipeline t_no_op = TNoOp(name='no_action', datatypes='x', feat_constraints=[]) lgbm_classifier = LGBMClassifier(class_weight='balanced', learning_rate=0.18) pipeline = make_pipeline(t_no_op, lgbm_classifier)""" self._roundtrip(expected, lale.pretty_print.to_string(pipeline, combinators=False))