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

* Refactored to remove un-necessary object base class.

* small fix.

src/transformers/models/deprecated/transfo_xl/tokenization_transfo_xl.py

@@ -511,7 +511,7 @@ class TransfoXLTokenizer(PreTrainedTokenizer):
             return symbols
 
 
-class LMOrderedIterator(object):
+class LMOrderedIterator:
     def __init__(self, data, bsz, bptt, device="cpu", ext_len=None):
         """
         data -- LongTensor -- the LongTensor is strictly ordered
@@ -570,7 +570,7 @@ class LMOrderedIterator(object):
         return self.get_fixlen_iter()
 
 
-class LMShuffledIterator(object):
+class LMShuffledIterator:
     def __init__(self, data, bsz, bptt, device="cpu", ext_len=None, shuffle=False):
         """
         data -- list[LongTensor] -- there is no order among the LongTensors
@@ -679,7 +679,7 @@ class LMMultiFileIterator(LMShuffledIterator):
                 yield batch
 
 
-class TransfoXLCorpus(object):
+class TransfoXLCorpus:
     @classmethod
     @torch_only_method
     def from_pretrained(cls, pretrained_model_name_or_path, cache_dir=None, *inputs, **kwargs):

src/transformers/models/detr/modeling_detr.py

@@ -2292,7 +2292,7 @@ def _max_by_axis(the_list):
     return maxes
 
 
-class NestedTensor(object):
+class NestedTensor:
     def __init__(self, tensors, mask: Optional[Tensor]):
         self.tensors = tensors
         self.mask = mask

src/transformers/models/distilbert/tokenization_distilbert.py

@@ -295,7 +295,7 @@ class DistilBertTokenizer(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.).
 
@@ -457,7 +457,7 @@ 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/dpt/convert_dinov2_depth_to_hf.py

@@ -200,7 +200,7 @@ name_to_url = {
 
 
 def get_original_pixel_values(image):
-    class CenterPadding(object):
+    class CenterPadding:
         def __init__(self, multiple):
             super().__init__()
             self.multiple = multiple

src/transformers/models/electra/tokenization_electra.py

@@ -284,7 +284,7 @@ class ElectraTokenizer(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):
 
 
 # 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/funnel/tokenization_funnel.py

@@ -315,7 +315,7 @@ class FunnelTokenizer(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.).
 
@@ -477,7 +477,7 @@ 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/gpt_neox_japanese/tokenization_gpt_neox_japanese.py

@@ -192,7 +192,7 @@ class GPTNeoXJapaneseTokenizer(PreTrainedTokenizer):
         return vocab_file, emoji_file
 
 
-class SubWordJapaneseTokenizer(object):
+class SubWordJapaneseTokenizer:
     """
     https://github.com/tanreinama/Japanese-BPEEncoder_V2 This tokenizer class is under MIT Lisence according to the
     original repository.

src/transformers/models/grounding_dino/modeling_grounding_dino.py

@@ -2617,7 +2617,7 @@ def sigmoid_focal_loss(inputs, targets, num_boxes, alpha: float = 0.25, gamma: f
 
 
 # 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/herbert/tokenization_herbert.py

@@ -113,7 +113,7 @@ def whitespace_tokenize(text):
 
 
 # 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.).
 

src/transformers/models/layoutlm/tokenization_layoutlm.py

@@ -285,7 +285,7 @@ class LayoutLMTokenizer(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.).
 
@@ -447,7 +447,7 @@ 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/layoutlmv2/tokenization_layoutlmv2.py

@@ -1323,7 +1323,7 @@ class LayoutLMv2Tokenizer(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.).
 
@@ -1485,7 +1485,7 @@ 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/lxmert/tokenization_lxmert.py

@@ -284,7 +284,7 @@ class LxmertTokenizer(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):
 
 
 # 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/mobilebert/tokenization_mobilebert.py

@@ -286,7 +286,7 @@ class MobileBertTokenizer(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.).
 
@@ -448,7 +448,7 @@ 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/mpnet/tokenization_mpnet.py

@@ -310,7 +310,7 @@ class MPNetTokenizer(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.).
 
@@ -472,7 +472,7 @@ 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/openai/tokenization_openai.py

@@ -43,7 +43,7 @@ def whitespace_tokenize(text):
 
 
 # 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.).
 

src/transformers/models/prophetnet/tokenization_prophetnet.py

@@ -38,7 +38,7 @@ def whitespace_tokenize(text):
 
 
 # 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.).
 
@@ -200,7 +200,7 @@ 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/roc_bert/tokenization_roc_bert.py

@@ -889,7 +889,7 @@ class RoCBertTokenizer(PreTrainedTokenizer):
 
 
 # Copied from  transformers.models.bert.tokenization_bert.BasicTokenizer with BasicTokenizer->RoCBertBasicTokenizer
-class RoCBertBasicTokenizer(object):
+class RoCBertBasicTokenizer:
     """
     Constructs a RoCBertBasicTokenizer that will run basic tokenization (punctuation splitting, lower casing, etc.).
 
@@ -1051,7 +1051,7 @@ class RoCBertBasicTokenizer(object):
 
 
 # Copied from  transformers.models.bert.tokenization_bert.WordpieceTokenizer with WordpieceTokenizer->RoCBertWordpieceTokenizer
-class RoCBertWordpieceTokenizer(object):
+class RoCBertWordpieceTokenizer:
     """Runs WordPiece tokenization."""
 
     def __init__(self, vocab, unk_token, max_input_chars_per_word=100):

src/transformers/models/roformer/tokenization_roformer.py

@@ -51,7 +51,7 @@ def whitespace_tokenize(text):
 
 
 # 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.).
 
@@ -213,7 +213,7 @@ 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/rt_detr/modeling_rt_detr.py

@@ -2452,7 +2452,7 @@ 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/sew_d/modeling_sew_d.py

@@ -555,7 +555,7 @@ class XSoftmax(torch.autograd.Function):
 
 
 # Copied from transformers.models.deberta.modeling_deberta.DropoutContext
-class DropoutContext(object):
+class DropoutContext:
     def __init__(self):
         self.dropout = 0
         self.mask = None