Update repo to isort v5 (#6686)

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

tests/test_benchmark.py

@@ -8,10 +8,7 @@ from transformers.testing_utils import require_torch, torch_device
 
 
 if is_torch_available():
-    from transformers import (
-        PyTorchBenchmarkArguments,
-        PyTorchBenchmark,
-    )
+    from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
 
 
 @require_torch

tests/test_benchmark_tf.py

@@ -9,6 +9,7 @@ from transformers.testing_utils import require_tf
 
 if is_tf_available():
     import tensorflow as tf
+
     from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
 
 

tests/test_hf_api.py

@@ -20,7 +20,6 @@ import unittest
 
 import requests
 from requests.exceptions import HTTPError
-
 from transformers.hf_api import HfApi, HfFolder, ModelInfo, PresignedUrl, S3Obj
 
 

tests/test_modeling_albert.py

@@ -26,13 +26,13 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 if is_torch_available():
     from transformers import (
         AlbertConfig,
-        AlbertModel,
-        AlbertForPreTraining,
         AlbertForMaskedLM,
         AlbertForMultipleChoice,
+        AlbertForPreTraining,
+        AlbertForQuestionAnswering,
         AlbertForSequenceClassification,
         AlbertForTokenClassification,
-        AlbertForQuestionAnswering,
+        AlbertModel,
     )
     from transformers.modeling_albert import ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST
 

tests/test_modeling_auto.py

@@ -23,42 +23,42 @@ from transformers.testing_utils import DUMMY_UNKWOWN_IDENTIFIER, SMALL_MODEL_IDE
 if is_torch_available():
     from transformers import (
         AutoConfig,
-        BertConfig,
-        GPT2Config,
-        T5Config,
         AutoModel,
-        BertModel,
-        AutoModelForPreTraining,
-        BertForPreTraining,
         AutoModelForCausalLM,
-        GPT2LMHeadModel,
-        AutoModelWithLMHead,
         AutoModelForMaskedLM,
-        BertForMaskedLM,
-        RobertaForMaskedLM,
+        AutoModelForPreTraining,
+        AutoModelForQuestionAnswering,
         AutoModelForSeq2SeqLM,
-        T5ForConditionalGeneration,
         AutoModelForSequenceClassification,
-        BertForSequenceClassification,
-        AutoModelForQuestionAnswering,
-        BertForQuestionAnswering,
         AutoModelForTokenClassification,
+        AutoModelWithLMHead,
+        BertConfig,
+        BertForMaskedLM,
+        BertForPreTraining,
+        BertForQuestionAnswering,
+        BertForSequenceClassification,
         BertForTokenClassification,
+        BertModel,
+        GPT2Config,
+        GPT2LMHeadModel,
+        RobertaForMaskedLM,
+        T5Config,
+        T5ForConditionalGeneration,
     )
-    from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_LIST
-    from transformers.modeling_gpt2 import GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
-    from transformers.modeling_t5 import T5_PRETRAINED_MODEL_ARCHIVE_LIST
     from transformers.modeling_auto import (
-        MODEL_MAPPING,
+        MODEL_FOR_CAUSAL_LM_MAPPING,
+        MODEL_FOR_MASKED_LM_MAPPING,
         MODEL_FOR_PRETRAINING_MAPPING,
         MODEL_FOR_QUESTION_ANSWERING_MAPPING,
+        MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
         MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
         MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
+        MODEL_MAPPING,
         MODEL_WITH_LM_HEAD_MAPPING,
-        MODEL_FOR_CAUSAL_LM_MAPPING,
-        MODEL_FOR_MASKED_LM_MAPPING,
-        MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
     )
+    from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_LIST
+    from transformers.modeling_gpt2 import GPT2_PRETRAINED_MODEL_ARCHIVE_LIST
+    from transformers.modeling_t5 import T5_PRETRAINED_MODEL_ARCHIVE_LIST
 
