aeb3649fb9
### What changes were proposed in this pull request? This replaces deprecated API usage in PySpark tests with the preferred APIs. These have been deprecated for some time and usage is not consistent within tests. - https://docs.python.org/3/library/unittest.html#deprecated-aliases ### Why are the changes needed? For consistency and eventual removal of deprecated APIs. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Existing tests Closes #30557 from BryanCutler/replace-deprecated-apis-in-tests. Authored-by: Bryan Cutler <cutlerb@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
77 lines
3.2 KiB
Python
77 lines
3.2 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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import unittest
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from pyspark.ml.image import ImageSchema
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from pyspark.testing.mlutils import SparkSessionTestCase
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from pyspark.sql import Row
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from pyspark.testing.utils import QuietTest
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class ImageFileFormatTest(SparkSessionTestCase):
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def test_read_images(self):
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data_path = 'data/mllib/images/origin/kittens'
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df = self.spark.read.format("image") \
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.option("dropInvalid", True) \
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.option("recursiveFileLookup", True) \
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.load(data_path)
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self.assertEqual(df.count(), 4)
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first_row = df.take(1)[0][0]
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# compare `schema.simpleString()` instead of directly compare schema,
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# because the df loaded from datasource may change schema column nullability.
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self.assertEqual(df.schema.simpleString(), ImageSchema.imageSchema.simpleString())
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self.assertEqual(df.schema["image"].dataType.simpleString(),
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ImageSchema.columnSchema.simpleString())
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array = ImageSchema.toNDArray(first_row)
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self.assertEqual(len(array), first_row[1])
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self.assertEqual(ImageSchema.toImage(array, origin=first_row[0]), first_row)
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expected = {'CV_8UC3': 16, 'Undefined': -1, 'CV_8U': 0, 'CV_8UC1': 0, 'CV_8UC4': 24}
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self.assertEqual(ImageSchema.ocvTypes, expected)
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expected = ['origin', 'height', 'width', 'nChannels', 'mode', 'data']
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self.assertEqual(ImageSchema.imageFields, expected)
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self.assertEqual(ImageSchema.undefinedImageType, "Undefined")
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with QuietTest(self.sc):
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self.assertRaisesRegex(
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TypeError,
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"image argument should be pyspark.sql.types.Row; however",
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lambda: ImageSchema.toNDArray("a"))
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with QuietTest(self.sc):
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self.assertRaisesRegex(
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ValueError,
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"image argument should have attributes specified in",
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lambda: ImageSchema.toNDArray(Row(a=1)))
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with QuietTest(self.sc):
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self.assertRaisesRegex(
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TypeError,
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"array argument should be numpy.ndarray; however, it got",
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lambda: ImageSchema.toImage("a"))
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if __name__ == "__main__":
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from pyspark.ml.tests.test_image import * # noqa: F401
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try:
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import xmlrunner # type: ignore[import]
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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