Update quality tooling for formatting (#21480)

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

tests/models/mobilebert/test_modeling_mobilebert.py

@@ -254,7 +254,6 @@ class MobileBertModelTester:
 
 @require_torch
 class MobileBertModelTest(ModelTesterMixin, unittest.TestCase):
-
     all_model_classes = (
         (
             MobileBertModel,

tests/models/mobilebert/test_modeling_tf_mobilebert.py

@@ -42,7 +42,6 @@ if is_tf_available():
 
 @require_tf
 class TFMobileBertModelTest(TFModelTesterMixin, unittest.TestCase):
-
     all_model_classes = (
         (
             TFMobileBertModel,

tests/models/mobilebert/test_tokenization_mobilebert.py

@@ -35,7 +35,6 @@ from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english
 # Copied from transformers.tests.models.bert.test_modeling_bert.py with Bert->MobileBert and pathfix
 @require_tokenizers
 class MobileBERTTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
-
     tokenizer_class = MobileBertTokenizer
     rust_tokenizer_class = MobileBertTokenizerFast
     test_rust_tokenizer = True
@@ -312,7 +311,6 @@ class MobileBERTTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
         text_with_chinese_char = "".join(list_of_commun_chinese_char)
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
-
                 kwargs["tokenize_chinese_chars"] = True
                 tokenizer_p = self.tokenizer_class.from_pretrained(pretrained_name, **kwargs)
                 tokenizer_r = self.rust_tokenizer_class.from_pretrained(pretrained_name, **kwargs)