 
 @require_torch

tests/test_modeling_bart.py

@@ -28,24 +28,25 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor
 
 if is_torch_available():
     import torch
+
     from transformers import (
         AutoModel,
         AutoModelForSequenceClassification,
         AutoTokenizer,
-        BartModel,
+        BartConfig,
         BartForConditionalGeneration,
-        BartForSequenceClassification,
         BartForQuestionAnswering,
-        BartConfig,
+        BartForSequenceClassification,
+        BartModel,
         BartTokenizer,
         BartTokenizerFast,
         pipeline,
     )
     from transformers.modeling_bart import (
-        shift_tokens_right,
-        invert_mask,
-        _prepare_bart_decoder_inputs,
         SinusoidalPositionalEmbedding,
+        _prepare_bart_decoder_inputs,
+        invert_mask,
+        shift_tokens_right,
     )
 PGE_ARTICLE = """ PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow."""
 

tests/test_modeling_camembert.py

@@ -21,6 +21,7 @@ from transformers.testing_utils import require_torch, slow, torch_device
 
 if is_torch_available():
     import torch
+
     from transformers import CamembertModel
 
 

tests/test_modeling_common.py

@@ -29,19 +29,19 @@ if is_torch_available():
     import torch
 
     from transformers import (
-        AdaptiveEmbedding,
-        PretrainedConfig,
-        PreTrainedModel,
-        BertConfig,
-        BertModel,
         BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
-        MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
-        MODEL_FOR_QUESTION_ANSWERING_MAPPING,
         MODEL_FOR_CAUSAL_LM_MAPPING,
         MODEL_FOR_MASKED_LM_MAPPING,
+        MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
+        MODEL_FOR_QUESTION_ANSWERING_MAPPING,
         MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
         MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
         MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
+        AdaptiveEmbedding,
+        BertConfig,
+        BertModel,
+        PretrainedConfig,
+        PreTrainedModel,
         top_k_top_p_filtering,
     )
 

tests/test_modeling_ctrl.py

@@ -24,7 +24,8 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 
 if is_torch_available():
     import torch
-    from transformers import CTRLConfig, CTRLModel, CTRL_PRETRAINED_MODEL_ARCHIVE_LIST, CTRLLMHeadModel
+
+    from transformers import CTRL_PRETRAINED_MODEL_ARCHIVE_LIST, CTRLConfig, CTRLLMHeadModel, CTRLModel
 
 
 class CTRLModelTester:

tests/test_modeling_distilbert.py

@@ -25,14 +25,14 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 
 if is_torch_available():
     from transformers import (
+        DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
         DistilBertConfig,
-        DistilBertModel,
         DistilBertForMaskedLM,
         DistilBertForMultipleChoice,
-        DistilBertForTokenClassification,
         DistilBertForQuestionAnswering,
         DistilBertForSequenceClassification,
-        DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
+        DistilBertForTokenClassification,
+        DistilBertModel,
     )
 
     class DistilBertModelTester(object):

tests/test_modeling_electra.py

@@ -26,13 +26,13 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 if is_torch_available():
     from transformers import (
         ElectraConfig,
-        ElectraModel,
         ElectraForMaskedLM,
-        ElectraForTokenClassification,
-        ElectraForPreTraining,
         ElectraForMultipleChoice,
-        ElectraForSequenceClassification,
+        ElectraForPreTraining,
         ElectraForQuestionAnswering,
+        ElectraForSequenceClassification,
+        ElectraForTokenClassification,
+        ElectraModel,
     )
     from transformers.modeling_electra import ELECTRA_PRETRAINED_MODEL_ARCHIVE_LIST
 

tests/test_modeling_encoder_decoder.py

@@ -27,17 +27,18 @@ from .test_modeling_roberta import RobertaModelTester
 
 
 if is_torch_available():
+    import numpy as np
+    import torch
+
     from transformers import (
-        BertModel,
         BertLMHeadModel,
+        BertModel,
+        EncoderDecoderConfig,
+        EncoderDecoderModel,
         GPT2LMHeadModel,
-        RobertaModel,
         RobertaForCausalLM,
-        EncoderDecoderModel,
-        EncoderDecoderConfig,
+        RobertaModel,
     )
-    import numpy as np
-    import torch
 
