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Diffstat (limited to 'python/pyspark/ml/tests.py')
-rw-r--r-- | python/pyspark/ml/tests.py | 115 |
1 files changed, 115 insertions, 0 deletions
diff --git a/python/pyspark/ml/tests.py b/python/pyspark/ml/tests.py new file mode 100644 index 0000000000..b627c2b4e9 --- /dev/null +++ b/python/pyspark/ml/tests.py @@ -0,0 +1,115 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +""" +Unit tests for Spark ML Python APIs. +""" + +import sys + +if sys.version_info[:2] <= (2, 6): + try: + import unittest2 as unittest + except ImportError: + sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier') + sys.exit(1) +else: + import unittest + +from pyspark.tests import ReusedPySparkTestCase as PySparkTestCase +from pyspark.sql import DataFrame +from pyspark.ml.param import Param +from pyspark.ml.pipeline import Transformer, Estimator, Pipeline + + +class MockDataset(DataFrame): + + def __init__(self): + self.index = 0 + + +class MockTransformer(Transformer): + + def __init__(self): + super(MockTransformer, self).__init__() + self.fake = Param(self, "fake", "fake", None) + self.dataset_index = None + self.fake_param_value = None + + def transform(self, dataset, params={}): + self.dataset_index = dataset.index + if self.fake in params: + self.fake_param_value = params[self.fake] + dataset.index += 1 + return dataset + + +class MockEstimator(Estimator): + + def __init__(self): + super(MockEstimator, self).__init__() + self.fake = Param(self, "fake", "fake", None) + self.dataset_index = None + self.fake_param_value = None + self.model = None + + def fit(self, dataset, params={}): + self.dataset_index = dataset.index + if self.fake in params: + self.fake_param_value = params[self.fake] + model = MockModel() + self.model = model + return model + + +class MockModel(MockTransformer, Transformer): + + def __init__(self): + super(MockModel, self).__init__() + + +class PipelineTests(PySparkTestCase): + + def test_pipeline(self): + dataset = MockDataset() + estimator0 = MockEstimator() + transformer1 = MockTransformer() + estimator2 = MockEstimator() + transformer3 = MockTransformer() + pipeline = Pipeline() \ + .setStages([estimator0, transformer1, estimator2, transformer3]) + pipeline_model = pipeline.fit(dataset, {estimator0.fake: 0, transformer1.fake: 1}) + self.assertEqual(0, estimator0.dataset_index) + self.assertEqual(0, estimator0.fake_param_value) + model0 = estimator0.model + self.assertEqual(0, model0.dataset_index) + self.assertEqual(1, transformer1.dataset_index) + self.assertEqual(1, transformer1.fake_param_value) + self.assertEqual(2, estimator2.dataset_index) + model2 = estimator2.model + self.assertIsNone(model2.dataset_index, "The model produced by the last estimator should " + "not be called during fit.") + dataset = pipeline_model.transform(dataset) + self.assertEqual(2, model0.dataset_index) + self.assertEqual(3, transformer1.dataset_index) + self.assertEqual(4, model2.dataset_index) + self.assertEqual(5, transformer3.dataset_index) + self.assertEqual(6, dataset.index) + + +if __name__ == "__main__": + unittest.main() |