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test_sklearn_naive_bayes_converter.py
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test_sklearn_naive_bayes_converter.py
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import onnx
import unittest
from distutils.version import StrictVersion
from sklearn.naive_bayes import MultinomialNB, BernoulliNB
from skl2onnx import convert_sklearn
from skl2onnx.common.data_types import FloatTensorType, Int64TensorType
from skl2onnx.common.data_types import onnx_built_with_ml
from test_utils import dump_data_and_model, fit_classification_model
class TestNaiveBayesConverter(unittest.TestCase):
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_multinomial_nb_binary_classification(self):
model, X = fit_classification_model(
MultinomialNB(), 2, pos_features=True)
model_onnx = convert_sklearn(
model,
"multinomial naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnBinMultinomialNB-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(
StrictVersion(onnx.__version__) <= StrictVersion("1.3"),
reason="Requires opset 9.",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_bernoulli_nb_binary_classification(self):
model, X = fit_classification_model(
BernoulliNB(), 2)
model_onnx = convert_sklearn(
model,
"bernoulli naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnBinBernoulliNB",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_multinomial_nb_multiclass(self):
model, X = fit_classification_model(
MultinomialNB(), 5, pos_features=True)
model_onnx = convert_sklearn(
model,
"multinomial naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclMultinomialNB-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_multinomial_nb_multiclass_params(self):
model, X = fit_classification_model(
MultinomialNB(alpha=0.5, fit_prior=False), 5, pos_features=True)
model_onnx = convert_sklearn(
model,
"multinomial naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclMultinomialNBParams-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(
StrictVersion(onnx.__version__) <= StrictVersion("1.3"),
reason="Requires opset 9.",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_bernoulli_nb_multiclass(self):
model, X = fit_classification_model(
BernoulliNB(), 4)
model_onnx = convert_sklearn(
model,
"bernoulli naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclBernoulliNB",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(
StrictVersion(onnx.__version__) <= StrictVersion("1.3"),
reason="Requires opset 9.",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_bernoulli_nb_multiclass_params(self):
model, X = fit_classification_model(
BernoulliNB(alpha=0, binarize=1.0, fit_prior=False), 4)
model_onnx = convert_sklearn(
model,
"bernoulli naive bayes",
[("input", FloatTensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclBernoulliNBParams",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_multinomial_nb_binary_classification_int(self):
model, X = fit_classification_model(
MultinomialNB(), 2, is_int=True, pos_features=True)
model_onnx = convert_sklearn(
model,
"multinomial naive bayes",
[("input", Int64TensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnBinMultinomialNBInt-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(
StrictVersion(onnx.__version__) <= StrictVersion("1.3"),
reason="Requires opset 9.",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_bernoulli_nb_binary_classification_int(self):
model, X = fit_classification_model(
BernoulliNB(), 2, is_int=True)
model_onnx = convert_sklearn(
model,
"bernoulli naive bayes",
[("input", Int64TensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnBinBernoulliNBInt",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_multinomial_nb_multiclass_int(self):
model, X = fit_classification_model(
MultinomialNB(), 5, is_int=True, pos_features=True)
model_onnx = convert_sklearn(
model,
"multinomial naive bayes",
[("input", Int64TensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclMultinomialNBInt-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
@unittest.skipIf(
StrictVersion(onnx.__version__) <= StrictVersion("1.3"),
reason="Requires opset 9.",
)
@unittest.skipIf(not onnx_built_with_ml(),
reason="Requires ONNX-ML extension.")
def test_model_bernoulli_nb_multiclass_int(self):
model, X = fit_classification_model(
BernoulliNB(), 4, is_int=True)
model_onnx = convert_sklearn(
model,
"bernoulli naive bayes",
[("input", Int64TensorType(X.shape))],
)
self.assertIsNotNone(model_onnx)
dump_data_and_model(
X,
model,
model_onnx,
basename="SklearnMclBernoulliNBInt-Dec4",
allow_failure="StrictVersion(onnxruntime.__version__)"
"<= StrictVersion('0.2.1')",
)
if __name__ == "__main__":
unittest.main()