 
 @require_torch

tests/test_modeling_flaubert.py

@@ -26,13 +26,13 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 if is_torch_available():
     from transformers import (
         FlaubertConfig,
-        FlaubertModel,
-        FlaubertWithLMHeadModel,
+        FlaubertForMultipleChoice,
         FlaubertForQuestionAnswering,
         FlaubertForQuestionAnsweringSimple,
         FlaubertForSequenceClassification,
         FlaubertForTokenClassification,
-        FlaubertForMultipleChoice,
+        FlaubertModel,
+        FlaubertWithLMHeadModel,
     )
     from transformers.modeling_flaubert import FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST
 

tests/test_modeling_gpt2.py

@@ -25,12 +25,13 @@ from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r
 
 if is_torch_available():
     import torch
+
     from transformers import (
-        GPT2Config,
-        GPT2Model,
         GPT2_PRETRAINED_MODEL_ARCHIVE_LIST,
-        GPT2LMHeadModel,
+        GPT2Config,
         GPT2DoubleHeadsModel,
+        GPT2LMHeadModel,
+        GPT2Model,
     )
 
 

tests/test_modeling_longformer.py

@@ -25,14 +25,15 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention
 
 if is_torch_available():
     import torch
+
     from transformers import (
         LongformerConfig,
-        LongformerModel,
         LongformerForMaskedLM,
+        LongformerForMultipleChoice,
+        LongformerForQuestionAnswering,
         LongformerForSequenceClassification,
         LongformerForTokenClassification,
-        LongformerForQuestionAnswering,
-        LongformerForMultipleChoice,
+        LongformerModel,
         LongformerSelfAttention,
     )
 

tests/test_modeling_marian.py

@@ -24,18 +24,19 @@ from transformers.testing_utils import require_torch, slow, torch_device
 
 if is_torch_available():
     import torch
+
     from transformers import (
-        AutoTokenizer,
-        MarianConfig,
         AutoConfig,
         AutoModelWithLMHead,
-        MarianTokenizer,
+        AutoTokenizer,
+        MarianConfig,
         MarianMTModel,
+        MarianTokenizer,
     )
     from transformers.convert_marian_to_pytorch import (
+        ORG_NAME,
         convert_hf_name_to_opus_name,
         convert_opus_name_to_hf_name,
-        ORG_NAME,
     )
     from transformers.pipelines import TranslationPipeline
 

tests/test_modeling_mbart.py

@@ -9,12 +9,13 @@ from .test_modeling_bart import TOLERANCE, _assert_tensors_equal, _long_tensor
 
 if is_torch_available():
     import torch
+
     from transformers import (
         AutoModelForSeq2SeqLM,
+        AutoTokenizer,
+        BatchEncoding,
         MBartConfig,
         MBartForConditionalGeneration,
-        BatchEncoding,
-        AutoTokenizer,
     )
 
 

tests/test_modeling_mobilebert.py

@@ -25,16 +25,17 @@ from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r
 
 if is_torch_available():
     import torch
+
     from transformers import (
         MobileBertConfig,
-        MobileBertModel,
         MobileBertForMaskedLM,
+        MobileBertForMultipleChoice,
         MobileBertForNextSentencePrediction,
         MobileBertForPreTraining,
         MobileBertForQuestionAnswering,
         MobileBertForSequenceClassification,
         MobileBertForTokenClassification,
-        MobileBertForMultipleChoice,
+        MobileBertModel,
     )
 
 

tests/test_modeling_openai.py

@@ -25,12 +25,13 @@ from .test_modeling_common import ModelTesterMixin, ids_tensor
 
 if is_torch_available():
     import torch
+
     from transformers import (
-        OpenAIGPTConfig,
-        OpenAIGPTModel,
         OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_LIST,
-        OpenAIGPTLMHeadModel,
+        OpenAIGPTConfig,
         OpenAIGPTDoubleHeadsModel,
+        OpenAIGPTLMHeadModel,
+        OpenAIGPTModel,
     )
 
 

tests/test_modeling_reformer.py

@@ -23,18 +23,19 @@ from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r
 
 
 if is_torch_available():
+    import torch
+
     from transformers import (
+        REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
         ReformerConfig,
         ReformerForMaskedLM,
+        ReformerForQuestionAnswering,
+        ReformerForSequenceClassification,
+        ReformerLayer,
         ReformerModel,
         ReformerModelWithLMHead,
-        ReformerForSequenceClassification,
         ReformerTokenizer,
-        ReformerLayer,
-        ReformerForQuestionAnswering,
-        REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
     )
-    import torch
 
 
 class ReformerModelTester: