Update repo to isort v5 (#6686)

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

tests/test_modeling_tf_xlnet.py

@@ -28,13 +28,13 @@ if is_tf_available():
     import tensorflow as tf
 
     from transformers.modeling_tf_xlnet import (
-        TFXLNetModel,
-        TFXLNetLMHeadModel,
+        TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
+        TFXLNetForMultipleChoice,
+        TFXLNetForQuestionAnsweringSimple,
         TFXLNetForSequenceClassification,
         TFXLNetForTokenClassification,
-        TFXLNetForQuestionAnsweringSimple,
-        TFXLNetForMultipleChoice,
-        TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
+        TFXLNetLMHeadModel,
+        TFXLNetModel,
     )
 
 

tests/test_modeling_transfo_xl.py

@@ -25,7 +25,8 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor
 
 if is_torch_available():
     import torch
-    from transformers import TransfoXLConfig, TransfoXLModel, TransfoXLLMHeadModel
+
+    from transformers import TransfoXLConfig, TransfoXLLMHeadModel, TransfoXLModel
     from transformers.modeling_transfo_xl import TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST
 
 

tests/test_modeling_xlm.py

@@ -25,15 +25,16 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 
 if is_torch_available():
     import torch
+
     from transformers import (
         XLMConfig,
-        XLMModel,
-        XLMWithLMHeadModel,
-        XLMForTokenClassification,
+        XLMForMultipleChoice,
         XLMForQuestionAnswering,
-        XLMForSequenceClassification,
         XLMForQuestionAnsweringSimple,
-        XLMForMultipleChoice,
+        XLMForSequenceClassification,
+        XLMForTokenClassification,
+        XLMModel,
+        XLMWithLMHeadModel,
     )
     from transformers.modeling_xlm import XLM_PRETRAINED_MODEL_ARCHIVE_LIST
 

tests/test_modeling_xlm_roberta.py

@@ -22,6 +22,7 @@ from transformers.testing_utils import slow
 
 if is_torch_available():
     import torch
+
     from transformers import XLMRobertaModel
 
 

tests/test_modeling_xlnet.py

@@ -29,13 +29,13 @@ if is_torch_available():
 
     from transformers import (
         XLNetConfig,
-        XLNetModel,
-        XLNetLMHeadModel,
         XLNetForMultipleChoice,
-        XLNetForSequenceClassification,
-        XLNetForTokenClassification,
         XLNetForQuestionAnswering,
         XLNetForQuestionAnsweringSimple,
+        XLNetForSequenceClassification,
+        XLNetForTokenClassification,
+        XLNetLMHeadModel,
+        XLNetModel,
     )
     from transformers.modeling_xlnet import XLNET_PRETRAINED_MODEL_ARCHIVE_LIST
 

tests/test_optimization_tf.py

@@ -8,7 +8,8 @@ if is_tf_available():
     import tensorflow as tf
     from tensorflow.python.eager import context
     from tensorflow.python.framework import ops
-    from transformers import create_optimizer, GradientAccumulator
+
+    from transformers import GradientAccumulator, create_optimizer
 
 
 @require_tf

tests/test_tokenization_common.py

@@ -28,11 +28,7 @@ from transformers.tokenization_utils import AddedToken
 
 
 if TYPE_CHECKING:
-    from transformers import (
-        PretrainedConfig,
-        PreTrainedModel,
-        TFPreTrainedModel,
-    )
+    from transformers import PretrainedConfig, PreTrainedModel, TFPreTrainedModel
 
 
 def merge_model_tokenizer_mappings(
@@ -1398,6 +1394,7 @@ class TokenizerTesterMixin:
     @require_torch
     def test_torch_encode_plus_sent_to_model(self):
         import torch
+
         from transformers import MODEL_MAPPING, TOKENIZER_MAPPING
 
         MODEL_TOKENIZER_MAPPING = merge_model_tokenizer_mappings(MODEL_MAPPING, TOKENIZER_MAPPING)

tests/test_tokenization_reformer.py

@@ -232,7 +232,8 @@ class ReformerTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
     @require_torch
     def test_torch_encode_plus_sent_to_model(self):
         import torch
-        from transformers import ReformerModel, ReformerConfig
+
+        from transformers import ReformerConfig, ReformerModel
 
         # Build sequence
         first_ten_tokens = list(self.big_tokenizer.get_vocab().keys())[:10]

tests/test_tokenization_transfo_xl.py

@@ -24,7 +24,7 @@ from .test_tokenization_common import TokenizerTesterMixin
 
 
 if is_torch_available():
-    from transformers.tokenization_transfo_xl import TransfoXLTokenizer, VOCAB_FILES_NAMES
+    from transformers.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
 
 
 @require_torch