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/lxmert/test_modeling_lxmert.py

@@ -129,7 +129,6 @@ class LxmertModelTester:
         self.num_hidden_layers = {"vision": r_layers, "cross_encoder": x_layers, "language": l_layers}
 
     def prepare_config_and_inputs(self):
-
         output_attentions = self.output_attentions
         input_ids = ids_tensor([self.batch_size, self.seq_length], vocab_size=self.vocab_size)
         visual_feats = torch.rand(self.batch_size, self.num_visual_features, self.visual_feat_dim, device=torch_device)
@@ -412,7 +411,6 @@ class LxmertModelTester:
         ans,
         output_attentions,
     ):
-
         start_labels = config.num_qa_labels
         num_large_labels = config.num_qa_labels * 2
         num_small_labels = int(config.num_qa_labels * 2)
@@ -532,7 +530,6 @@ class LxmertModelTester:
 
 @require_torch
 class LxmertModelTest(ModelTesterMixin, unittest.TestCase):
-
     all_model_classes = (LxmertModel, LxmertForPreTraining, LxmertForQuestionAnswering) if is_torch_available() else ()
 
     fx_compatible = True
@@ -741,7 +738,6 @@ class LxmertModelTest(ModelTesterMixin, unittest.TestCase):
         self.assertIsNotNone(attentions_vision.grad)
 
     def prepare_tf_inputs_from_pt_inputs(self, pt_inputs_dict):
-
         tf_inputs_dict = {}
         for key, value in pt_inputs_dict.items():
             # skip key that does not exist in tf

tests/models/lxmert/test_modeling_tf_lxmert.py

@@ -364,7 +364,6 @@ class TFLxmertModelTester(object):
 
 @require_tf
 class TFLxmertModelTest(TFModelTesterMixin, unittest.TestCase):
-
     all_model_classes = (TFLxmertModel, TFLxmertForPreTraining) if is_tf_available() else ()
     test_head_masking = False
     test_onnx = False
@@ -493,7 +492,6 @@ class TFLxmertModelTest(TFModelTesterMixin, unittest.TestCase):
 
         pt_inputs_dict = {}
         for key, value in tf_inputs_dict.items():
-
             if isinstance(value, dict):
                 pt_inputs_dict[key] = self.prepare_pt_inputs_from_tf_inputs(value)
             elif isinstance(value, (list, tuple)):

tests/models/lxmert/test_tokenization_lxmert.py

@@ -26,7 +26,6 @@ from ...test_tokenization_common import TokenizerTesterMixin
 
 @require_tokenizers
 class LxmertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
-
     tokenizer_class = LxmertTokenizer
     rust_tokenizer_class = LxmertTokenizerFast
     test_rust_tokenizer = True