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/t5/test_modeling_flax_t5.py

@@ -46,6 +46,7 @@ if is_flax_available():
     from flax.core.frozen_dict import unfreeze
     from flax.training.common_utils import onehot
     from flax.traverse_util import flatten_dict
+
     from transformers import FLAX_MODEL_MAPPING, ByT5Tokenizer, T5Config, T5Tokenizer
     from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
     from transformers.models.t5.modeling_flax_t5 import (
@@ -81,7 +82,6 @@ class FlaxT5ModelTester:
         scope=None,
         decoder_layers=None,
     ):
-
         self.parent = parent
         self.batch_size = batch_size
         self.encoder_seq_length = encoder_seq_length
@@ -228,7 +228,6 @@ class FlaxT5ModelTester:
 
 @require_flax
 class FlaxT5ModelTest(FlaxModelTesterMixin, FlaxGenerationTesterMixin, unittest.TestCase):
-
     all_model_classes = (FlaxT5Model, FlaxT5ForConditionalGeneration) if is_flax_available() else ()
     all_generative_model_classes = (FlaxT5ForConditionalGeneration,) if is_flax_available() else ()
     is_encoder_decoder = True
@@ -489,7 +488,6 @@ class FlaxT5EncoderOnlyModelTester:
         decoder_start_token_id=0,
         scope=None,
     ):
-
         self.parent = parent
         self.batch_size = batch_size
         self.encoder_seq_length = encoder_seq_length
@@ -576,7 +574,6 @@ class FlaxT5EncoderOnlyModelTester:
 
 @require_flax
 class FlaxT5EncoderOnlyModelTest(FlaxModelTesterMixin, unittest.TestCase):
-
     all_model_classes = (FlaxT5EncoderModel,) if is_flax_available() else ()
     is_encoder_decoder = False
 

tests/models/t5/test_modeling_t5.py

@@ -73,7 +73,6 @@ class T5ModelTester:
         scope=None,
         decoder_layers=None,
     ):
-
         self.parent = parent
         self.batch_size = batch_size
         self.encoder_seq_length = encoder_seq_length
@@ -520,7 +519,6 @@ class T5ModelTester:
 
 @require_torch
 class T5ModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
-
     all_model_classes = (T5Model, T5ForConditionalGeneration) if is_torch_available() else ()
     all_generative_model_classes = (T5ForConditionalGeneration,) if is_torch_available() else ()
     all_parallelizable_model_classes = (T5Model, T5ForConditionalGeneration) if is_torch_available() else ()
@@ -703,7 +701,6 @@ class T5EncoderOnlyModelTester:
         pad_token_id=0,
         scope=None,
     ):
-
         self.parent = parent
         self.batch_size = batch_size
         self.encoder_seq_length = encoder_seq_length

tests/models/t5/test_modeling_tf_t5.py

@@ -240,7 +240,6 @@ class TFT5ModelTester:
 
 @require_tf
 class TFT5ModelTest(TFModelTesterMixin, unittest.TestCase):
-
     is_encoder_decoder = True
     all_model_classes = (TFT5Model, TFT5ForConditionalGeneration) if is_tf_available() else ()
     all_generative_model_classes = (TFT5ForConditionalGeneration,) if is_tf_available() else ()
@@ -346,7 +345,6 @@ class TFT5EncoderOnlyModelTester:
         pad_token_id=0,
         scope=None,
     ):
-
         self.parent = parent
         self.batch_size = batch_size
         self.encoder_seq_length = encoder_seq_length

tests/models/t5/test_tokenization_t5.py

@@ -38,7 +38,6 @@ else:
 @require_sentencepiece
 @require_tokenizers
 class T5TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
-
     tokenizer_class = T5Tokenizer
     rust_tokenizer_class = T5TokenizerFast
     test_rust_tokenizer = True
@@ -272,7 +271,6 @@ class T5TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
     def test_special_tokens_initialization(self):
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
-
                 added_tokens = [f"<extra_id_{i}>" for i in range(100)] + [AddedToken("<special>", lstrip=True)]
 
                 tokenizer_r = self.rust_tokenizer_class.from_pretrained(
@@ -306,7 +304,6 @@ class T5TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer()))
 
         for tokenizer_class, tokenizer_utils in tokenizer_list:
-
             with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer_utils.save_pretrained(tmp_dir)