85 lines
3.1 KiB
Python
85 lines
3.1 KiB
Python
|
#
|
||
|
# 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., 2.]), 1.0),
|
||
|
(Vectors.dense([-1., -2.]), 0.0),
|
||
|
], ['features', 'label'])
|
||
|
df2 = self.spark.createDataFrame([
|
||
|
(1., 2., 1.0),
|
||
|
(1., 2., 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 # type: ignore[import]
|
||
|
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
|
||
|
except ImportError:
|
||
|
testRunner = None
|
||
|
unittest.main(testRunner=testRunner, verbosity=2)
|