Fix pylint errors

Author: vijayphoenix

tensorflow_datasets/core/decode/base_test.py

@@ -64,7 +64,7 @@ def decode_crop(serialized_image, feature):
     with tf.io.gfile.GFile(image_path, 'rb') as f:
       serialized_img = f.read()
 
-    self.assertFeature(
+    self.assert_feature(
         # Image with statically defined shape
         feature=features_lib.Image(shape=(30, 60, 3), encoding_format='jpeg'),
         shape=(30, 60, 3),
@@ -98,7 +98,7 @@ def test_video_custom_decode(self):
     with tf.io.gfile.GFile(image_path, 'rb') as f:
       serialized_img = f.read()
 
-    self.assertFeature(
+    self.assert_feature(
         # Image with statically defined shape
         feature=features_lib.Video(shape=(None, 30, 60, 3)),
         shape=(None, 30, 60, 3),
@@ -115,7 +115,7 @@ def test_video_custom_decode(self):
     )
 
     # Test with FeatureDict
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.FeaturesDict({
             'image': features_lib.Image(
                 shape=(30, 60, 3), encoding_format='jpeg'),

tensorflow_datasets/core/download/kaggle_test.py

@@ -44,15 +44,15 @@ def test_competition_download(self):
 
   def test_competition_download_404(self):
     with testing.mock_kaggle_api(err_msg="404 - Not found"):
-      with self.assertLogs(
+      with self.assert_logs(
           "spelled the competition name correctly", level="error"):
         downloader = kaggle.KaggleCompetitionDownloader("digit-recognizer")
         with self.assertRaises(subprocess.CalledProcessError):
           _ = downloader.competition_files
 
   def test_competition_download_error(self):
     with testing.mock_kaggle_api(err_msg="Some error"):
-      with self.assertLogs("install the kaggle API", level="error"):
+      with self.assert_logs("install the kaggle API", level="error"):
         downloader = kaggle.KaggleCompetitionDownloader("digit-recognizer")
         with self.assertRaises(subprocess.CalledProcessError):
           _ = downloader.competition_files

tensorflow_datasets/core/example_serializer_test.py

@@ -36,7 +36,7 @@ def assertRaggedFieldEqual(self, dict1, dict2):
     self.assertIsInstance(dict2, dict)
     self.assertEqual(set(dict1.keys()), set(dict2.keys()))
     for k, (field1, field2) in py_utils.zip_dict(dict1, dict2):
-      with self._subTest(k):
+      with self._sub_test(k):
         # Compare the example_data
         self.assertAllEqual(field1[0], field2[0])
         # Compare the tensor_info

tensorflow_datasets/core/features/audio_feature_test.py

@@ -40,7 +40,7 @@ def create_np_audio(self):
   def test_numpy_array(self):
     np_audio = self.create_np_audio()
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Audio(),
         shape=(None,),
         dtype=tf.int64,
@@ -65,7 +65,7 @@ def test_wav_file(self):
     _, tmp_file = tempfile.mkstemp()
     self.write_wave_file(np_audio, tmp_file)
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Audio(file_format="wav"),
         shape=(None,),
         dtype=tf.int64,
@@ -85,7 +85,7 @@ def test_file_object(self):
     class GFileWithSeekOnRead(tf.io.gfile.GFile):
       """Wrapper around GFile which is reusable across multiple read() calls.
 
-      This is needed because assertFeature reuses the same
+      This is needed because assert_feature reuses the same
       FeatureExpectationItem several times.
       """
 
@@ -95,7 +95,7 @@ def read(self, *args, **kwargs):
         return data_read
 
     with GFileWithSeekOnRead(tmp_file, "rb") as file_obj:
-      self.assertFeature(
+      self.assert_feature(
           feature=features.Audio(file_format="wav"),
           shape=(None,),
           dtype=tf.int64,

tensorflow_datasets/core/features/bounding_boxes_test.py

@@ -31,7 +31,7 @@ class BBoxFeatureTest(testing.FeatureExpectationsTestCase):
 
   def test_feature(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features.BBoxFeature(),
         shape=(4,),
         dtype=tf.float32,

tensorflow_datasets/core/features/class_label_feature_test.py

@@ -30,7 +30,7 @@
 class ClassLabelFeatureTest(testing.FeatureExpectationsTestCase):
 
