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/research_projects/rag/_test_finetune_rag.py

@@ -5,6 +5,7 @@ import sys
 from pathlib import Path
 
 import finetune_rag
+
 from transformers.file_utils import is_apex_available
 from transformers.testing_utils import (
     TestCasePlus,

examples/research_projects/rag/callbacks_rag.py

@@ -6,7 +6,6 @@ import pytorch_lightning as pl
 import torch
 from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
 from pytorch_lightning.utilities import rank_zero_only
-
 from utils_rag import save_json
 
 

examples/research_projects/rag/consolidate_rag_checkpoint.py

@@ -17,7 +17,6 @@ def consolidate(
     generator_tokenizer_name_or_path: str = None,
     question_encoder_tokenizer_name_or_path: str = None,
 ):
-
     if config_name_or_path is None:
         config_name_or_path = "facebook/rag-token-base" if model_type == "rag_token" else "facebook/rag-sequence-base"
 

examples/research_projects/rag/distributed_ray_retriever.py

@@ -2,6 +2,7 @@ import logging
 import random
 
 import ray
+
 from transformers import RagConfig, RagRetriever, RagTokenizer
 from transformers.models.rag.retrieval_rag import CustomHFIndex
 

examples/research_projects/rag/lightning_base.py

@@ -69,7 +69,7 @@ class BaseTransformer(pl.LightningModule):
         config=None,
         tokenizer=None,
         model=None,
-        **config_kwargs
+        **config_kwargs,
     ):
         """Initialize a model, tokenizer and config."""
         super().__init__()
@@ -356,7 +356,7 @@ def generic_train(
     extra_callbacks=[],
     checkpoint_callback=None,
     logging_callback=None,
-    **extra_train_kwargs
+    **extra_train_kwargs,
 ):
     pl.seed_everything(args.seed)
 

examples/research_projects/rag/test_distributed_retriever.py

@@ -7,10 +7,10 @@ import unittest
 from unittest import TestCase
 from unittest.mock import patch
 
+import faiss
 import numpy as np
 from datasets import Dataset
 
-import faiss
 from transformers import BartConfig, BartTokenizer, DPRConfig, DPRQuestionEncoderTokenizer, RagConfig
 from transformers.file_utils import is_datasets_available, is_faiss_available, is_psutil_available, is_torch_available
 from transformers.integrations import is_ray_available

examples/research_projects/rag/use_own_knowledge_dataset.py

@@ -6,10 +6,10 @@ from pathlib import Path
 from tempfile import TemporaryDirectory
 from typing import List, Optional
 
+import faiss
 import torch
 from datasets import Features, Sequence, Value, load_dataset
 
-import faiss
 from transformers import (
     DPRContextEncoder,
     DPRContextEncoderTokenizerFast,
@@ -56,7 +56,6 @@ def main(
     processing_args: "ProcessingArguments",
     index_hnsw_args: "IndexHnswArguments",
 ):
-
     ######################################
     logger.info("Step 1 - Create the dataset")
     ######################################