ml/tests/test_wrapper.py

0001 #
0002 # Licensed to the Apache Software Foundation (ASF) under one or more
0003 # contributor license agreements.  See the NOTICE file distributed with
0004 # this work for additional information regarding copyright ownership.
0005 # The ASF licenses this file to You under the Apache License, Version 2.0
0006 # (the "License"); you may not use this file except in compliance with
0007 # the License.  You may obtain a copy of the License at
0008 #
0009 #    http://www.apache.org/licenses/LICENSE-2.0
0010 #
0011 # Unless required by applicable law or agreed to in writing, software
0012 # distributed under the License is distributed on an "AS IS" BASIS,
0013 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014 # See the License for the specific language governing permissions and
0015 # limitations under the License.
0016 #
0017
0018 import unittest
0019
0020 import py4j
0021
0022 from pyspark.ml.linalg import DenseVector, Vectors
0023 from pyspark.ml.regression import LinearRegression
0024 from pyspark.ml.wrapper import _java2py, _py2java, JavaParams, JavaWrapper
0025 from pyspark.testing.mllibutils import MLlibTestCase
0026 from pyspark.testing.mlutils import SparkSessionTestCase
0027 from pyspark.testing.utils import eventually
0028
0029
0030 class JavaWrapperMemoryTests(SparkSessionTestCase):
0031
0032     def test_java_object_gets_detached(self):
0033         df = self.spark.createDataFrame([(1.0, 2.0, Vectors.dense(1.0)),
0034                                          (0.0, 2.0, Vectors.sparse(1, [], []))],
0035                                         ["label", "weight", "features"])
0036         lr = LinearRegression(maxIter=1, regParam=0.0, solver="normal", weightCol="weight",
0037                               fitIntercept=False)
0038
0039         model = lr.fit(df)
0040         summary = model.summary
0041
0042         self.assertIsInstance(model, JavaWrapper)
0043         self.assertIsInstance(summary, JavaWrapper)
0044         self.assertIsInstance(model, JavaParams)
0045         self.assertNotIsInstance(summary, JavaParams)
0046
0047         error_no_object = 'Target Object ID does not exist for this gateway'
0048
0049         self.assertIn("LinearRegression_", model._java_obj.toString())
0050         self.assertIn("LinearRegressionTrainingSummary", summary._java_obj.toString())
0051
0052         model.__del__()
0053
0054         def condition():
0055             with self.assertRaisesRegexp(py4j.protocol.Py4JError, error_no_object):
0056                 model._java_obj.toString()
0057             self.assertIn("LinearRegressionTrainingSummary", summary._java_obj.toString())
0058             return True
0059
0060         eventually(condition, timeout=10, catch_assertions=True)
0061
0062         try:
0063             summary.__del__()
0064         except:
0065             pass
0066
0067         def condition():
0068             with self.assertRaisesRegexp(py4j.protocol.Py4JError, error_no_object):
0069                 model._java_obj.toString()
0070             with self.assertRaisesRegexp(py4j.protocol.Py4JError, error_no_object):
0071                 summary._java_obj.toString()
0072             return True
0073
0074         eventually(condition, timeout=10, catch_assertions=True)
0075
0076
0077 class WrapperTests(MLlibTestCase):
0078
0079     def test_new_java_array(self):
0080         # test array of strings
0081         str_list = ["a", "b", "c"]
0082         java_class = self.sc._gateway.jvm.java.lang.String
0083         java_array = JavaWrapper._new_java_array(str_list, java_class)
0084         self.assertEqual(_java2py(self.sc, java_array), str_list)
0085         # test array of integers
0086         int_list = [1, 2, 3]
0087         java_class = self.sc._gateway.jvm.java.lang.Integer
0088         java_array = JavaWrapper._new_java_array(int_list, java_class)
0089         self.assertEqual(_java2py(self.sc, java_array), int_list)
0090         # test array of floats
0091         float_list = [0.1, 0.2, 0.3]
0092         java_class = self.sc._gateway.jvm.java.lang.Double
0093         java_array = JavaWrapper._new_java_array(float_list, java_class)
0094         self.assertEqual(_java2py(self.sc, java_array), float_list)
0095         # test array of bools
0096         bool_list = [False, True, True]
0097         java_class = self.sc._gateway.jvm.java.lang.Boolean
0098         java_array = JavaWrapper._new_java_array(bool_list, java_class)
0099         self.assertEqual(_java2py(self.sc, java_array), bool_list)
0100         # test array of Java DenseVectors
0101         v1 = DenseVector([0.0, 1.0])
0102         v2 = DenseVector([1.0, 0.0])
0103         vec_java_list = [_py2java(self.sc, v1), _py2java(self.sc, v2)]
0104         java_class = self.sc._gateway.jvm.org.apache.spark.ml.linalg.DenseVector
0105         java_array = JavaWrapper._new_java_array(vec_java_list, java_class)
0106         self.assertEqual(_java2py(self.sc, java_array), [v1, v2])
0107         # test empty array
0108         java_class = self.sc._gateway.jvm.java.lang.Integer
0109         java_array = JavaWrapper._new_java_array([], java_class)
0110         self.assertEqual(_java2py(self.sc, java_array), [])
0111         # test array of array of strings
0112         str_list = [["a", "b", "c"], ["d", "e"], ["f", "g", "h", "i"], []]
0113         expected_str_list = [("a", "b", "c", None), ("d", "e", None, None), ("f", "g", "h", "i"),
0114                              (None, None, None, None)]
0115         java_class = self.sc._gateway.jvm.java.lang.String
0116         java_array = JavaWrapper._new_java_array(str_list, java_class)
0117         self.assertEqual(_java2py(self.sc, java_array), expected_str_list)
0118
0119 if __name__ == "__main__":
0120     from pyspark.ml.tests.test_wrapper import *
0121
0122     try:
0123         import xmlrunner
0124         testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
0125     except ImportError:
0126         testRunner = None
0127     unittest.main(testRunner=testRunner, verbosity=2)