Update repo to isort v5 (#6686)

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

examples/seq2seq/bertabs/run_summarization.py

@@ -44,9 +44,10 @@ def evaluate(args):
         reference_summaries = []
         generated_summaries = []
 
-        import rouge
         import nltk
 
+        import rouge
+
         nltk.download("punkt")
         rouge_evaluator = rouge.Rouge(
             metrics=["rouge-n", "rouge-l"],

examples/seq2seq/distillation.py

@@ -15,27 +15,27 @@ from transformers import BartConfig, BartForConditionalGeneration, MBartTokenize
 
 try:
     from .finetune import SummarizationModule, TranslationModule
-    from .initialization_utils import init_student, copy_layers
-    from .utils import (
-        use_task_specific_params,
-        pickle_load,
-        freeze_params,
-        assert_all_frozen,
-        any_requires_grad,
-        calculate_bleu_score,
-    )
     from .finetune import main as ft_main
+    from .initialization_utils import copy_layers, init_student
+    from .utils import (
+        any_requires_grad,
+        assert_all_frozen,
+        calculate_bleu_score,
+        freeze_params,
+        pickle_load,
+        use_task_specific_params,
+    )
 except ImportError:
     from finetune import SummarizationModule, TranslationModule
     from finetune import main as ft_main
-    from initialization_utils import init_student, copy_layers
+    from initialization_utils import copy_layers, init_student
     from utils import (
-        use_task_specific_params,
-        pickle_load,
-        freeze_params,
-        assert_all_frozen,
         any_requires_grad,
+        assert_all_frozen,
         calculate_bleu_score,
+        freeze_params,
+        pickle_load,
+        use_task_specific_params,
     )
 
 

examples/seq2seq/finetune.py

@@ -17,44 +17,43 @@ from transformers import MarianTokenizer, MBartTokenizer, T5ForConditionalGenera
 
 
 try:
-    from .utils import (
-        assert_all_frozen,
-        use_task_specific_params,
-        lmap,
-        flatten_list,
-        pickle_save,
-        save_git_info,
-        save_json,
-        freeze_params,
-        calculate_rouge,
-        get_git_info,
-        ROUGE_KEYS,
-        calculate_bleu_score,
-        Seq2SeqDataset,
-        TranslationDataset,
-        label_smoothed_nll_loss,
-    )
-
     from .callbacks import Seq2SeqLoggingCallback, get_checkpoint_callback, get_early_stopping_callback
-except ImportError:
-    from utils import (
+    from .utils import (
+        ROUGE_KEYS,
         Seq2SeqDataset,
         TranslationDataset,
         assert_all_frozen,
-        use_task_specific_params,
-        lmap,
+        calculate_bleu_score,
+        calculate_rouge,
         flatten_list,
+        freeze_params,
+        get_git_info,
+        label_smoothed_nll_loss,
+        lmap,
         pickle_save,
         save_git_info,
         save_json,
-        freeze_params,
-        calculate_rouge,
-        get_git_info,
-        ROUGE_KEYS,
-        calculate_bleu_score,
-        label_smoothed_nll_loss,
+        use_task_specific_params,
     )
+except ImportError:
     from callbacks import Seq2SeqLoggingCallback, get_checkpoint_callback, get_early_stopping_callback
+    from utils import (
+        ROUGE_KEYS,
+        Seq2SeqDataset,
+        TranslationDataset,
+        assert_all_frozen,
+        calculate_bleu_score,
+        calculate_rouge,
+        flatten_list,
+        freeze_params,
+        get_git_info,
+        label_smoothed_nll_loss,
+        lmap,
+        pickle_save,
+        save_git_info,
+        save_json,
+        use_task_specific_params,
+    )
 
 logger = logging.getLogger(__name__)
 

examples/seq2seq/run_eval.py

@@ -9,9 +9,9 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 
 try:
-    from .utils import calculate_rouge, use_task_specific_params, calculate_bleu_score, trim_batch
+    from .utils import calculate_bleu_score, calculate_rouge, trim_batch, use_task_specific_params
 except ImportError:
-    from utils import calculate_rouge, use_task_specific_params, calculate_bleu_score, trim_batch
+    from utils import calculate_bleu_score, calculate_rouge, trim_batch, use_task_specific_params
 
 DEFAULT_DEVICE = "cuda" if torch.cuda.is_available() else "cpu"