Fix F401 flake8 warning (x88 / 116).

This change is mostly autogenerated with:

    $ python -m autoflake --in-place --recursive --remove-all-unused-imports --ignore-init-module-imports examples templates transformers utils hubconf.py setup.py

I made minor changes in the generated diff.

examples/distillation/distiller.py

@@ -19,14 +19,13 @@ import math
 import os
 import time
 
-import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 from torch.optim import AdamW
 from torch.utils.data import BatchSampler, DataLoader, RandomSampler
 from torch.utils.data.distributed import DistributedSampler
-from tqdm import tqdm, trange
+from tqdm import tqdm
 
 import psutil
 from grouped_batch_sampler import GroupedBatchSampler, create_lengths_groups

examples/distillation/scripts/extract.py

@@ -20,7 +20,7 @@ import argparse
 
 import torch
 
-from transformers import BertForMaskedLM, GPT2LMHeadModel, RobertaForMaskedLM
+from transformers import GPT2LMHeadModel, RobertaForMaskedLM
 
 
 if __name__ == "__main__":

examples/distillation/scripts/extract_distilbert.py

@@ -20,7 +20,7 @@ import argparse
 
 import torch
 
-from transformers import BertForMaskedLM, RobertaForMaskedLM
+from transformers import BertForMaskedLM
 
 
 if __name__ == "__main__":

examples/run_bertology.py

@@ -26,8 +26,7 @@ from datetime import datetime
 
 import numpy as np
 import torch
-from torch.nn import CrossEntropyLoss, MSELoss
-from torch.utils.data import DataLoader, SequentialSampler, Subset, TensorDataset
+from torch.utils.data import DataLoader, SequentialSampler, Subset
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm
 

examples/run_squad.py

@@ -26,7 +26,7 @@ import timeit
 
 import numpy as np
 import torch
-from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
+from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
 from torch.utils.data.distributed import DistributedSampler
 from tqdm import tqdm, trange
 

examples/run_tf_ner.py

 # coding=utf-8
-import _pickle as pickle
 import collections
 import datetime
 import glob

templates/adding_a_new_model/configuration_xxx.py

@@ -18,8 +18,6 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 
 import logging
 
-import six
-
 from .configuration_utils import PretrainedConfig
 
 

templates/adding_a_new_model/modeling_tf_xxx.py

@@ -21,10 +21,8 @@
 
 from __future__ import absolute_import, division, print_function, unicode_literals
 
-import itertools
 import logging
 
-import numpy as np
 import tensorflow as tf
 
 from .configuration_xxx import XxxConfig

templates/adding_a_new_model/modeling_xxx.py

@@ -20,7 +20,6 @@
 
 from __future__ import absolute_import, division, print_function, unicode_literals
 
-import itertools
 import logging
 import os
 
@@ -30,7 +29,7 @@ from torch.nn import CrossEntropyLoss, MSELoss
 
 from .configuration_xxx import XxxConfig
 from .file_utils import add_start_docstrings
-from .modeling_utils import PreTrainedModel, prune_linear_layer
+from .modeling_utils import PreTrainedModel
 
 
 logger = logging.getLogger(__name__)

templates/adding_a_new_model/tests/modeling_tf_xxx_test.py

@@ -24,7 +24,6 @@ from .utils import CACHE_DIR, require_tf, slow
 
 
 if is_tf_available():
-    import tensorflow as tf
     from transformers.modeling_tf_xxx import (
         TFXxxModel,
         TFXxxForMaskedLM,

templates/adding_a_new_model/tokenization_xxx.py

@@ -19,7 +19,6 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 import collections
 import logging
 import os
-import unicodedata
 from io import open
 
 from .tokenization_utils import PreTrainedTokenizer

transformers/commands/convert.py

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

transformers/configuration_t5.py

@@ -18,8 +18,6 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 
 import logging
 
-import six
-
 from .configuration_utils import PretrainedConfig
 
 

transformers/convert_pytorch_checkpoint_to_tf2.py

@@ -20,8 +20,6 @@ import argparse
 import logging
 import os
 
-import tensorflow as tf
-
 from transformers import (
     ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
     BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,

transformers/convert_roberta_original_pytorch_checkpoint_to_pytorch.py

@@ -20,7 +20,6 @@ import argparse
 import logging
 import pathlib
 
-import numpy as np
 import torch
 from packaging import version
 

transformers/data/metrics/squad_metrics.py

@@ -16,9 +16,7 @@ import re
 import string
 from io import open
 
-from tqdm import tqdm
-
-from transformers.tokenization_bert import BasicTokenizer, whitespace_tokenize
+from transformers.tokenization_bert import BasicTokenizer
 
 
 logger = logging.getLogger(__name__)

transformers/data/processors/squad.py

@@ -8,8 +8,8 @@ import numpy as np
 from tqdm import tqdm
 
 from ...file_utils import is_tf_available, is_torch_available
-from ...tokenization_bert import BasicTokenizer, whitespace_tokenize
-from .utils import DataProcessor, InputExample, InputFeatures
+from ...tokenization_bert import whitespace_tokenize
+from .utils import DataProcessor
 
 
 if is_torch_available():

transformers/hf_api.py

@@ -21,7 +21,6 @@ from typing import List
 
 import requests
 import six
-from requests.exceptions import HTTPError
 from tqdm import tqdm
 
 

transformers/modeling_auto.py

@@ -32,7 +32,6 @@ from .configuration_auto import (
     XLMRobertaConfig,
     XLNetConfig,
 )
-from .file_utils import add_start_docstrings
 from .modeling_albert import (
     ALBERT_PRETRAINED_MODEL_ARCHIVE_MAP,
     AlbertForMaskedLM,
@@ -76,7 +75,6 @@ from .modeling_roberta import (
 )
 from .modeling_t5 import T5_PRETRAINED_MODEL_ARCHIVE_MAP, T5Model, T5WithLMHeadModel
 from .modeling_transfo_xl import TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_MAP, TransfoXLLMHeadModel, TransfoXLModel
-from .modeling_utils import PreTrainedModel, SequenceSummary
 from .modeling_xlm import (
     XLM_PRETRAINED_MODEL_ARCHIVE_MAP,
     XLMForQuestionAnswering,

transformers/modeling_ctrl.py

@@ -23,11 +23,10 @@ import numpy as np
 import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss
-from torch.nn.parameter import Parameter
 
 from .configuration_ctrl import CTRLConfig
 from .file_utils import add_start_docstrings
-from .modeling_utils import Conv1D, PreTrainedModel, SequenceSummary, prune_conv1d_layer
+from .modeling_utils import Conv1D, PreTrainedModel
 
 
 logger = logging.getLogger(__name__)