   def test_feature(self):
-    self.assertFeature(
+    self.assert_feature(
         feature=features.ClassLabel(num_classes=10),
         dtype=tf.int64,
         shape=(),
@@ -58,7 +58,7 @@ def test_feature(self):
 
   def test_labels(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features.ClassLabel(names=['left', 'right']),
         dtype=tf.int64,
         shape=(),

tensorflow_datasets/core/features/features_test.py

@@ -96,7 +96,7 @@ def test_tensor_info(self):
 
   def test_fdict(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.FeaturesDict({
             'input': AnInputConnector(),
             'output': AnOutputConnector(),
@@ -239,7 +239,7 @@ def test_shape_static(self):
         [4, 5, 6],
     ]
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(2, 3), dtype=tf.float32),
         dtype=tf.float32,
         shape=(2, 3),
@@ -274,7 +274,7 @@ def test_shape_dynamic(self):
     np_input_dynamic_1 = np.random.randint(256, size=(2, 3, 2), dtype=np.int32)
     np_input_dynamic_2 = np.random.randint(256, size=(5, 3, 2), dtype=np.int32)
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(None, 3, 2), dtype=tf.int32),
         dtype=tf.int32,
         shape=(None, 3, 2),
@@ -299,7 +299,7 @@ def test_shape_dynamic(self):
 
   def test_bool_flat(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(), dtype=tf.bool),
         dtype=tf.bool,
         shape=(),
@@ -325,7 +325,7 @@ def test_bool_flat(self):
 
   def test_bool_array(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(3,), dtype=tf.bool),
         dtype=tf.bool,
         shape=(3,),
@@ -345,7 +345,7 @@ def test_string(self):
     nonunicode_text = 'hello world'
     unicode_text = u'你好'
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(), dtype=tf.string),
         shape=(),
         dtype=tf.string,
@@ -373,7 +373,7 @@ def test_string(self):
         ],
     )
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Tensor(shape=(2, 1), dtype=tf.string),
         shape=(2, 1),
         dtype=tf.string,

tensorflow_datasets/core/features/image_feature_test.py

@@ -51,7 +51,7 @@ def test_images(self, dtype):
     if dtype == tf.uint16:
       img_file_expected_content *= 257  # Scale int16 images
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features_lib.Image(dtype=dtype),
         shape=(None, None, 3),
         dtype=dtype,
@@ -96,7 +96,7 @@ def test_image_shaped(self):
 
     img_shaped = randint(256, size=(32, 64, 3), dtype=np.uint8)
 
-    self.assertFeature(
+    self.assert_feature(
         # Image with statically defined shape
         feature=features_lib.Image(shape=(32, 64, 3)),
         shape=(32, 64, 3),

tensorflow_datasets/core/features/sequence_feature_test.py

@@ -32,7 +32,7 @@ class SequenceDictFeatureTest(testing.FeatureExpectationsTestCase):
 
   def test_int(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence({'int': tf.int32}, length=3),
         shape={'int': (3,)},
         dtype={'int': tf.int32},
@@ -70,7 +70,7 @@ def test_int(self):
 
   def test_label(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence({
             'label': feature_lib.ClassLabel(names=['left', 'right']),
         }, length=None),
@@ -99,7 +99,7 @@ def test_label(self):
 
   def test_nested(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence({
             'a': tf.string,
             'b': {
@@ -218,10 +218,10 @@ def test_encoding(self):
     def to_ragged(ex):
       ex['a']['c'] = tf.ragged.constant(ex['a']['c'])
       return ex
-    self.assertAllEqualNested(to_ragged(ex1), out)
-    self.assertAllEqualNested(to_ragged(ex2), out)
-    self.assertAllEqualNested(to_ragged(ex3), out)
-    self.assertAllEqualNested(to_ragged(ex4), out)
+    self.assert_all_equal_nested(to_ragged(ex1), out)
+    self.assert_all_equal_nested(to_ragged(ex2), out)
+    self.assert_all_equal_nested(to_ragged(ex3), out)
+    self.assert_all_equal_nested(to_ragged(ex4), out)
 
