Update repo to isort v5 (#6686)

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

src/transformers/data/datasets/glue.py

@@ -6,9 +6,10 @@ from enum import Enum
 from typing import List, Optional, Union
 
 import torch
-from filelock import FileLock
 from torch.utils.data.dataset import Dataset
 
+from filelock import FileLock
+
 from ...tokenization_bart import BartTokenizer, BartTokenizerFast
 from ...tokenization_roberta import RobertaTokenizer, RobertaTokenizerFast
 from ...tokenization_utils import PreTrainedTokenizer

src/transformers/data/datasets/language_modeling.py

@@ -4,9 +4,10 @@ import pickle
 import time
 
 import torch
-from filelock import FileLock
 from torch.utils.data.dataset import Dataset
 
+from filelock import FileLock
+
 from ...tokenization_utils import PreTrainedTokenizer
 
 

src/transformers/data/datasets/squad.py

@@ -6,9 +6,10 @@ from enum import Enum
 from typing import Dict, List, Optional, Union
 
 import torch
-from filelock import FileLock
 from torch.utils.data.dataset import Dataset
 
+from filelock import FileLock
+
 from ...modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
 from ...tokenization_utils import PreTrainedTokenizer
 from ..processors.squad import SquadFeatures, SquadV1Processor, SquadV2Processor, squad_convert_examples_to_features

src/transformers/data/metrics/__init__.py

@@ -15,8 +15,9 @@
 # limitations under the License.
 
 try:
+    from sklearn.metrics import f1_score, matthews_corrcoef
+
     from scipy.stats import pearsonr, spearmanr
-    from sklearn.metrics import matthews_corrcoef, f1_score
 
     _has_sklearn = True
 except (AttributeError, ImportError):

src/transformers/data/test_generation_utils.py

@@ -11,10 +11,7 @@ from transformers.testing_utils import require_torch
 if is_torch_available():
     import torch
 
-    from transformers import (
-        MarianConfig,
-        MarianMTModel,
-    )
+    from transformers import MarianConfig, MarianMTModel
 
 
 @require_torch

src/transformers/file_utils.py

@@ -24,9 +24,10 @@ from urllib.parse import urlparse
 from zipfile import ZipFile, is_zipfile
 
 import numpy as np
+from tqdm.auto import tqdm
+
 import requests
 from filelock import FileLock
-from tqdm.auto import tqdm
 
 from . import __version__
 

src/transformers/hf_api.py

@@ -19,9 +19,10 @@ import os
 from os.path import expanduser
 from typing import Dict, List, Optional, Tuple
 
-import requests
 from tqdm import tqdm
 
+import requests
+
 
 ENDPOINT = "https://huggingface.co"
 

src/transformers/modeling_electra.py

@@ -50,6 +50,7 @@ def load_tf_weights_in_electra(model, config, tf_checkpoint_path, discriminator_
     """
     try:
         import re
+
         import numpy as np
         import tensorflow as tf
     except ImportError:

src/transformers/modeling_gpt2.py

@@ -65,6 +65,7 @@ def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path):
     """
     try:
         import re
+
         import tensorflow as tf
     except ImportError:
         logger.error(

src/transformers/modeling_mobilebert.py

@@ -68,6 +68,7 @@ def load_tf_weights_in_mobilebert(model, config, tf_checkpoint_path):
     """
     try:
         import re
+
         import numpy as np
         import tensorflow as tf
     except ImportError:

src/transformers/modeling_openai.py

@@ -62,6 +62,7 @@ def load_tf_weights_in_openai_gpt(model, config, openai_checkpoint_folder_path):
     """ Load tf pre-trained weights in a pytorch model (from NumPy arrays here)
     """
     import re
+
     import numpy as np
 
     if ".ckpt" in openai_checkpoint_folder_path:

src/transformers/modeling_t5.py

@@ -66,6 +66,7 @@ def load_tf_weights_in_t5(model, config, tf_checkpoint_path):
     """
     try:
         import re
+
         import numpy as np
         import tensorflow as tf
     except ImportError:

src/transformers/modeling_tf_pytorch_utils.py

@@ -108,8 +108,8 @@ def load_pytorch_weights_in_tf2_model(tf_model, pt_state_dict, tf_inputs=None, a
     """ Load pytorch state_dict in a TF 2.0 model.
     """
     try:
-        import torch  # noqa: F401
         import tensorflow as tf  # noqa: F401
+        import torch  # noqa: F401
         from tensorflow.python.keras import backend as K
     except ImportError:
         logger.error(

