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

examples/pytorch/question-answering/run_qa.py

@@ -25,11 +25,12 @@ from dataclasses import dataclass, field
 from typing import Optional
 
 import datasets
-from datasets import load_dataset
-
 import evaluate
-import transformers
+from datasets import load_dataset
 from trainer_qa import QuestionAnsweringTrainer
+from utils_qa import postprocess_qa_predictions
+
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForQuestionAnswering,
@@ -45,7 +46,6 @@ from transformers import (
 from transformers.trainer_utils import get_last_checkpoint
 from transformers.utils import check_min_version, send_example_telemetry
 from transformers.utils.versions import require_version
-from utils_qa import postprocess_qa_predictions
 
 
 # Will error if the minimal version of Transformers is not installed. Remove at your own risks.

examples/pytorch/question-answering/run_qa_beam_search.py

@@ -25,11 +25,12 @@ from dataclasses import dataclass, field
 from typing import Optional
 
 import datasets
-from datasets import load_dataset
-
 import evaluate
-import transformers
+from datasets import load_dataset
 from trainer_qa import QuestionAnsweringTrainer
+from utils_qa import postprocess_qa_predictions_with_beam_search
+
+import transformers
 from transformers import (
     DataCollatorWithPadding,
     EvalPrediction,
@@ -44,7 +45,6 @@ from transformers import (
 from transformers.trainer_utils import get_last_checkpoint
 from transformers.utils import check_min_version, send_example_telemetry
 from transformers.utils.versions import require_version
-from utils_qa import postprocess_qa_predictions_with_beam_search
 
 
 # Will error if the minimal version of Transformers is not installed. Remove at your own risks.

examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py

@@ -27,18 +27,19 @@ import random
 from pathlib import Path
 
 import datasets
+import evaluate
 import numpy as np
 import torch
-from datasets import load_dataset
-from torch.utils.data import DataLoader
-from tqdm.auto import tqdm
-
-import evaluate
-import transformers
 from accelerate import Accelerator
 from accelerate.logging import get_logger
 from accelerate.utils import set_seed
+from datasets import load_dataset
 from huggingface_hub import Repository, create_repo
+from torch.utils.data import DataLoader
+from tqdm.auto import tqdm
+from utils_qa import postprocess_qa_predictions_with_beam_search
+
+import transformers
 from transformers import (
     AdamW,
     DataCollatorWithPadding,
@@ -52,7 +53,6 @@ from transformers import (
 )
 from transformers.utils import check_min_version, get_full_repo_name, send_example_telemetry
 from transformers.utils.versions import require_version
-from utils_qa import postprocess_qa_predictions_with_beam_search
 
 
 # Will error if the minimal version of Transformers is not installed. Remove at your own risks.

examples/pytorch/question-answering/run_qa_no_trainer.py

@@ -27,18 +27,19 @@ import random
 from pathlib import Path
 
 import datasets
+import evaluate
 import numpy as np
 import torch
-from datasets import load_dataset
-from torch.utils.data import DataLoader
-from tqdm.auto import tqdm
-
-import evaluate
-import transformers
 from accelerate import Accelerator
 from accelerate.logging import get_logger
 from accelerate.utils import set_seed
+from datasets import load_dataset
 from huggingface_hub import Repository, create_repo
+from torch.utils.data import DataLoader
+from tqdm.auto import tqdm
+from utils_qa import postprocess_qa_predictions
+
+import transformers
 from transformers import (
     CONFIG_MAPPING,
     MODEL_MAPPING,
@@ -53,7 +54,6 @@ from transformers import (
 )
 from transformers.utils import check_min_version, get_full_repo_name, send_example_telemetry
 from transformers.utils.versions import require_version
-from utils_qa import postprocess_qa_predictions
 
 
 # Will error if the minimal version of Transformers is not installed. Remove at your own risks.

examples/pytorch/question-answering/run_seq2seq_qa.py

@@ -25,11 +25,11 @@ from dataclasses import dataclass, field
 from typing import List, Optional, Tuple
 
 import datasets
-from datasets import load_dataset
-
 import evaluate
-import transformers
+from datasets import load_dataset
 from trainer_seq2seq_qa import QuestionAnsweringSeq2SeqTrainer
+
+import transformers
 from transformers import (
     AutoConfig,
     AutoModelForSeq2SeqLM,