def test_keys_with_list_of_values():
# No exception in creating and executing model with a key/list pair
model = Workspace(quiet=True, q=["fa", "fb"])
model.learn("1 | a b c")
prediction = model.predict(" | a b c")
assert isinstance(prediction, float)
del model
def test_example_learn():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
ex.learn()
assert ex.setup_done is True
ex.unsetup_example() # unsetup an example as it is already setup
assert ex.setup_done is False
def test_slates_label():
model = Workspace(slates=True, quiet=True)
slates_shared_label = vowpalwabbit.SlatesLabel.from_example(
model.example("slates shared 0.8 | shared_0 shared_1"))
slates_action_label = vowpalwabbit.SlatesLabel.from_example(
model.example("slates action 1 | action_3"))
slates_slot_label = vowpalwabbit.SlatesLabel.from_example(
model.example("slates slot 1:0.8,0:0.1,2:0.1 | slot_0"))
assert slates_shared_label.type == vowpalwabbit.SlatesLabelType.SHARED
assert slates_shared_label.labeled == True
assert isclose(slates_shared_label.cost, 0.8)
assert str(slates_shared_label) == "slates shared 0.8"
assert slates_action_label.type == vowpalwabbit.SlatesLabelType.ACTION
assert slates_action_label.labeled == False
assert slates_action_label.weight == 1.0
assert slates_action_label.slot_id == 1
assert str(slates_action_label) == "slates action 1"
assert slates_slot_label.type == vowpalwabbit.SlatesLabelType.SLOT
assert slates_slot_label.labeled == True
assert slates_slot_label.probabilities[0].action == 1
assert isclose(slates_slot_label.probabilities[0].score, 0.8)
assert slates_slot_label.probabilities[1].action == 0
assert isclose(slates_slot_label.probabilities[1].score, 0.1)
assert slates_slot_label.probabilities[2].action == 2
assert isclose(slates_slot_label.probabilities[2].score, 0.1)
assert str(slates_slot_label) == "slates slot 1:0.8,0:0.1,2:0.1"
del model
def test_example_namespace_id():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
ns = vowpalwabbit.NamespaceId(ex, 1)
assert isinstance(ex.get_ns(1), vowpalwabbit.NamespaceId)
assert isinstance(ex[2], vowpalwabbit.ExampleNamespace)
assert ex.setup_done is True
assert ex.num_features_in(ns) == 3
def test_multilabel_label():
model = Workspace(multilabel_oaa=5, quiet=True)
multil = vowpalwabbit.MultilabelLabel.from_example(
model.example("1,2,3 |"))
assert len(multil.labels) == 3
assert multil.labels[0] == 1
assert multil.labels[1] == 2
assert multil.labels[2] == 3
assert str(multil) == "1,2,3"
def test_SimpleLabel_example():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
sl2 = vowpalwabbit.SimpleLabel.from_example(ex)
assert sl2.label == 1.0
assert sl2.weight == 1.0
assert sl2.prediction == 0.0
assert sl2.initial == 0.0
assert str(sl2) == "1.0"
def test_CostSensitiveLabel():
model = Workspace(csoaa=4, quiet=True)
csl = vowpalwabbit.CostSensitiveLabel.from_example(model.example("2:5 |"))
assert csl.costs[0].label == 2
assert csl.costs[0].wap_value == 0.0
assert csl.costs[0].partial_prediction == 0.0
assert csl.costs[0].cost == 5.0
assert str(csl) == "2:5.0"
del model
def test_action_scores_prediction_type():
model = Workspace(loss_function="logistic", csoaa_ldf="m", quiet=True)
multi_ex = [model.example("1:1 | a b c"), model.example("2:-1 | a b c")]
model.learn(multi_ex)
assert model.get_prediction_type() == model.pMULTICLASS
multi_ex = [model.example("1 | a b c"), model.example("2 | a b c")]
prediction = model.predict(multi_ex)
assert isinstance(prediction, int)
del model
def test_CBLabel():
model = Workspace(cb=4, quiet=True)
cbl = vowpalwabbit.CBLabel.from_example(model.example("1:10:0.5 |"))
assert cbl.weight == 1.0
assert cbl.costs[0].action == 1
assert cbl.costs[0].probability == 0.5
assert cbl.costs[0].partial_prediction == 0
assert cbl.costs[0].cost == 10.0
assert str(cbl) == "1:10.0:0.5"
del model
def helper_parse(examples):
model = Workspace(quiet=True, cb_adf=True)
ex = model.parse(examples)
assert len(ex) == 2
model.learn(ex)
model.finish_example(ex)
model.finish()
def test_learn_predict_multiline():
model = Workspace(quiet=True, cb_adf=True)
ex = model.parse(["| a:1 b:0.5", "0:0.1:0.75 | a:0.5 b:1 c:2"])
assert model.predict(ex) == [0.0, 0.0]
model.finish_example(ex)
ex = ["| a", "| b"]
