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#
# 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.
#
import unittest
from pyspark.ml import Pipeline
from pyspark.ml.classification import LogisticRegression, OneVsRest
from pyspark.ml.feature import VectorAssembler
from pyspark.ml.linalg import Vectors
from pyspark.ml.util import MetaAlgorithmReadWrite
from pyspark.testing.mlutils import SparkSessionTestCase
class MetaAlgorithmReadWriteTests(SparkSessionTestCase):
def test_getAllNestedStages(self):
def _check_uid_set_equal(stages, expected_stages):
uids = set(map(lambda x: x.uid, stages))
expected_uids = set(map(lambda x: x.uid, expected_stages))
self.assertEqual(uids, expected_uids)
df1 = self.spark.createDataFrame(
[
(Vectors.dense([1.0, 2.0]), 1.0),
(Vectors.dense([-1.0, -2.0]), 0.0),
],
["features", "label"],
)
df2 = self.spark.createDataFrame(
[
(1.0, 2.0, 1.0),
(1.0, 2.0, 0.0),
],
["a", "b", "label"],
)
vs = VectorAssembler(inputCols=["a", "b"], outputCol="features")
lr = LogisticRegression()
pipeline = Pipeline(stages=[vs, lr])
pipelineModel = pipeline.fit(df2)
ova = OneVsRest(classifier=lr)
ovaModel = ova.fit(df1)
ova_pipeline = Pipeline(stages=[vs, ova])
nested_pipeline = Pipeline(stages=[ova_pipeline])
_check_uid_set_equal(
MetaAlgorithmReadWrite.getAllNestedStages(pipeline), [pipeline, vs, lr]
)
_check_uid_set_equal(
MetaAlgorithmReadWrite.getAllNestedStages(pipelineModel),
[pipelineModel] + pipelineModel.stages,
)
_check_uid_set_equal(MetaAlgorithmReadWrite.getAllNestedStages(ova), [ova, lr])
_check_uid_set_equal(
MetaAlgorithmReadWrite.getAllNestedStages(ovaModel), [ovaModel, lr] + ovaModel.models
)
_check_uid_set_equal(
MetaAlgorithmReadWrite.getAllNestedStages(nested_pipeline),
[nested_pipeline, ova_pipeline, vs, ova, lr],
)
if __name__ == "__main__":
from pyspark.ml.tests.test_util import * # noqa: F401
try:
import xmlrunner
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)