     # Should raise error if two sequences do not have the same length.
     with self.assertRaisesWithPredicateMatch(
@@ -233,14 +233,14 @@ def to_ragged(ex):
 
     # Empty sequence should create the correct number of dimension
     ex2 = f.encode_example([])
-    self.assertAllEqualNested(ex2, {
+    self.assert_all_equal_nested(ex2, {
         'a': {'c': np.zeros((0, 0), np.int64)},
         'b': np.zeros((0,), np.int64),
     })
 
   def test_2lvl_sequences_mixed(self):
     # Mix of sequence and non-sequence
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence({
             'a': feature_lib.Sequence(tf.int32),
             'b': tf.int32,
@@ -269,7 +269,7 @@ def test_2lvl_sequences_mixed(self):
 
   def test_2lvl_sequences(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence(
             feature_lib.Sequence(
                 feature_lib.Tensor(shape=(2,), dtype=tf.int32),
@@ -336,7 +336,7 @@ def test_2lvl_sequences(self):
 
   def test_2lvl_sequences_string(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence(
             feature_lib.Sequence(tf.string),
         ),
@@ -379,7 +379,7 @@ def test_2lvl_sequences_string(self):
 
   def test_3lvl_sequence(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence(
             feature_lib.Sequence(
                 feature_lib.Sequence(tf.int32),
@@ -420,7 +420,7 @@ def test_image(self):
     ]
     imgs_stacked = np.stack(imgs)
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence({
             'image': feature_lib.Image(shape=(128, 100, 3)),
         }, length=None),
@@ -458,7 +458,7 @@ class SequenceFeatureTest(testing.FeatureExpectationsTestCase):
 
   def test_int(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence(tf.int32, length=3),
         shape=(3,),
         dtype=tf.int32,
@@ -484,7 +484,7 @@ def test_int(self):
 
   def test_label(self):
 
-    self.assertFeature(
+    self.assert_feature(
         feature=feature_lib.Sequence(
             feature_lib.ClassLabel(names=['left', 'right']),
         ),

tensorflow_datasets/core/features/text_feature_test.py

@@ -35,7 +35,7 @@ def test_text(self):
     nonunicode_text = 'hello world'
     unicode_text = u'你好'
 
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Text(),
         shape=(),
         dtype=tf.string,
@@ -62,7 +62,7 @@ def test_text_encoded(self):
     unicode_text = u'你好'
 
     # Unicode integer-encoded by byte
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Text(encoder=text_encoder.ByteTextEncoder()),
         shape=(None,),
         dtype=tf.int64,

tensorflow_datasets/core/features/translation_feature_test.py

@@ -42,7 +42,7 @@
 class TranslationFeatureTest(testing.FeatureExpectationsTestCase):
 
   def test_translation(self):
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Translation(["en", "zh"]),
         shape={"en": (), "zh": ()},
         dtype={"en": tf.string, "zh": tf.string},
@@ -57,7 +57,7 @@ def test_translation(self):
 
   def test_translation_encoded(self):
     # Unicode integer-encoded by byte
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Translation(
             languages=["en", "zh"],
             encoder=text_encoder.ByteTextEncoder()),
@@ -77,7 +77,7 @@ def test_translation_encoded(self):
 
   def test_translation_multiple_encoders(self):
     # Unicode integer-encoded by byte
-    self.assertFeature(
+    self.assert_feature(
         feature=features.Translation(
             languages=["en", "zh"],
             encoder=[text_encoder.TokenTextEncoder(["hello", " "]),
@@ -100,7 +100,7 @@ class TranslationVariableLanguagesFeatureTest(
     testing.FeatureExpectationsTestCase):
 
   def test_translation_variable_languages_nolist(self):
-    self.assertFeature(
+    self.assert_feature(
         feature=features.TranslationVariableLanguages(),
         shape={"language": (None,), "translation": (None,)},
         dtype={"language": tf.string, "translation": tf.string},
@@ -130,7 +130,7 @@ def test_translation_variable_languages_nolist(self):
     )
 
   def test_translation_variable_languages_list(self):
-    self.assertFeature(
+    self.assert_feature(
         feature=features.TranslationVariableLanguages(
             languages=["en", "de", "zh"]),
         shape={"language": (None,), "translation": (None,)},