model.learn(ex)
assert model.predict(ex) == [0.0, 0.0]
def test_CBContinuousLabel():
model = Workspace(cats=4,
min_value=185,
max_value=23959,
bandwidth=3000,
quiet=True)
cb_contl = vowpalwabbit.CBContinuousLabel.from_example(
model.example("ca 1:10:0.5 |"))
assert cb_contl.costs[0].action == 1
assert cb_contl.costs[0].pdf_value == 0.5
assert cb_contl.costs[0].cost == 10.0
assert str(cb_contl) == "ca 1:10.0:0.5"
del model
def test_example_features():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
ns = vowpalwabbit.NamespaceId(ex, 1)
assert ex.get_feature_id(ns, "a") == 127530
ex.push_hashed_feature(ns, 1122)
ex.push_features("x", [("c", 1.0), "d"])
ex.push_feature(ns, 11000)
assert ex.num_features_in("x") == 2
assert ex.sum_feat_sq(ns) == 5.0
ns2 = vowpalwabbit.NamespaceId(ex, 2)
ex.push_namespace(ns2)
assert ex.pop_namespace()
def test_command_line_with_space_and_escape_kwargs():
# load and parse external data file
test_file_dir = Path(__file__).resolve().parent
data_file = test_file_dir / "resources" / "train file.dat"
model = Workspace(oaa=3,
data=str(data_file),
final_regressor="test model.vw")
assert model.predict("| feature1:2.5") == 1
del model
model_file = Path("test model.vw")
assert model_file.is_file()
model_file.unlink()
def test_save_to_Path():
model = Workspace(quiet=True)
model.learn("1 | a b c")
model.save(Path("tmp1.model"))
model.save("tmp2.model")
assert filecmp.cmp("tmp1.model", "tmp2.model")
os.remove("tmp1.model")
os.remove("tmp2.model")
def test_namespace_id():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
nm1 = vowpalwabbit.NamespaceId(ex, 0)
nm2 = vowpalwabbit.NamespaceId(ex, 1)
nm3 = vowpalwabbit.NamespaceId(ex, 2)
assert nm1.id == 0
assert nm1.ord_ns == 97
assert nm1.ns == "a"
assert nm2.id == 1
assert nm2.ord_ns == 98
assert nm2.ns == "b"
assert nm3.id == 2
assert nm3.ord_ns == 128
assert nm3.ns == "\x80" # Represents string of ord_ns
def test_command_line_using_arg_list():
# load and parse external data file
test_file_dir = Path(__file__).resolve().parent
data_file = test_file_dir / "resources" / "train file.dat"
args = [
"--oaa", "3", "--data",
str(data_file), "--final_regressor", "test model2.vw"
]
model = Workspace(arg_list=args)
assert model.predict("| feature1:2.5") == 1
del model
model_file = Path("test model2.vw")
assert model_file.is_file()
model_file.unlink()
class TestVW:
model = Workspace(quiet=True, b=BIT_SIZE)
def test_constructor(self):
assert isinstance(self.model, Workspace)
def test_learn_predict(self):
ex = self.model.example("1 | a b c")
init = self.model.predict(ex)
assert init == 0
self.model.learn(ex)
assert self.model.predict(ex) > init
ex = ["| a", "| b"]
check_error_raises(TypeError, lambda: self.model.predict(ex))
check_error_raises(TypeError, lambda: self.model.learn(ex))
def test_get_tag(self):
ex = self.model.example("1 foo| a b c")
assert ex.get_tag() == "foo"
ex = self.model.example("1 1.0 bar| a b c")
assert ex.get_tag() == "bar"
ex = self.model.example("1 'baz | a b c")
assert ex.get_tag() == "baz"
def test_num_weights(self):
assert self.model.num_weights() == 2**BIT_SIZE
def test_get_weight(self):
assert self.model.get_weight(0, 0) == 0
def test_finish(self):
assert not self.model.finished
self.model.finish()
assert self.model.finished
def test_prob_prediction_type():
model = Workspace(
loss_function="logistic",
csoaa_ldf="mc",
probabilities=True,
quiet=True,
)
multi_ex = [
model.example("1:0.2 | a b c"),
model.example("2:0.8 | a b c"),
]
model.learn(multi_ex)
assert model.get_prediction_type() == vowpalwabbit.PredictionType.PROB
multi_ex = [model.example("1 | a b c"), model.example("2 | a b c")]
prediction = model.predict(multi_ex)
assert isinstance(prediction, float)
del model
def test_example_namespace():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
ns_id = vowpalwabbit.NamespaceId(ex, 1)
ex_nm = vowpalwabbit.ExampleNamespace(ex,
ns_id,
ns_hash=vw_ex.hash_space(ns_id.ns))
assert isinstance(ex_nm.ex, vowpalwabbit.Example)
assert isinstance(ex_nm.ns, vowpalwabbit.NamespaceId)
assert ex_nm.ns_hash == 2514386435
assert ex_nm.num_features_in() == 3
assert ex_nm[2] == (11617, 1.0) # represents (feature, value)
iter_obj = ex_nm.iter_features()
for i in range(ex_nm.num_features_in()):
