[ 
https://issues.apache.org/jira/browse/SPARK-28735?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Dongjoon Hyun updated SPARK-28735:
----------------------------------
    Description: 
Build Spark and run PySpark UT with JDK11. The last commented `assertTrue` 
failed.

{code}
$ build/sbt -Phadoop-3.2 test:package
$ python/run-tests --testnames 'pyspark.ml.tests.test_algorithms' 
--python-executables python
...
======================================================================
FAIL: test_raw_and_probability_prediction 
(pyspark.ml.tests.test_algorithms.MultilayerPerceptronClassifierTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File 
"/Users/dongjoon/APACHE/spark-master/python/pyspark/ml/tests/test_algorithms.py",
 line 89, in test_raw_and_probability_prediction
    self.assertTrue(np.allclose(result.rawPrediction, expected_rawPrediction, 
atol=1E-4))
AssertionError: False is not true
{code}

{code:python}
class MultilayerPerceptronClassifierTest(SparkSessionTestCase):
    def test_raw_and_probability_prediction(self):
        data_path = "data/mllib/sample_multiclass_classification_data.txt"
        df = self.spark.read.format("libsvm").load(data_path)
        mlp = MultilayerPerceptronClassifier(maxIter=100, layers=[4, 5, 4, 3],
                                             blockSize=128, seed=123)
        model = mlp.fit(df)
        test = self.sc.parallelize([Row(features=Vectors.dense(0.1, 0.1, 0.25, 
0.25))]).toDF()
        result = model.transform(test).head()
        expected_prediction = 2.0
        expected_probability = [0.0, 0.0, 1.0]
                expected_rawPrediction = [-11.6081922998, -8.15827998691, 
22.17757045]
                self.assertTrue(result.prediction, expected_prediction)
                self.assertTrue(np.allclose(result.probability, 
expected_probability, atol=1E-4))
                self.assertTrue(np.allclose(result.rawPrediction, 
expected_rawPrediction, atol=1E-4))
                # self.assertTrue(np.allclose(result.rawPrediction, 
expected_rawPrediction, atol=1E-4))
{code}

  was:
Build Spark with JDK11 and run `python/run-tests --testnames 
'pyspark.ml.tests.test_algorithms' --python-executables python`. The last 
commented `assertTrue` failed.

- 
https://github.com/apache/spark/pull/25443/commits/593a154813880fb13e3091043d809e0c00e57bc5

{code:python}
class MultilayerPerceptronClassifierTest(SparkSessionTestCase):
    def test_raw_and_probability_prediction(self):
        data_path = "data/mllib/sample_multiclass_classification_data.txt"
        df = self.spark.read.format("libsvm").load(data_path)
        mlp = MultilayerPerceptronClassifier(maxIter=100, layers=[4, 5, 4, 3],
                                             blockSize=128, seed=123)
        model = mlp.fit(df)
        test = self.sc.parallelize([Row(features=Vectors.dense(0.1, 0.1, 0.25, 
0.25))]).toDF()
        result = model.transform(test).head()
        expected_prediction = 2.0
        expected_probability = [0.0, 0.0, 1.0]
                expected_rawPrediction = [-11.6081922998, -8.15827998691, 
22.17757045]
                self.assertTrue(result.prediction, expected_prediction)
                self.assertTrue(np.allclose(result.probability, 
expected_probability, atol=1E-4))
                self.assertTrue(np.allclose(result.rawPrediction, 
expected_rawPrediction, atol=1E-4))
                # self.assertTrue(np.allclose(result.rawPrediction, 
expected_rawPrediction, atol=1E-4))
{code}


> MultilayerPerceptronClassifierTest.test_raw_and_probability_prediction fails 
> on JDK11
> -------------------------------------------------------------------------------------
>
>                 Key: SPARK-28735
>                 URL: https://issues.apache.org/jira/browse/SPARK-28735
>             Project: Spark
>          Issue Type: Sub-task
>          Components: PySpark
>    Affects Versions: 3.0.0
>            Reporter: Dongjoon Hyun
>            Priority: Major
>
> Build Spark and run PySpark UT with JDK11. The last commented `assertTrue` 
> failed.
> {code}
> $ build/sbt -Phadoop-3.2 test:package
> $ python/run-tests --testnames 'pyspark.ml.tests.test_algorithms' 
> --python-executables python
> ...
> ======================================================================
> FAIL: test_raw_and_probability_prediction 
> (pyspark.ml.tests.test_algorithms.MultilayerPerceptronClassifierTest)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File 
> "/Users/dongjoon/APACHE/spark-master/python/pyspark/ml/tests/test_algorithms.py",
>  line 89, in test_raw_and_probability_prediction
>     self.assertTrue(np.allclose(result.rawPrediction, expected_rawPrediction, 
> atol=1E-4))
> AssertionError: False is not true
> {code}
> {code:python}
> class MultilayerPerceptronClassifierTest(SparkSessionTestCase):
>     def test_raw_and_probability_prediction(self):
>         data_path = "data/mllib/sample_multiclass_classification_data.txt"
>         df = self.spark.read.format("libsvm").load(data_path)
>         mlp = MultilayerPerceptronClassifier(maxIter=100, layers=[4, 5, 4, 3],
>                                              blockSize=128, seed=123)
>         model = mlp.fit(df)
>         test = self.sc.parallelize([Row(features=Vectors.dense(0.1, 0.1, 
> 0.25, 0.25))]).toDF()
>         result = model.transform(test).head()
>         expected_prediction = 2.0
>         expected_probability = [0.0, 0.0, 1.0]
>               expected_rawPrediction = [-11.6081922998, -8.15827998691, 
> 22.17757045]
>               self.assertTrue(result.prediction, expected_prediction)
>               self.assertTrue(np.allclose(result.probability, 
> expected_probability, atol=1E-4))
>               self.assertTrue(np.allclose(result.rawPrediction, 
> expected_rawPrediction, atol=1E-4))
>               # self.assertTrue(np.allclose(result.rawPrediction, 
> expected_rawPrediction, atol=1E-4))
> {code}



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