def test_lightgbm_regressor(self):
model = LGBMRegressor(n_estimators=3, min_child_samples=1)
dump_single_regression(model,
target_opset={
'': TARGET_OPSET,
'ai.onnx.ml': TARGET_OPSET_ML
})
def test_decision_tree_regressor(self):
model = DecisionTreeRegressor()
dump_single_regression(
model,
allow_failure=
"StrictVersion(onnx.__version__) < StrictVersion('1.2')")
dump_multiple_regression(
model,
allow_failure=
"StrictVersion(onnx.__version__) < StrictVersion('1.2')")
def test_extra_trees_regressor(self):
model = ExtraTreesRegressor(n_estimators=3)
dump_single_regression(
model,
allow_failure=
"StrictVersion(onnxruntime.__version__) <= StrictVersion('0.2.1')")
dump_multiple_regression(
model,
allow_failure=
"StrictVersion(onnxruntime.__version__) <= StrictVersion('0.2.1')")
def test_random_forest_regressor(self):
model = RandomForestRegressor(n_estimators=3)
dump_single_regression(
model,
allow_failure=
"StrictVersion(onnxruntime.__version__) <= StrictVersion('0.2.1')")
dump_multiple_regression(
model,
allow_failure=
"StrictVersion(onnxruntime.__version__) <= StrictVersion('0.2.1')")
def test_extra_tree_regressor(self):
model = ExtraTreeRegressor()
dump_single_regression(
model,
allow_failure="StrictVersion(onnx.__version__)"
" < StrictVersion('1.2')",
)
dump_multiple_regression(
model,
allow_failure="StrictVersion(onnx.__version__)"
" < StrictVersion('1.2')",
)
def test_xgb_regressor(self):
iris = load_iris()
X = iris.data[:, :2]
y = iris.target
xgb = XGBRegressor()
xgb.fit(X, y)
conv_model = convert_sklearn(
xgb, initial_types=[
('input', FloatTensorType(shape=[None, X.shape[1]]))])
self.assertTrue(conv_model is not None)
dump_single_regression(xgb, suffix="-Dec4")
def test_extra_trees_regressor(self):
model = ExtraTreesRegressor(n_estimators=3)
dump_single_regression(model)
dump_multiple_regression(model)
def test_random_forest_regressor(self):
model = RandomForestRegressor(n_estimators=3)
dump_single_regression(model)
dump_multiple_regression(model)
def test_lightgbm_regressor2(self):
model = LGBMRegressor(n_estimators=2, max_depth=1, min_child_samples=1)
dump_single_regression(model, suffix="2")
def test_lightgbm_regressor(self):
model = LGBMRegressor(n_estimators=3, min_child_samples=1)
dump_single_regression(model)
def test_extra_tree_regressor(self):
model = ExtraTreeRegressor()
dump_single_regression(model)
dump_multiple_regression(model)
def test_decision_tree_regressor(self):
model = DecisionTreeRegressor()
dump_single_regression(model)
dump_multiple_regression(model)
def test_gradient_boosting_regressor(self):
model = GradientBoostingRegressor(n_estimators=3)
dump_single_regression(model)
