This is an automated email from the ASF dual-hosted git repository. zero323 pushed a commit to branch branch-3.3 in repository https://gitbox.apache.org/repos/asf/spark.git
The following commit(s) were added to refs/heads/branch-3.3 by this push: new 7101e88201d [SPARK-37405][FOLLOW-UP][PYTHON][ML] Move _input_kwargs hints to consistent positions 7101e88201d is described below commit 7101e88201d88cf24057187f360c828d1b376589 Author: zero323 <mszymkiew...@gmail.com> AuthorDate: Fri Apr 15 10:32:13 2022 +0200 [SPARK-37405][FOLLOW-UP][PYTHON][ML] Move _input_kwargs hints to consistent positions ### What changes were proposed in this pull request? This PR moves `_input_kwargs` hints to beginning of the bodies of the annotated classes. ### Why are the changes needed? Consistency with other modules. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Existing tests. Closes #36203 from zero323/SPARK-37405-FOLLOW-UP. Authored-by: zero323 <mszymkiew...@gmail.com> Signed-off-by: zero323 <mszymkiew...@gmail.com> (cherry picked from commit 797abc069348a2770742d5b57fd8c0fab0abe8d4) Signed-off-by: zero323 <mszymkiew...@gmail.com> --- python/pyspark/ml/feature.py | 68 ++++++++++++++++++++++---------------------- 1 file changed, 34 insertions(+), 34 deletions(-) diff --git a/python/pyspark/ml/feature.py b/python/pyspark/ml/feature.py index 8cebea2363d..7136c29f156 100755 --- a/python/pyspark/ml/feature.py +++ b/python/pyspark/ml/feature.py @@ -177,6 +177,8 @@ class Binarizer( ... """ + _input_kwargs: Dict[str, Any] + threshold: Param[float] = Param( Params._dummy(), "threshold", @@ -195,8 +197,6 @@ class Binarizer( typeConverter=TypeConverters.toListFloat, ) - _input_kwargs: Dict[str, Any] - @overload def __init__( self, @@ -721,6 +721,8 @@ class Bucketizer( ... """ + _input_kwargs: Dict[str, Any] + splits: Param[List[float]] = Param( Params._dummy(), "splits", @@ -762,8 +764,6 @@ class Bucketizer( typeConverter=TypeConverters.toListListFloat, ) - _input_kwargs: Dict[str, Any] - @overload def __init__( self, @@ -1284,6 +1284,8 @@ class DCT(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable["DCT"], Jav False """ + _input_kwargs: Dict[str, Any] + inverse: Param[bool] = Param( Params._dummy(), "inverse", @@ -1291,8 +1293,6 @@ class DCT(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable["DCT"], Jav typeConverter=TypeConverters.toBoolean, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -1392,6 +1392,8 @@ class ElementwiseProduct( True """ + _input_kwargs: Dict[str, Any] + scalingVec: Param[Vector] = Param( Params._dummy(), "scalingVec", @@ -1399,8 +1401,6 @@ class ElementwiseProduct( typeConverter=TypeConverters.toVector, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -1528,6 +1528,8 @@ class FeatureHasher( True """ + _input_kwargs: Dict[str, Any] + categoricalCols: Param[List[str]] = Param( Params._dummy(), "categoricalCols", @@ -1535,8 +1537,6 @@ class FeatureHasher( typeConverter=TypeConverters.toListString, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -1650,6 +1650,8 @@ class HashingTF( 5 """ + _input_kwargs: Dict[str, Any] + binary: Param[bool] = Param( Params._dummy(), "binary", @@ -1659,8 +1661,6 @@ class HashingTF( typeConverter=TypeConverters.toBoolean, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -2882,6 +2882,8 @@ class NGram(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable["NGram"], True """ + _input_kwargs: Dict[str, Any] + n: Param[int] = Param( Params._dummy(), "n", @@ -2889,8 +2891,6 @@ class