Sort imports with isort.

This is the result of:

    $ isort --recursive examples templates transformers utils hubconf.py setup.py

templates/adding_a_new_example_script/utils_xxx.py

@@ -16,16 +16,17 @@
 
 from __future__ import absolute_import, division, print_function
 
+import collections
 import json
 import logging
 import math
-import collections
 from io import open
 
 from transformers.tokenization_bert import BasicTokenizer, whitespace_tokenize
 
 # Required by XLNet evaluation method to compute optimal threshold (see write_predictions_extended() method)
-from utils_squad_evaluate import find_all_best_thresh_v2, make_qid_to_has_ans, get_raw_scores
+from utils_squad_evaluate import find_all_best_thresh_v2, get_raw_scores, make_qid_to_has_ans
+
 
 logger = logging.getLogger(__name__)
 

templates/adding_a_new_model/configuration_xxx.py

@@ -19,11 +19,13 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 import json
 import logging
 import sys
-import six
 from io import open
 
+import six
+
 from .configuration_utils import PretrainedConfig
 
+
 logger = logging.getLogger(__name__)
 
 XXX_PRETRAINED_CONFIG_ARCHIVE_MAP = {

templates/adding_a_new_model/convert_xxx_original_tf_checkpoint_to_pytorch.py

@@ -14,16 +14,15 @@
 # limitations under the License.
 """Convert XXX checkpoint."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
 import argparse
+import logging
+
 import torch
 
 from transformers import XxxConfig, XxxForPreTraining, load_tf_weights_in_xxx
 
-import logging
 
 logging.basicConfig(level=logging.INFO)
 

templates/adding_a_new_model/modeling_tf_xxx.py

@@ -21,21 +21,22 @@
 
 from __future__ import absolute_import, division, print_function, unicode_literals
 
+import copy
+import itertools
 import json
 import logging
 import math
 import os
 import sys
-import copy
-import itertools
 from io import open
 
 import numpy as np
 import tensorflow as tf
 
 from .configuration_xxx import XxxConfig
-from .modeling_tf_utils import TFPreTrainedModel, get_initializer, shape_list
 from .file_utils import add_start_docstrings
+from .modeling_tf_utils import TFPreTrainedModel, get_initializer, shape_list
+
 
 logger = logging.getLogger(__name__)
 

templates/adding_a_new_model/modeling_xxx.py

@@ -20,22 +20,23 @@
 
 from __future__ import absolute_import, division, print_function, unicode_literals
 
+import copy
+import itertools
 import json
 import logging
 import math
 import os
 import sys
-import copy
-import itertools
 from io import open
 
 import torch
 from torch import nn
 from torch.nn import CrossEntropyLoss, MSELoss
 
-from .modeling_utils import PreTrainedModel, prune_linear_layer
 from .configuration_xxx import XxxConfig
 from .file_utils import add_start_docstrings
+from .modeling_utils import PreTrainedModel, prune_linear_layer
+
 
 logger = logging.getLogger(__name__)
 

templates/adding_a_new_model/tests/modeling_tf_xxx_test.py

@@ -12,18 +12,17 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
-import unittest
 import sys
+import unittest
+
+from transformers import XxxConfig, is_tf_available
 
-from .modeling_tf_common_test import TFCommonTestCases, ids_tensor
 from .configuration_common_test import ConfigTester
+from .modeling_tf_common_test import TFCommonTestCases, ids_tensor
 from .utils import CACHE_DIR, require_tf, slow
 
-from transformers import XxxConfig, is_tf_available
 
 if is_tf_available():
     import tensorflow as tf

templates/adding_a_new_model/tests/modeling_xxx_test.py

@@ -12,18 +12,17 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
 import unittest
 
 from transformers import is_torch_available
 
-from .modeling_common_test import CommonTestCases, ids_tensor
 from .configuration_common_test import ConfigTester
+from .modeling_common_test import CommonTestCases, ids_tensor
 from .utils import CACHE_DIR, require_torch, slow, torch_device
 
