message: Limit the number of statements in exception raising test blocks to 1
diff: @@ -167,12 +167,11 @@ class SequenceFeaturesTest(test.TestCase, parameterized.TestCase):
  key='aaa', num_buckets=vocabulary_size)
  embedding_column_a = fc.embedding_column(
  categorical_column_a, dimension=2)
  -
  + sequence_input_layer = sfc.SequenceFeatures([embedding_column_a])
  with self.assertRaisesRegexp(
  ValueError,
  r'In embedding_column: aaa_embedding\. categorical_column must be of '
  r'type SequenceCategoricalColumn to use SequenceFeatures\.'):
  - sequence_input_layer = sfc.SequenceFeatures([embedding_column_a])
  _, _ = sequence_input_layer({'aaa': sparse_input})
  @test_util.run_in_graph_and_eager_modes
  @@ -267,11 +266,11 @@ class SequenceFeaturesTest(test.TestCase, parameterized.TestCase):
  shared_embedding_columns = fc.shared_embedding_columns_v2(
  [categorical_column_a, categorical_column_b], dimension=2)
  + sequence_input_layer = sfc.SequenceFeatures(shared_embedding_columns)
  with self.assertRaisesRegexp(
  ValueError,
  r'In embedding_column: aaa_shared_embedding\. categorical_column must '
  r'be of type SequenceCategoricalColumn to use SequenceFeatures\.'):
  - sequence_input_layer = sfc.SequenceFeatures(shared_embedding_columns)
  _, _ = sequence_input_layer({'aaa': sparse_input_a,
  'bbb': sparse_input_b})
  @@ -358,11 +357,11 @@ class SequenceFeaturesTest(test.TestCase, parameterized.TestCase):
  key='aaa', num_buckets=vocabulary_size)
  indicator_column_a = fc.indicator_column(categorical_column_a)
  + sequence_input_layer = sfc.SequenceFeatures([indicator_column_a])
  with self.assertRaisesRegexp(
  ValueError,
  r'In indicator_column: aaa_indicator\. categorical_column must be of '
  r'type SequenceCategoricalColumn to use SequenceFeatures\.'):
  - sequence_input_layer = sfc.SequenceFeatures([indicator_column_a])
  _, _ = sequence_input_layer({'aaa': sparse_input})
  @parameterized.named_parameters(
  @@ -468,8 +467,8 @@ class SequenceFeaturesTest(test.TestCase, parameterized.TestCase):
  with self.assertRaisesRegexp(
  errors.InvalidArgumentError, r'Condition x == y did not hold.*'):
  - _, sequence_length = sequence_input_layer({
  - 'aaa': sparse_input_a, 'bbb': sparse_input_b})
  + _, sequence_length = sequence_input_layer(
  + {'aaa': sparse_input_a, 'bbb': sparse_input_b})
  self.evaluate(sequence_length)
  @parameterized.named_parameters(
  @@ -661,11 +660,11 @@ class DenseFeaturesTest(test.TestCase):
  embedding_column_a = fc.embedding_column(
  categorical_column_a, dimension=2)
  + input_layer = dense_features.DenseFeatures([embedding_column_a])
  with self.assertRaisesRegexp(
  ValueError,
  r'In embedding_column: aaa_embedding\. categorical_column must not be '
  r'of type SequenceCategoricalColumn\.'):
  - input_layer = dense_features.DenseFeatures([embedding_column_a])
  _ = input_layer({'aaa': sparse_input})
  def test_indicator_column(self):
  @@ -682,11 +681,11 @@ class DenseFeaturesTest(test.TestCase):
  key='aaa', num_buckets=vocabulary_size)
  indicator_column_a = fc.indicator_column(categorical_column_a)
  + input_layer = dense_features.DenseFeatures([indicator_column_a])
  with self.assertRaisesRegexp(
  ValueError,
  r'In indicator_column: aaa_indicator\. categorical_column must not be '
  r'of type SequenceCategoricalColumn\.'):
  - input_layer = dense_features.DenseFeatures([indicator_column_a])
  _ = input_layer({'aaa': sparse_input})
  