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))