Repository: spark Updated Branches: refs/heads/master d1aadea05 -> 87d69a01f
[MINOR][PYSPARK] update _shared_params_code_gen.py ## What changes were proposed in this pull request? 1, add arg-checkings for `tol` and `stepSize` to keep in line with `SharedParamsCodeGen.scala` 2, fix one typo ## How was this patch tested? local build Author: Zheng RuiFeng <[email protected]> Closes #12996 from zhengruifeng/py_args_checking. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/87d69a01 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/87d69a01 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/87d69a01 Branch: refs/heads/master Commit: 87d69a01f027aa18718827f94f921b4a1eaa78a5 Parents: d1aadea Author: Zheng RuiFeng <[email protected]> Authored: Fri May 13 08:52:06 2016 +0200 Committer: Nick Pentreath <[email protected]> Committed: Fri May 13 08:52:06 2016 +0200 ---------------------------------------------------------------------- python/pyspark/ml/clustering.py | 2 +- python/pyspark/ml/param/_shared_params_code_gen.py | 6 +++--- python/pyspark/ml/param/shared.py | 12 ++++++------ 3 files changed, 10 insertions(+), 10 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/87d69a01/python/pyspark/ml/clustering.py ---------------------------------------------------------------------- diff --git a/python/pyspark/ml/clustering.py b/python/pyspark/ml/clustering.py index b90daf1..9216331 100644 --- a/python/pyspark/ml/clustering.py +++ b/python/pyspark/ml/clustering.py @@ -517,7 +517,7 @@ class LDAModel(JavaModel): def estimatedDocConcentration(self): """ Value for :py:attr:`LDA.docConcentration` estimated from data. - If Online LDA was used and :py:attr::`LDA.optimizeDocConcentration` was set to false, + If Online LDA was used and :py:attr:`LDA.optimizeDocConcentration` was set to false, then this returns the fixed (given) value for the :py:attr:`LDA.docConcentration` parameter. """ return self._call_java("estimatedDocConcentration") http://git-wip-us.apache.org/repos/asf/spark/blob/87d69a01/python/pyspark/ml/param/_shared_params_code_gen.py ---------------------------------------------------------------------- diff --git a/python/pyspark/ml/param/_shared_params_code_gen.py b/python/pyspark/ml/param/_shared_params_code_gen.py index 12f1453..c32dcc4 100644 --- a/python/pyspark/ml/param/_shared_params_code_gen.py +++ b/python/pyspark/ml/param/_shared_params_code_gen.py @@ -124,12 +124,12 @@ if __name__ == "__main__": "E.g. 10 means that the cache will get checkpointed every 10 iterations.", None, "TypeConverters.toInt"), ("seed", "random seed.", "hash(type(self).__name__)", "TypeConverters.toInt"), - ("tol", "the convergence tolerance for iterative algorithms.", None, + ("tol", "the convergence tolerance for iterative algorithms (>= 0).", None, "TypeConverters.toFloat"), - ("stepSize", "Step size to be used for each iteration of optimization.", None, + ("stepSize", "Step size to be used for each iteration of optimization (>= 0).", None, "TypeConverters.toFloat"), ("handleInvalid", "how to handle invalid entries. Options are skip (which will filter " + - "out rows with bad values), or error (which will throw an errror). More options may be " + + "out rows with bad values), or error (which will throw an error). More options may be " + "added later.", None, "TypeConverters.toString"), ("elasticNetParam", "the ElasticNet mixing parameter, in range [0, 1]. For alpha = 0, " + "the penalty is an L2 penalty. For alpha = 1, it is an L1 penalty.", "0.0", http://git-wip-us.apache.org/repos/asf/spark/blob/87d69a01/python/pyspark/ml/param/shared.py ---------------------------------------------------------------------- diff --git a/python/pyspark/ml/param/shared.py b/python/pyspark/ml/param/shared.py index 9ed63e4..c5ccf81 100644 --- a/python/pyspark/ml/param/shared.py +++ b/python/pyspark/ml/param/shared.py @@ -328,10 +328,10 @@ class HasSeed(Params): class HasTol(Params): """ - Mixin for param tol: the convergence tolerance for iterative algorithms. + Mixin for param tol: the convergence tolerance for iterative algorithms (>= 0). """ - tol = Param(Params._dummy(), "tol", "the convergence tolerance for iterative algorithms.", typeConverter=TypeConverters.toFloat) + tol = Param(Params._dummy(), "tol", "the convergence tolerance for iterative algorithms (>= 0).", typeConverter=TypeConverters.toFloat) def __init__(self): super(HasTol, self).__init__() @@ -351,10 +351,10 @@ class HasTol(Params): class HasStepSize(Params): """ - Mixin for param stepSize: Step size to be used for each iteration of optimization. + Mixin for param stepSize: Step size to be used for each iteration of optimization (>= 0). """ - stepSize = Param(Params._dummy(), "stepSize", "Step size to be used for each iteration of optimization.", typeConverter=TypeConverters.toFloat) + stepSize = Param(Params._dummy(), "stepSize", "Step size to be used for each iteration of optimization (>= 0).", typeConverter=TypeConverters.toFloat) def __init__(self): super(HasStepSize, self).__init__() @@ -374,10 +374,10 @@ class HasStepSize(Params): class HasHandleInvalid(Params): """ - Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later. + Mixin for param handleInvalid: how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an error). More options may be added later. """ - handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an errror). More options may be added later.", typeConverter=TypeConverters.toString) + handleInvalid = Param(Params._dummy(), "handleInvalid", "how to handle invalid entries. Options are skip (which will filter out rows with bad values), or error (which will throw an error). More options may be added later.", typeConverter=TypeConverters.toString) def __init__(self): super(HasHandleInvalid, self).__init__() --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