assert ex_nm[i] == next(iter_obj)
assert ex_nm.pop_feature()
ex_nm.push_features(ns_id, ["c", "d"])
assert ex_nm.num_features_in() == 4
def test_scalar_prediction_type():
model = Workspace(quiet=True)
model.learn("1 | a b c")
assert model.get_prediction_type() == model.pSCALAR
prediction = model.predict(" | a b c")
assert isinstance(prediction, float)
del model
def test_action_probs_prediction_type():
model = Workspace(cb_explore=2, ngram=2, quiet=True)
model.learn("1 | a b c")
assert model.get_prediction_type() == model.pACTION_PROBS
prediction = model.predict(" | a b c")
assert isinstance(prediction, list)
del model
def test_multilabel_prediction_type():
model = Workspace(multilabel_oaa=4, quiet=True)
model.learn("1 | a b c")
assert model.get_prediction_type() == model.pMULTILABELS
prediction = model.predict(" | a b c")
assert isinstance(prediction, list)
del model
def test_ccb_label():
model = Workspace(ccb_explore_adf=True, quiet=True)
ccb_shared_label = vowpalwabbit.CCBLabel.from_example(
model.example("ccb shared | shared_0 shared_1"))
ccb_action_label = vowpalwabbit.CCBLabel.from_example(
model.example("ccb action | action_1 action_3"))
ccb_slot_label = vowpalwabbit.CCBLabel.from_example(
model.example("ccb slot 0:0.8:1.0 0 | slot_0"))
ccb_slot_pred_label = vowpalwabbit.CCBLabel.from_example(
model.example("ccb slot |"))
assert ccb_shared_label.type == vowpalwabbit.CCBLabelType.SHARED
assert len(ccb_shared_label.explicit_included_actions) == 0
assert ccb_shared_label.outcome is None
assert str(ccb_shared_label) == "ccb shared"
assert ccb_action_label.type == vowpalwabbit.CCBLabelType.ACTION
assert len(ccb_action_label.explicit_included_actions) == 0
assert ccb_action_label.weight == 1.0
assert ccb_action_label.outcome is None
assert str(ccb_action_label) == "ccb action"
assert ccb_slot_label.type == vowpalwabbit.CCBLabelType.SLOT
assert ccb_slot_label.explicit_included_actions[0] == 0
assert ccb_slot_label.outcome.action_probs[0].action == 0
assert isclose(ccb_slot_label.outcome.action_probs[0].score, 1.0)
assert isclose(ccb_slot_label.outcome.cost, 0.8)
assert str(ccb_slot_label) == "ccb slot 0:0.8:1.0 0"
assert ccb_slot_pred_label.type == vowpalwabbit.CCBLabelType.SLOT
assert len(ccb_slot_pred_label.explicit_included_actions) == 0
assert ccb_slot_pred_label.outcome is None
assert str(ccb_slot_pred_label) == "ccb slot"
del model
def test_multiclass_prediction_type():
n = 3
model = Workspace(loss_function="logistic", oaa=n, quiet=True)
model.learn("1 | a b c")
assert model.get_prediction_type(
) == vowpalwabbit.PredictionType.MULTICLASS
prediction = model.predict(" | a b c")
assert isinstance(prediction, int)
del model
def test_scalars_prediction_type():
n = 3
model = Workspace(loss_function="logistic",
oaa=n,
probabilities=True,
quiet=True)
model.learn("1 | a b c")
assert model.get_prediction_type() == vowpalwabbit.PredictionType.SCALARS
prediction = model.predict(" | a b c")
assert isinstance(prediction, list)
assert len(prediction) == n
del model
def test_parse_2():
model = Workspace(quiet=True, cb_adf=True)
ex = model.parse("| a:1 b:0.5\n0:0.1:0.75 | a:0.5 b:1 c:2")
assert len(ex) == 2
model.learn(ex)
model.finish_example(ex)
model.finish()
model = Workspace(quiet=True, cb_adf=True)
ex = model.parse(["| a:1 b:0.5", "0:0.1:0.75 | a:0.5 b:1 c:2"])
assert len(ex) == 2
model.learn(ex)
model.finish_example(ex)
model.finish()
def test_delete():
model = Workspace(quiet=True, b=BIT_SIZE)
assert "model" in locals()
del model
assert "model" not in locals()
def test_get_weight_name():
model = Workspace(quiet=True)
model.learn("1 | a a b c |ns x")
assert model.get_weight_from_name("a") != 0.0
assert model.get_weight_from_name("b") != 0.0
assert model.get_weight_from_name("b") == model.get_weight_from_name("c")
assert model.get_weight_from_name("a") != model.get_weight_from_name("b")
assert model.get_weight_from_name("x") == 0.0
assert model.get_weight_from_name("x", "ns") != 0.0
assert model.get_weight_from_name("x",
"ns") == model.get_weight_from_name("b")
def test_example_label():
vw_ex = Workspace(quiet=True)
ex = vw_ex.example("1 |a two features |b more features here")
ex.set_label_string("1.0")
assert isinstance(ex.get_label(), vowpalwabbit.SimpleLabel)