+
 if is_torch_available():
     from transformers import (
         XxxConfig,

templates/adding_a_new_model/tests/tokenization_xxx_test.py

@@ -18,7 +18,7 @@ import os
 import unittest
 from io import open
 
-from transformers.tokenization_bert import XxxTokenizer, VOCAB_FILES_NAMES
+from transformers.tokenization_bert import VOCAB_FILES_NAMES, XxxTokenizer
 
 from .tokenization_tests_commons import CommonTestCases
 

templates/adding_a_new_model/tokenization_xxx.py

@@ -24,6 +24,7 @@ from io import open
 
 from .tokenization_utils import PreTrainedTokenizer
 
+
 logger = logging.getLogger(__name__)
 
 ####################################################

transformers/__init__.py

@@ -15,86 +15,114 @@ except:
 
 import logging
 
-logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
-
-# Files and general utilities
-from .file_utils import (
-    TRANSFORMERS_CACHE,
-    PYTORCH_TRANSFORMERS_CACHE,
-    PYTORCH_PRETRAINED_BERT_CACHE,
-    cached_path,
-    add_start_docstrings,
-    add_end_docstrings,
-    WEIGHTS_NAME,
-    TF2_WEIGHTS_NAME,
-    TF_WEIGHTS_NAME,
-    CONFIG_NAME,
-    MODEL_CARD_NAME,
-    is_tf_available,
-    is_torch_available,
-)
+from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig
+from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, AutoConfig
+from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig
+from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig
+from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
+from .configuration_distilbert import DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, DistilBertConfig
+from .configuration_gpt2 import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2Config
+from .configuration_mmbt import MMBTConfig
+from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
+from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig
+from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config
+from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
 
+# Configurations
+from .configuration_utils import PretrainedConfig
+from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig
+from .configuration_xlm_roberta import XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMRobertaConfig
+from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig
 from .data import (
-    is_sklearn_available,
+    DataProcessor,
     InputExample,
     InputFeatures,
-    DataProcessor,
     SingleSentenceClassificationProcessor,
-    glue_output_modes,
+    SquadExample,
+    SquadFeatures,
+    SquadV1Processor,
+    SquadV2Processor,
     glue_convert_examples_to_features,
+    glue_output_modes,
     glue_processors,
     glue_tasks_num_labels,
+    is_sklearn_available,
+    squad_convert_examples_to_features,
     xnli_output_modes,
     xnli_processors,
     xnli_tasks_num_labels,
-    squad_convert_examples_to_features,
-    SquadFeatures,
-    SquadExample,
-    SquadV1Processor,
-    SquadV2Processor,
 )
 
-if is_sklearn_available():
-    from .data import glue_compute_metrics, xnli_compute_metrics
+# Files and general utilities
+from .file_utils import (
+    CONFIG_NAME,
+    MODEL_CARD_NAME,
+    PYTORCH_PRETRAINED_BERT_CACHE,
+    PYTORCH_TRANSFORMERS_CACHE,
+    TF2_WEIGHTS_NAME,
+    TF_WEIGHTS_NAME,
+    TRANSFORMERS_CACHE,
+    WEIGHTS_NAME,
+    add_end_docstrings,
+    add_start_docstrings,
+    cached_path,
+    is_tf_available,
+    is_torch_available,
+)
 
