Refactor: Removed un-necessary `object` base class (#32230)

* Refactored to remove un-necessary object base class.

* small fix.

src/transformers/models/splinter/tokenization_splinter.py

@@ -297,7 +297,7 @@ class SplinterTokenizer(PreTrainedTokenizer):
         return (vocab_file,)
 
 
-class BasicTokenizer(object):
+class BasicTokenizer:
     """
     Constructs a BasicTokenizer that will run basic tokenization (punctuation splitting, lower casing, etc.).
 
@@ -446,7 +446,7 @@ class BasicTokenizer(object):
         return "".join(output)
 
 
-class WordpieceTokenizer(object):
+class WordpieceTokenizer:
     """Runs WordPiece tokenization."""
 
     def __init__(self, vocab, unk_token, max_input_chars_per_word=100):

src/transformers/models/squeezebert/tokenization_squeezebert.py

@@ -285,7 +285,7 @@ class SqueezeBertTokenizer(PreTrainedTokenizer):
 
 
 # Copied from transformers.models.bert.tokenization_bert.BasicTokenizer
-class BasicTokenizer(object):
+class BasicTokenizer:
     """
     Constructs a BasicTokenizer that will run basic tokenization (punctuation splitting, lower casing, etc.).
 
@@ -446,7 +446,7 @@ class BasicTokenizer(object):
         return "".join(output)
 
 
-class WordpieceTokenizer(object):
+class WordpieceTokenizer:
     """Runs WordPiece tokenization."""
 
     def __init__(self, vocab, unk_token, max_input_chars_per_word=100):

src/transformers/models/table_transformer/modeling_table_transformer.py

@@ -1888,7 +1888,7 @@ def _max_by_axis(the_list):
 
 
 # Copied from transformers.models.detr.modeling_detr.NestedTensor
-class NestedTensor(object):
+class NestedTensor:
     def __init__(self, tensors, mask: Optional[Tensor]):
         self.tensors = tensors
         self.mask = mask

src/transformers/models/tapas/modeling_tapas.py

@@ -1550,7 +1550,7 @@ class AverageApproximationFunction(str, enum.Enum):
 # Beginning of everything related to segmented tensors
 
 
-class IndexMap(object):
+class IndexMap:
     """Index grouping entries within a tensor."""
 
     def __init__(self, indices, num_segments, batch_dims=0):

src/transformers/models/tapas/modeling_tf_tapas.py

@@ -1830,7 +1830,7 @@ class AverageApproximationFunction(str, enum.Enum):
 # Beginning of everything related to segmented tensors
 
 
-class IndexMap(object):
+class IndexMap:
     """Index grouping entries within a tensor."""
 
     def __init__(self, indices, num_segments, batch_dims=0):

src/transformers/models/tapas/tokenization_tapas.py

@@ -1961,7 +1961,7 @@ class TapasTokenizer(PreTrainedTokenizer):
 
 
 # Copied from transformers.models.bert.tokenization_bert.BasicTokenizer
-class BasicTokenizer(object):
+class BasicTokenizer:
     """
     Constructs a BasicTokenizer that will run basic tokenization (punctuation splitting, lower casing, etc.).
 
@@ -2123,7 +2123,7 @@ class BasicTokenizer(object):
 
 
 # Copied from transformers.models.bert.tokenization_bert.WordpieceTokenizer
-class WordpieceTokenizer(object):
+class WordpieceTokenizer:
     """Runs WordPiece tokenization."""
 
     def __init__(self, vocab, unk_token, max_input_chars_per_word=100):

src/transformers/models/yolos/modeling_yolos.py

@@ -1322,7 +1322,7 @@ def _max_by_axis(the_list):
 
 
 # Copied from transformers.models.detr.modeling_detr.NestedTensor
-class NestedTensor(object):
+class NestedTensor:
     def __init__(self, tensors, mask: Optional[Tensor]):
         self.tensors = tensors
         self.mask = mask

tests/models/ctrl/test_modeling_tf_ctrl.py

@@ -37,7 +37,7 @@ if is_tf_available():
     )
 
 
-class TFCTRLModelTester(object):
+class TFCTRLModelTester:
     def __init__(
         self,
         parent,

tests/models/deberta/test_modeling_deberta.py

@@ -34,7 +34,7 @@ if is_torch_available():
     )
 
 
-class DebertaModelTester(object):
+class DebertaModelTester:
     def __init__(
         self,
         parent,

tests/models/deberta_v2/test_modeling_deberta_v2.py

@@ -35,7 +35,7 @@ if is_torch_available():
     )
 
 
-class DebertaV2ModelTester(object):
+class DebertaV2ModelTester:
     def __init__(
         self,
         parent,

tests/models/distilbert/test_modeling_distilbert.py

@@ -40,7 +40,7 @@ if is_torch_available():
     from transformers.models.distilbert.modeling_distilbert import _create_sinusoidal_embeddings
 
 
-class DistilBertModelTester(object):
+class DistilBertModelTester:
     def __init__(
         self,
         parent,

tests/models/flaubert/test_modeling_flaubert.py

@@ -39,7 +39,7 @@ if is_torch_available():
     from transformers.models.flaubert.modeling_flaubert import create_sinusoidal_embeddings
 
 
-class FlaubertModelTester(object):
+class FlaubertModelTester:
     def __init__(
         self,
         parent,

tests/models/lxmert/test_modeling_tf_lxmert.py

@@ -34,7 +34,7 @@ if is_tf_available():
     from transformers.models.lxmert.modeling_tf_lxmert import TFLxmertForPreTraining, TFLxmertModel
 
 
-class TFLxmertModelTester(object):
+class TFLxmertModelTester:
     def __init__(
         self,
         parent,

tests/models/mobilebert/test_modeling_tf_mobilebert.py

@@ -84,7 +84,7 @@ class TFMobileBertModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.Te
 
         return inputs_dict
 
-    class TFMobileBertModelTester(object):
+    class TFMobileBertModelTester:
         def __init__(
             self,
             parent,

tests/models/squeezebert/test_modeling_squeezebert.py

@@ -37,7 +37,7 @@ if is_torch_available():
     )
 
 
-class SqueezeBertModelTester(object):
+class SqueezeBertModelTester:
     def __init__(
         self,
         parent,

tests/test_configuration_common.py

@@ -23,7 +23,7 @@ from transformers import is_torch_available
 from .utils.test_configuration_utils import config_common_kwargs
 
 
-class ConfigTester(object):
+class ConfigTester:
     def __init__(self, parent, config_class=None, has_text_modality=True, common_properties=None, **kwargs):
         self.parent = parent
         self.config_class = config_class