14ee57f33aa9a07fa6440c049fefd47099dbc5ae,tensorflow_transform/beam/impl_test.py,BeamImplTest,testNumericAnalyzersWithScalarInputs,#BeamImplTest#,410

Before Change


      }

    input_data = [{"a": 4}, {"a": 1}]
    input_metadata = self.toMetadata(
        {"a": tf.FixedLenFeature((), tf.int64, 0)})
    with beam_impl.Context(temp_dir=self.get_temp_dir()):
      transformed_dataset, _ = (
          (input_data, input_metadata) |
          beam_impl.AnalyzeAndTransformDataset(preprocessing_fn))

    expected_transformed_data = [
        {"min": 1, "max": 4, "sum": 5, "size": 2, "mean": 2.5},
        {"min": 1, "max": 4, "sum": 5, "size": 2, "mean": 2.5}]
    expected_transformed_metadata = self.toMetadata({
        "min": tf.FixedLenFeature((), tf.int64, None),
        "max": tf.FixedLenFeature((), tf.int64, None),
        "sum": tf.FixedLenFeature((), tf.int64, None),
        "size": tf.FixedLenFeature((), tf.int64, None),
        "mean": tf.FixedLenFeature((), tf.float64, None)
    })
    self.assertDatasetsEqual(
        transformed_dataset,
        (expected_transformed_data, expected_transformed_metadata))

After Change


      }

    input_data = [{"a": 4}, {"a": 1}]
    input_metadata = dataset_metadata.DatasetMetadata({
        "a": sch.ColumnSchema(tf.int64, [], sch.FixedColumnRepresentation())
    })
    expected_data = [
        {"min": 1, "max": 4, "sum": 5, "size": 2, "mean": 2.5},
        {"min": 1, "max": 4, "sum": 5, "size": 2, "mean": 2.5}
    ]
    expected_metadata = dataset_metadata.DatasetMetadata({
        "min": sch.ColumnSchema(tf.int64, [], sch.FixedColumnRepresentation()),
        "max": sch.ColumnSchema(tf.int64, [], sch.FixedColumnRepresentation()),
        "sum": sch.ColumnSchema(tf.int64, [], sch.FixedColumnRepresentation()),
        "size": sch.ColumnSchema(tf.int64, [], sch.FixedColumnRepresentation()),
        "mean": sch.ColumnSchema(tf.float64, [],
                                 sch.FixedColumnRepresentation())
    })
    self.assertAnalyzeAndTransformResults(
        input_data, input_metadata, preprocessing_fn, expected_data,
        expected_metadata)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 46

Instances


Project Name: tensorflow/transform
Commit Name: 14ee57f33aa9a07fa6440c049fefd47099dbc5ae
Time: 2017-04-26
Author: no-reply@google.com
File Name: tensorflow_transform/beam/impl_test.py
Class Name: BeamImplTest
Method Name: testNumericAnalyzersWithScalarInputs


Project Name: tensorflow/transform
Commit Name: 14ee57f33aa9a07fa6440c049fefd47099dbc5ae
Time: 2017-04-26
Author: no-reply@google.com
File Name: tensorflow_transform/beam/impl_test.py
Class Name: BeamImplTest
Method Name: testUniquesAnalyzer


Project Name: tensorflow/transform
Commit Name: 14ee57f33aa9a07fa6440c049fefd47099dbc5ae
Time: 2017-04-26
Author: no-reply@google.com
File Name: tensorflow_transform/beam/impl_test.py
Class Name: BeamImplTest
Method Name: testUniquesAnalyzerWithNDInputs


Project Name: tensorflow/transform
Commit Name: 14ee57f33aa9a07fa6440c049fefd47099dbc5ae
Time: 2017-04-26
Author: no-reply@google.com
File Name: tensorflow_transform/beam/impl_test.py
Class Name: BeamImplTest
Method Name: testNumericAnalyzersWithScalarInputs