57cd1e86d1
Same as #5431 but for Python. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #5534 from mengxr/SPARK-6893 and squashes the following commits: d3b519b [Xiangrui Meng] address comments ebaccc6 [Xiangrui Meng] style update fce244e [Xiangrui Meng] update explainParams with test 4d6b07a [Xiangrui Meng] add tests 5294500 [Xiangrui Meng] update default param handling in python
164 lines
5.3 KiB
Python
164 lines
5.3 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Unit tests for Spark ML Python APIs.
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"""
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import sys
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if sys.version_info[:2] <= (2, 6):
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try:
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import unittest2 as unittest
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except ImportError:
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sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier')
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sys.exit(1)
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else:
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import unittest
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from pyspark.tests import ReusedPySparkTestCase as PySparkTestCase
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from pyspark.sql import DataFrame
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from pyspark.ml.param import Param
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from pyspark.ml.param.shared import HasMaxIter, HasInputCol
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from pyspark.ml.pipeline import Transformer, Estimator, Pipeline
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class MockDataset(DataFrame):
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def __init__(self):
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self.index = 0
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class MockTransformer(Transformer):
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def __init__(self):
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super(MockTransformer, self).__init__()
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self.fake = Param(self, "fake", "fake")
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self.dataset_index = None
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self.fake_param_value = None
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def transform(self, dataset, params={}):
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self.dataset_index = dataset.index
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if self.fake in params:
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self.fake_param_value = params[self.fake]
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dataset.index += 1
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return dataset
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class MockEstimator(Estimator):
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def __init__(self):
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super(MockEstimator, self).__init__()
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self.fake = Param(self, "fake", "fake")
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self.dataset_index = None
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self.fake_param_value = None
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self.model = None
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def fit(self, dataset, params={}):
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self.dataset_index = dataset.index
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if self.fake in params:
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self.fake_param_value = params[self.fake]
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model = MockModel()
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self.model = model
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return model
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class MockModel(MockTransformer, Transformer):
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def __init__(self):
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super(MockModel, self).__init__()
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class PipelineTests(PySparkTestCase):
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def test_pipeline(self):
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dataset = MockDataset()
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estimator0 = MockEstimator()
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transformer1 = MockTransformer()
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estimator2 = MockEstimator()
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transformer3 = MockTransformer()
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pipeline = Pipeline() \
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.setStages([estimator0, transformer1, estimator2, transformer3])
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pipeline_model = pipeline.fit(dataset, {estimator0.fake: 0, transformer1.fake: 1})
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self.assertEqual(0, estimator0.dataset_index)
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self.assertEqual(0, estimator0.fake_param_value)
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model0 = estimator0.model
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self.assertEqual(0, model0.dataset_index)
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self.assertEqual(1, transformer1.dataset_index)
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self.assertEqual(1, transformer1.fake_param_value)
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self.assertEqual(2, estimator2.dataset_index)
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model2 = estimator2.model
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self.assertIsNone(model2.dataset_index, "The model produced by the last estimator should "
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"not be called during fit.")
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dataset = pipeline_model.transform(dataset)
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self.assertEqual(2, model0.dataset_index)
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self.assertEqual(3, transformer1.dataset_index)
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self.assertEqual(4, model2.dataset_index)
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self.assertEqual(5, transformer3.dataset_index)
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self.assertEqual(6, dataset.index)
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class TestParams(HasMaxIter, HasInputCol):
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"""
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A subclass of Params mixed with HasMaxIter and HasInputCol.
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"""
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def __init__(self):
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super(TestParams, self).__init__()
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self._setDefault(maxIter=10)
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class ParamTests(PySparkTestCase):
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def test_param(self):
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testParams = TestParams()
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maxIter = testParams.maxIter
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self.assertEqual(maxIter.name, "maxIter")
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self.assertEqual(maxIter.doc, "max number of iterations")
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self.assertTrue(maxIter.parent is testParams)
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def test_params(self):
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testParams = TestParams()
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maxIter = testParams.maxIter
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inputCol = testParams.inputCol
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params = testParams.params
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self.assertEqual(params, [inputCol, maxIter])
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self.assertTrue(testParams.hasDefault(maxIter))
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self.assertFalse(testParams.isSet(maxIter))
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self.assertTrue(testParams.isDefined(maxIter))
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self.assertEqual(testParams.getMaxIter(), 10)
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testParams.setMaxIter(100)
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self.assertTrue(testParams.isSet(maxIter))
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self.assertEquals(testParams.getMaxIter(), 100)
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self.assertFalse(testParams.hasDefault(inputCol))
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self.assertFalse(testParams.isSet(inputCol))
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self.assertFalse(testParams.isDefined(inputCol))
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with self.assertRaises(KeyError):
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testParams.getInputCol()
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self.assertEquals(
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testParams.explainParams(),
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"\n".join(["inputCol: input column name (undefined)",
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"maxIter: max number of iterations (default: 10, current: 100)"]))
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if __name__ == "__main__":
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unittest.main()
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