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Sparml converter: support type StringType and StringType() #638

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Sparml converter: support type StringType and StringType() #638

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8dcbd5d
Fix: buildInputDictSimple dataType Stringtype()
mattoh91 Mar 20, 2023
13f52ac
Fix: getTensorTypeFromSpark for batch input
mattoh91 Mar 20, 2023
301973e
fix merged conflicts
xadupre Aug 1, 2023
174e5d9
Support for lightgbm >= 4.0 (#634)
xadupre Jul 28, 2023
2b70976
Apply black and ruff. (#635)
xadupre Aug 1, 2023
b268fe7
Fix: buildInputDictSimple dataType Stringtype()
mattoh91 Mar 20, 2023
0ba3181
fix merge conflicts
xadupre Aug 1, 2023
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13 changes: 6 additions & 7 deletions onnxmltools/convert/sparkml/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,9 @@ def buildInitialTypesSimple(dataframe):


def getTensorTypeFromSpark(sparktype):
if sparktype == "StringType" or sparktype == "StringType()":
return StringTensorType([1, 1])
elif (
if sparktype in ("StringType", "StringType()"):
return StringTensorType([None, 1])
if (
sparktype == "DecimalType"
or sparktype == "DecimalType()"
or sparktype == "DoubleType"
Expand All @@ -34,17 +34,16 @@ def getTensorTypeFromSpark(sparktype):
or sparktype == "BooleanType"
or sparktype == "BooleanType()"
):
return FloatTensorType([1, 1])
else:
raise TypeError("Cannot map this type to Onnx types: " + sparktype)
return FloatTensorType([None, 1])
raise TypeError("Cannot map this type to Onnx types: " + sparktype)


def buildInputDictSimple(dataframe):
import numpy

result = {}
for field in dataframe.schema.fields:
if str(field.dataType) == "StringType":
if str(field.dataType) in ("StringType", "StringType()"):
result[field.name] = dataframe.select(field.name).toPandas().values
else:
result[field.name] = (
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