NGram(JavaTransformer, HasInputCol, HasOutputCol, JavaMLReadable["NGram"], typeConverter=TypeConverters.toInt, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, *, n: int = 2, inputCol: Optional[str] = None, outputCol: Optional[str] = None @@ -2982,10 +2982,10 @@ class Normalizer( True """ - p = Param(Params._dummy(), "p", "the p norm value.", typeConverter=TypeConverters.toFloat) - _input_kwargs: Dict[str, Any] + p = Param(Params._dummy(), "p", "the p norm value.", typeConverter=TypeConverters.toFloat) + @keyword_only def __init__( self, *, p: float = 2.0, inputCol: Optional[str] = None, outputCol: Optional[str] = None @@ -3378,6 +3378,8 @@ class PolynomialExpansion( True """ + _input_kwargs: Dict[str, Any] + degree: Param[int] = Param( Params._dummy(), "degree", @@ -3385,8 +3387,6 @@ class PolynomialExpansion( typeConverter=TypeConverters.toInt, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, *, degree: int = 2, inputCol: Optional[str] = None, outputCol: Optional[str] = None @@ -3546,6 +3546,8 @@ class QuantileDiscretizer( ... """ + _input_kwargs: Dict[str, Any] + numBuckets: Param[int] = Param( Params._dummy(), "numBuckets", @@ -3579,8 +3581,6 @@ class QuantileDiscretizer( typeConverter=TypeConverters.toListInt, ) - _input_kwargs: Dict[str, Any] - @overload def __init__( self, @@ -4076,6 +4076,8 @@ class RegexTokenizer( True """ + _input_kwargs: Dict[str, Any] + minTokenLength: Param[int] = Param( Params._dummy(), "minTokenLength", @@ -4100,8 +4102,6 @@ class RegexTokenizer( typeConverter=TypeConverters.toBoolean, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -4237,12 +4237,12 @@ class SQLTransformer(JavaTransformer, JavaMLReadable["SQLTransformer"], JavaMLWr True """ + _input_kwargs: Dict[str, Any] + statement = Param( Params._dummy(), "statement", "SQL statement", typeConverter=TypeConverters.toString ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__(self, *, statement: Optional[str] = None): """ @@ -4874,6 +4874,8 @@ class IndexToString( StringIndexer : for converting categorical values into category indices """ + _input_kwargs: Dict[str, Any] + labels: Param[List[str]] = Param( Params._dummy(), "labels", @@ -4882,8 +4884,6 @@ class IndexToString( typeConverter=TypeConverters.toListString, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -4996,6 +4996,8 @@ class StopWordsRemover( ... """ + _input_kwargs: Dict[str, Any] + stopWords: Param[List[str]] = Param( Params._dummy(), "stopWords", @@ -5015,8 +5017,6 @@ class StopWordsRemover( typeConverter=TypeConverters.toString, ) - _input_kwargs: Dict[str, Any] - @overload def __init__( self, @@ -5327,6 +5327,8 @@ class VectorAssembler( ... """ + _input_kwargs: Dict[str, Any] + handleInvalid: Param[str] = Param( Params._dummy(), "handleInvalid", @@ -5341,8 +5343,6 @@ class VectorAssembler( typeConverter=TypeConverters.toString, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -5690,6 +5690,8 @@ class VectorSlicer( True """ + _input_kwargs: Dict[str, Any] + indices: Param[List[int]] = Param( Params._dummy(), "indices", @@ -5707,8 +5709,6 @@ class VectorSlicer( typeConverter=TypeConverters.toListString, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, @@ -6909,6 +6909,8 @@ class VectorSizeHint( True """ + _input_kwargs: Dict[str, Any] + size: Param[int] = Param( Params._dummy(), "size", "Size of vectors in column.", typeConverter=TypeConverters.toInt ) @@ -6924,8 +6926,6 @@ class VectorSizeHint( TypeConverters.toString, ) - _input_kwargs: Dict[str, Any] - @keyword_only def __init__( self, --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org