message: Switch MakeBatchedFeaturesDatasetTest to use TF combinations
diff: @@ -17,26 +17,29 @@ from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  +from absl.testing import parameterized
  import numpy as np
  from tensorflow.python.data.experimental.kernel_tests import reader_dataset_ops_test_base
  from tensorflow.python.data.experimental.ops import readers
  +from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import readers as core_readers
  from tensorflow.python.data.util import nest
  +from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  -from tensorflow.python.framework import test_util
  from tensorflow.python.ops import io_ops
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.platform import test
  -@test_util.run_all_in_graph_and_eager_modes
  class MakeBatchedFeaturesDatasetTest(
  - reader_dataset_ops_test_base.MakeBatchedFeaturesDatasetTestBase):
  + reader_dataset_ops_test_base.MakeBatchedFeaturesDatasetTestBase,
  + parameterized.TestCase):
  + @combinations.generate(test_base.default_test_combinations())
  def testRead(self):
  for batch_size in [1, 2]:
  for num_epochs in [1, 10]:
  @@ -85,6 +88,7 @@ class MakeBatchedFeaturesDatasetTest(
  with self.assertRaises(errors.OutOfRangeError):
  self._next_actual_batch()
  + @combinations.generate(test_base.default_test_combinations())
  def testReadWithEquivalentDataset(self):
  features = {
  "file": parsing_ops.FixedLenFeature([], dtypes.int64),
  @@ -103,6 +107,7 @@ class MakeBatchedFeaturesDatasetTest(
  with self.assertRaises(errors.OutOfRangeError):
  self.evaluate(next_element())
  + @combinations.generate(test_base.default_test_combinations())
  def testReadWithFusedShuffleRepeatDataset(self):
  num_epochs = 5
  total_records = num_epochs * self._num_records
  @@ -151,6 +156,7 @@ class MakeBatchedFeaturesDatasetTest(
  all_equal = all_equal and np.array_equal(batch1[i], batch2[i])
  self.assertFalse(all_equal)
  + @combinations.generate(test_base.default_test_combinations())
  def testParallelReadersAndParsers(self):
  num_epochs = 5
  for batch_size in [1, 2]:
  @@ -186,6 +192,7 @@ class MakeBatchedFeaturesDatasetTest(
  with self.assertRaises(errors.OutOfRangeError):
  self._next_actual_batch()
  + @combinations.generate(test_base.default_test_combinations())
  def testDropFinalBatch(self):
  for batch_size in [1, 2]:
  for num_epochs in [1, 10]:
  @@ -201,6 +208,7 @@ class MakeBatchedFeaturesDatasetTest(
  if isinstance(tensor, ops.Tensor): # Guard against SparseTensor.
  self.assertEqual(tensor.shape[0], batch_size)
  + @combinations.generate(test_base.default_test_combinations())
  def testIndefiniteRepeatShapeInference(self):
  dataset = self.make_batch_feature(
  filenames=self.test_filenames[0],
  @@ -213,6 +221,7 @@ class MakeBatchedFeaturesDatasetTest(
  if issubclass(clazz, ops.Tensor):
  self.assertEqual(32, shape[0])
  + @combinations.generate(test_base.default_test_combinations())
  def testOldStyleReader(self):
  with self.assertRaisesRegexp(
  TypeError, r"The `reader` argument must return a `Dataset` object. "
  