 # Model Cards
 from .modelcard import ModelCard
 
-# Tokenizers
-from .tokenization_utils import PreTrainedTokenizer
+# TF 2.0 <=> PyTorch conversion utilities
+from .modeling_tf_pytorch_utils import (
+    convert_tf_weight_name_to_pt_weight_name,
+    load_pytorch_checkpoint_in_tf2_model,
+    load_pytorch_model_in_tf2_model,
+    load_pytorch_weights_in_tf2_model,
+    load_tf2_checkpoint_in_pytorch_model,
+    load_tf2_model_in_pytorch_model,
+    load_tf2_weights_in_pytorch_model,
+)
+
+# Pipelines
+from .pipelines import (
+    CsvPipelineDataFormat,
+    FeatureExtractionPipeline,
+    JsonPipelineDataFormat,
+    NerPipeline,
+    PipedPipelineDataFormat,
+    Pipeline,
+    PipelineDataFormat,
+    QuestionAnsweringPipeline,
+    TextClassificationPipeline,
+    pipeline,
+)
+from .tokenization_albert import AlbertTokenizer
 from .tokenization_auto import AutoTokenizer
-from .tokenization_bert import BertTokenizer, BasicTokenizer, WordpieceTokenizer
-from .tokenization_bert_japanese import BertJapaneseTokenizer, MecabTokenizer, CharacterTokenizer
-from .tokenization_openai import OpenAIGPTTokenizer
-from .tokenization_transfo_xl import TransfoXLTokenizer, TransfoXLCorpus
-from .tokenization_gpt2 import GPT2Tokenizer
+from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer
+from .tokenization_bert_japanese import BertJapaneseTokenizer, CharacterTokenizer, MecabTokenizer
+from .tokenization_camembert import CamembertTokenizer
 from .tokenization_ctrl import CTRLTokenizer
-from .tokenization_xlnet import XLNetTokenizer, SPIECE_UNDERLINE
-from .tokenization_xlm import XLMTokenizer
-from .tokenization_roberta import RobertaTokenizer
 from .tokenization_distilbert import DistilBertTokenizer
-from .tokenization_albert import AlbertTokenizer
-from .tokenization_camembert import CamembertTokenizer
+from .tokenization_gpt2 import GPT2Tokenizer
+from .tokenization_openai import OpenAIGPTTokenizer
+from .tokenization_roberta import RobertaTokenizer
 from .tokenization_t5 import T5Tokenizer
+from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer
+
+# Tokenizers
+from .tokenization_utils import PreTrainedTokenizer
+from .tokenization_xlm import XLMTokenizer
 from .tokenization_xlm_roberta import XLMRobertaTokenizer
+from .tokenization_xlnet import SPIECE_UNDERLINE, XLNetTokenizer
+
+
+logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
+
+
+if is_sklearn_available():
+    from .data import glue_compute_metrics, xnli_compute_metrics
 
-# Configurations
-from .configuration_utils import PretrainedConfig
-from .configuration_auto import AutoConfig, ALL_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_bert import BertConfig, BERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_openai import OpenAIGPTConfig, OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_transfo_xl import TransfoXLConfig, TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_gpt2 import GPT2Config, GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_ctrl import CTRLConfig, CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlnet import XLNetConfig, XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlm import XLMConfig, XLM_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_roberta import RobertaConfig, ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_distilbert import DistilBertConfig, DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_albert import AlbertConfig, ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_camembert import CamembertConfig, CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_t5 import T5Config, T5_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlm_roberta import XLMRobertaConfig, XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_mmbt import MMBTConfig
 
 # Modeling
 if is_torch_available():
@@ -345,30 +373,6 @@ if is_tf_available():
     # Optimization
     from .optimization_tf import WarmUp, create_optimizer, AdamWeightDecay, GradientAccumulator
 
-# TF 2.0 <=> PyTorch conversion utilities
-from .modeling_tf_pytorch_utils import (
-    convert_tf_weight_name_to_pt_weight_name,
-    load_pytorch_checkpoint_in_tf2_model,
-    load_pytorch_weights_in_tf2_model,
-    load_pytorch_model_in_tf2_model,
-    load_tf2_checkpoint_in_pytorch_model,
-    load_tf2_weights_in_pytorch_model,
-    load_tf2_model_in_pytorch_model,
-)
-
-# Pipelines
-from .pipelines import (
-    pipeline,
-    PipelineDataFormat,
-    CsvPipelineDataFormat,
-    JsonPipelineDataFormat,
-    PipedPipelineDataFormat,
-    Pipeline,
-    FeatureExtractionPipeline,
-    QuestionAnsweringPipeline,
-    NerPipeline,
-    TextClassificationPipeline,
-)
 
 if not is_tf_available() and not is_torch_available():
     logger.warning(

transformers/commands/convert.py

 from argparse import ArgumentParser, Namespace
-
 from logging import getLogger
 
 from transformers import AutoModel, AutoTokenizer

transformers/commands/run.py

@@ -2,7 +2,7 @@ import logging
 from argparse import ArgumentParser
 
 from transformers.commands import BaseTransformersCLICommand
-from transformers.pipelines import pipeline, Pipeline, PipelineDataFormat, SUPPORTED_TASKS
+from transformers.pipelines import SUPPORTED_TASKS, Pipeline, PipelineDataFormat, pipeline
 
 
 logger = logging.getLogger(__name__)  # pylint: disable=invalid-name

transformers/commands/serving.py

+import logging
 from argparse import ArgumentParser, Namespace
-from typing import List, Optional, Union, Any
+from typing import Any, List, Optional, Union
+
+from transformers import Pipeline
+from transformers.commands import BaseTransformersCLICommand
+from transformers.pipelines import SUPPORTED_TASKS, pipeline
 
