def test_model_grouping_default_config(sample_metadata):
with testing.postgresql.Postgresql() as postgresql:
engine = create_engine(postgresql.url())
ensure_db(engine)
model_grouper = ModelGrouper()
# get the basic first model group with our default matrix
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
sample_metadata, engine) == 1)
# the end time is not by default a model group key so changing it
# should still get us the same group
metadata_new_end_time = copy(sample_metadata)
metadata_new_end_time["end_time"] = datetime.date(2017, 3, 20)
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
metadata_new_end_time,
engine) == 1)
# max_training_history is a default key,
# so it should trigger a new group
metadata_train_history = copy(sample_metadata)
metadata_train_history["max_training_history"] = "3y"
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
metadata_train_history,
engine) == 2)
# classifier is of course a default key as well
assert (model_grouper.get_model_group_id("module.OtherClassifier",
{"param1": "val1"},
sample_metadata, engine) == 3)
def test_model_grouping_custom_config(sample_metadata):
with testing.postgresql.Postgresql() as postgresql:
engine = create_engine(postgresql.url())
ensure_db(engine)
model_grouper = ModelGrouper(
model_group_keys=["feature_names", "as_of_date_frequency"])
# get the basic first model group with our default matrix
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
sample_metadata, engine) == 1)
# classifier is now not a key, so changing it should not get a new id
assert (model_grouper.get_model_group_id("module.OtherClassifier",
{"param1": "val1"},
sample_metadata, engine) == 1)
# as_of_date_frequency is a key,
# so it should trigger a new group
metadata_frequency = copy(sample_metadata)
metadata_frequency["as_of_date_frequency"] = "2w"
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
metadata_frequency,
engine) == 2)
# testing feature names may seem redundant but it is on a separate
# code path so make sure its logic works
metadata_features = copy(sample_metadata)
metadata_features["feature_names"] = ["ft1", "ft3"]
assert (model_grouper.get_model_group_id("module.Classifier",
{"param1": "val1"},
metadata_features,
engine) == 3)
def test_model_grouping_custom_config(sample_metadata):
with testing.postgresql.Postgresql() as postgresql:
engine = create_engine(postgresql.url())
ensure_db(engine)
model_grouper = ModelGrouper(
model_group_keys=['feature_names', 'as_of_date_frequency'])
# get the basic first model group with our default matrix
assert model_grouper.get_model_group_id('module.Classifier',
{'param1': 'val1'},
sample_metadata, engine) == 1
# classifier is now not a key, so changing it should not get a new id
assert model_grouper.get_model_group_id('module.OtherClassifier',
{'param1': 'val1'},
sample_metadata, engine) == 1
# as_of_date_frequency is a key,
# so it should trigger a new group
metadata_frequency = copy(sample_metadata)
metadata_frequency['as_of_date_frequency'] = '2w'
assert model_grouper.get_model_group_id('module.Classifier',
{'param1': 'val1'},
metadata_frequency,
engine) == 2
# testing feature names may seem redundant but it is on a separate
# code path so make sure its logic works
metadata_features = copy(sample_metadata)
metadata_features['feature_names'] = ['ft1', 'ft3']
assert model_grouper.get_model_group_id('module.Classifier',
{'param1': 'val1'},
metadata_features, engine) == 3