src/transformers/pipelines.py

@@ -43,39 +43,41 @@ from .tokenization_utils_base import BatchEncoding, PaddingStrategy
 
 if is_tf_available():
     import tensorflow as tf
+
     from .modeling_tf_auto import (
+        TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
+        TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
+        TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
+        TF_MODEL_WITH_LM_HEAD_MAPPING,
         TFAutoModel,
-        TFAutoModelForSequenceClassification,
+        TFAutoModelForCausalLM,
         TFAutoModelForQuestionAnswering,
+        TFAutoModelForSequenceClassification,
         TFAutoModelForTokenClassification,
         TFAutoModelWithLMHead,
-        TF_MODEL_WITH_LM_HEAD_MAPPING,
-        TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
-        TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
-        TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
-        TFAutoModelForCausalLM,
     )
 
 if is_torch_available():
     import torch
+
     from .modeling_auto import (
+        MODEL_FOR_MASKED_LM_MAPPING,
+        MODEL_FOR_QUESTION_ANSWERING_MAPPING,
+        MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
+        MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
+        MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
         AutoModel,
-        AutoModelForSequenceClassification,
-        AutoModelForQuestionAnswering,
-        AutoModelForTokenClassification,
-        AutoModelForSeq2SeqLM,
         AutoModelForCausalLM,
         AutoModelForMaskedLM,
-        MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
-        MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
-        MODEL_FOR_QUESTION_ANSWERING_MAPPING,
-        MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
-        MODEL_FOR_MASKED_LM_MAPPING,
+        AutoModelForQuestionAnswering,
+        AutoModelForSeq2SeqLM,
+        AutoModelForSequenceClassification,
+        AutoModelForTokenClassification,
     )
 
 if TYPE_CHECKING:
-    from .modeling_utils import PreTrainedModel
     from .modeling_tf_utils import TFPreTrainedModel
+    from .modeling_utils import PreTrainedModel
 
 
 logger = logging.getLogger(__name__)

src/transformers/tokenization_transfo_xl.py

@@ -27,6 +27,7 @@ from collections import Counter, OrderedDict
 from typing import Optional
 
 import numpy as np
+
 from tokenizers import Tokenizer
 from tokenizers.implementations import BaseTokenizer
 from tokenizers.models import WordLevel

src/transformers/tokenization_utils_base.py

@@ -28,6 +28,7 @@ from enum import Enum
 from typing import Any, Dict, List, NamedTuple, Optional, Sequence, Tuple, Union
 
 import numpy as np
+
 from tokenizers import AddedToken
 from tokenizers import Encoding as EncodingFast
 

templates/adding_a_new_model/modeling_xxx.py

@@ -63,6 +63,7 @@ def load_tf_weights_in_xxx(model, config, tf_checkpoint_path):
     """
     try:
         import re
+
         import numpy as np
         import tensorflow as tf
     except ImportError:

templates/adding_a_new_model/tests/test_modeling_tf_xxx.py

@@ -25,13 +25,14 @@ from .utils import CACHE_DIR, require_tf, slow
 
 if is_tf_available():
     import tensorflow as tf
+
     from transformers.modeling_tf_xxx import (
-        TFXxxModel,
         TFXxxForMaskedLM,
         TFXxxForMultipleChoice,
+        TFXxxForQuestionAnswering,
         TFXxxForSequenceClassification,
         TFXxxForTokenClassification,
-        TFXxxForQuestionAnswering,
+        TFXxxModel,
     )
 
 

templates/adding_a_new_model/tests/test_modeling_xxx.py

@@ -25,14 +25,14 @@ from .utils import require_torch, require_torch_and_cuda, slow, torch_device
 
 if is_torch_available():
     from transformers import (
+        AutoModelForMaskedLM,
+        AutoTokenizer,
         XxxConfig,
-        XxxModel,
         XxxForMaskedLM,
         XxxForQuestionAnswering,
         XxxForSequenceClassification,
         XxxForTokenClassification,
-        AutoModelForMaskedLM,
-        AutoTokenizer,
+        XxxModel,
     )
     from transformers.file_utils import cached_property
 

tests/test_activations.py

@@ -5,9 +5,10 @@ from transformers.testing_utils import require_torch
 
 
 if is_torch_available():
-    from transformers.activations import _gelu_python, get_activation, gelu_new
     import torch
 
+    from transformers.activations import _gelu_python, gelu_new, get_activation
+
 
 @require_torch
 class TestActivations(unittest.TestCase):