-import logging
 
 try:
     from uvicorn import run
@@ -14,9 +18,6 @@ except (ImportError, AttributeError):
     Body = lambda *x, **y: None
     _serve_dependancies_installed = False
 
-from transformers import Pipeline
-from transformers.commands import BaseTransformersCLICommand
-from transformers.pipelines import SUPPORTED_TASKS, pipeline
 
 logger = logging.getLogger("transformers-cli/serving")
 

transformers/commands/train.py

@@ -2,13 +2,10 @@ import os
 from argparse import ArgumentParser, Namespace
 from logging import getLogger
 
+from transformers import SingleSentenceClassificationProcessor as Processor
+from transformers import TextClassificationPipeline, is_tf_available, is_torch_available
 from transformers.commands import BaseTransformersCLICommand
-from transformers import (
-    is_tf_available,
-    is_torch_available,
-    TextClassificationPipeline,
-    SingleSentenceClassificationProcessor as Processor,
-)
+
 
 if not is_tf_available() and not is_torch_available():
     raise ImportError("At least one of PyTorch or TensorFlow 2.0+ should be installed to use CLI training")

transformers/commands/user.py

+import os
 from argparse import ArgumentParser
 from getpass import getpass
-import os
 
 from transformers.commands import BaseTransformersCLICommand
 from transformers.hf_api import HfApi, HfFolder, HTTPError

transformers/configuration_albert.py

@@ -17,6 +17,7 @@
 
 from .configuration_utils import PretrainedConfig
 
+
 ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "albert-base-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-base-config.json",
     "albert-large-v1": "https://s3.amazonaws.com/models.huggingface.co/bert/albert-large-config.json",

transformers/configuration_auto.py

@@ -18,19 +18,20 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 
 import logging
 
-from .configuration_bert import BertConfig, BERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_openai import OpenAIGPTConfig, OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_transfo_xl import TransfoXLConfig, TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_gpt2 import GPT2Config, GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_ctrl import CTRLConfig, CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlnet import XLNetConfig, XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlm import XLMConfig, XLM_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_roberta import RobertaConfig, ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_distilbert import DistilBertConfig, DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_albert import AlbertConfig, ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_camembert import CamembertConfig, CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_t5 import T5Config, T5_PRETRAINED_CONFIG_ARCHIVE_MAP
-from .configuration_xlm_roberta import XLMRobertaConfig, XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
+from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig
+from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig
+from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig
+from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
+from .configuration_distilbert import DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, DistilBertConfig
+from .configuration_gpt2 import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2Config
+from .configuration_openai import OPENAI_GPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenAIGPTConfig
+from .configuration_roberta import ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, RobertaConfig
+from .configuration_t5 import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, T5Config
+from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
+from .configuration_xlm import XLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMConfig
+from .configuration_xlm_roberta import XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMRobertaConfig
+from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig
+
 
 logger = logging.getLogger(__name__)
 

transformers/configuration_bert.py

@@ -24,6 +24,7 @@ from io import open
 
 from .configuration_utils import PretrainedConfig
 
+
 logger = logging.getLogger(__name__)
 
 BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {

transformers/configuration_camembert.py

@@ -21,6 +21,7 @@ import logging
 
 from .configuration_roberta import RobertaConfig
 
+
 logger = logging.getLogger(__name__)
 
 CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {

transformers/configuration_ctrl.py

@@ -23,6 +23,7 @@ from io import open
 
 from .configuration_utils import PretrainedConfig
 
+
 logger = logging.getLogger(__name__)
 
 CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP = {"ctrl": "https://storage.googleapis.com/sf-ctrl/pytorch/ctrl-config.json"}