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fix: SparkML StandardScaler conversion fails when withStd or withMean is set to true #555

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Jun 5, 2022
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fix: SparkML StandardScaler conversion fails when withStd or withMean is set to true #555

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650c4d6
fix: SparkML StandardScaler conversion fails when withStd or withMean…
memoryz May 28, 2022
450911e
Merge branch 'main' into jasowang/iss540
memoryz Jun 4, 2022
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4 changes: 2 additions & 2 deletions onnxmltools/convert/sparkml/operator_converters/scaler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,8 @@ def convert_sparkml_scaler(scope, operator, container):
attrs = {'name': scope.get_unique_operator_name(op_type)}
if isinstance(op, StandardScalerModel):
C = operator.inputs[0].type.shape[1]
attrs['offset'] = op.mean if op.getOrDefault("withMean") else [0.0] * C
attrs['scale'] = [1.0 / x for x in op.std] if op.getOrDefault("withStd") else [1.0] * C
attrs['offset'] = op.mean.toArray() if op.getOrDefault("withMean") else [0.0] * C
attrs['scale'] = [1.0 / x for x in op.std.toArray()] if op.getOrDefault("withStd") else [1.0] * C
elif isinstance(op, MinMaxScalerModel):
epsilon = 1.0e-8 # to avoid dividing by zero
attrs['offset'] = [x for x in op.originalMin]
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2 changes: 1 addition & 1 deletion tests/sparkml/test_scaler.py
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Expand Up @@ -75,7 +75,7 @@ def test_standard_scaler(self):
(1, Vectors.dense([2.0, 1.1, 1.0]),),
(2, Vectors.dense([3.0, 10.1, 3.0]),)
], ["id", "features"])
scaler = StandardScaler(inputCol='features', outputCol='scaled_features')
scaler = StandardScaler(inputCol='features', outputCol='scaled_features', withStd=True, withMean=True)
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No need to test other values of withStd, withMean?

model = scaler.fit(data)

# the input names must match the inputCol(s) above
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