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.

transformers/modeling_distilbert.py

@@ -19,7 +19,6 @@
 from __future__ import absolute_import, division, print_function, unicode_literals
 
 import copy
-import itertools
 import logging
 import math
 

transformers/modeling_encoder_decoder.py

@@ -21,7 +21,6 @@ import os
 
 import torch
 from torch import nn
-from tqdm import trange
 
 from .modeling_auto import AutoModel, AutoModelWithLMHead
 

transformers/modeling_gpt2.py

@@ -24,7 +24,6 @@ import os
 import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss
-from torch.nn.parameter import Parameter
 
 from .configuration_gpt2 import GPT2Config
 from .file_utils import add_start_docstrings
@@ -47,7 +46,6 @@ def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path):
     """
     try:
         import re
-        import numpy as np
         import tensorflow as tf
     except ImportError:
         logger.error(

transformers/modeling_openai.py

@@ -26,7 +26,6 @@ from io import open
 import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss
-from torch.nn.parameter import Parameter
 
 from .configuration_openai import OpenAIGPTConfig
 from .file_utils import add_start_docstrings

transformers/modeling_t5.py

@@ -25,7 +25,7 @@ import os
 import torch
 import torch.nn.functional as F
 from torch import nn
-from torch.nn import CrossEntropyLoss, MSELoss
+from torch.nn import CrossEntropyLoss
 
 from .configuration_t5 import T5Config
 from .file_utils import DUMMY_INPUTS, DUMMY_MASK, add_start_docstrings

transformers/modeling_tf_auto.py

@@ -29,7 +29,6 @@ from .configuration_auto import (
     XLMConfig,
     XLNetConfig,
 )
-from .file_utils import add_start_docstrings
 from .modeling_tf_albert import (
     TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_MAP,
     TFAlbertForMaskedLM,

transformers/modeling_tf_ctrl.py

@@ -24,7 +24,7 @@ import tensorflow as tf
 
 from .configuration_ctrl import CTRLConfig
 from .file_utils import add_start_docstrings
-from .modeling_tf_utils import TFPreTrainedModel, TFSharedEmbeddings, get_initializer, shape_list
+from .modeling_tf_utils import TFPreTrainedModel, TFSharedEmbeddings, shape_list
 
 
 logger = logging.getLogger(__name__)

transformers/modeling_tf_distilbert.py

@@ -16,7 +16,6 @@
 """
 from __future__ import absolute_import, division, print_function, unicode_literals
 
-import itertools
 import logging
 import math
 

transformers/modeling_tf_pytorch_utils.py

@@ -75,8 +75,8 @@ def load_pytorch_checkpoint_in_tf2_model(tf_model, pytorch_checkpoint_path, tf_i
     """ Load pytorch checkpoints in a TF 2.0 model
     """
     try:
-        import tensorflow as tf
-        import torch
+        import tensorflow as tf  # noqa: F401
+        import torch  # noqa: F401
     except ImportError as e:
         logger.error(
             "Loading a PyTorch model in TensorFlow, requires both PyTorch and TensorFlow to be installed. Please see "
@@ -109,8 +109,8 @@ 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
-        import tensorflow as tf
+        import torch  # noqa: F401
+        import tensorflow as tf  # noqa: F401
         from tensorflow.python.keras import backend as K
     except ImportError as e:
         logger.error(
@@ -208,8 +208,8 @@ def load_tf2_checkpoint_in_pytorch_model(pt_model, tf_checkpoint_path, tf_inputs
         (see https://github.com/tensorflow/tensorflow/blob/ee16fcac960ae660e0e4496658a366e2f745e1f0/tensorflow/python/keras/engine/network.py#L1352-L1357).
     """
     try:
-        import tensorflow as tf
-        import torch
+        import tensorflow as tf  # noqa: F401
+        import torch  # noqa: F401
     except ImportError as e:
         logger.error(
             "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see "
@@ -250,8 +250,8 @@ def load_tf2_weights_in_pytorch_model(pt_model, tf_weights, allow_missing_keys=F
     """ Load TF2.0 symbolic weights in a PyTorch model
     """
     try:
-        import tensorflow as tf
-        import torch
+        import tensorflow as tf  # noqa: F401
+        import torch  # noqa: F401
     except ImportError as e:
         logger.error(
             "Loading a TensorFlow model in PyTorch, requires both PyTorch and TensorFlow to be installed. Please see "

transformers/modeling_tf_roberta.py

@@ -23,7 +23,7 @@ import tensorflow as tf
 
 from .configuration_roberta import RobertaConfig
 from .file_utils import add_start_docstrings
-from .modeling_tf_bert import TFBertEmbeddings, TFBertMainLayer, gelu, gelu_new
+from .modeling_tf_bert import TFBertEmbeddings, TFBertMainLayer, gelu
 from .modeling_tf_utils import TFPreTrainedModel, get_initializer, shape_list
 
 

transformers/modeling_tf_transfo_xl.py

@@ -20,13 +20,12 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 
 import logging
 
-import numpy as np
 import tensorflow as tf
 
 from .configuration_transfo_xl import TransfoXLConfig
 from .file_utils import add_start_docstrings
 from .modeling_tf_transfo_xl_utilities import TFAdaptiveSoftmaxMask
-from .modeling_tf_utils import TFConv1D, TFPreTrainedModel, TFSequenceSummary, get_initializer, shape_list
+from .modeling_tf_utils import TFPreTrainedModel, get_initializer, shape_list
 
 
 logger = logging.getLogger(__name__)

transformers/modeling_tf_transfo_xl_utilities.py

@@ -17,7 +17,6 @@
 """
 
 
-import numpy as np
 import tensorflow as tf
 
 from .modeling_tf_utils import shape_list

transformers/modeling_transfo_xl.py

@@ -25,13 +25,11 @@ import logging
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from torch.nn import CrossEntropyLoss
-from torch.nn.parameter import Parameter
 
 from .configuration_transfo_xl import TransfoXLConfig
 from .file_utils import add_start_docstrings
 from .modeling_transfo_xl_utilities import LogUniformSampler, ProjectedAdaptiveLogSoftmax, sample_logits
-from .modeling_utils import Conv1D, PreTrainedModel, SequenceSummary, prune_conv1d_layer
+from .modeling_utils import PreTrainedModel
 
 
 logger = logging.getLogger(__name__)

transformers/modeling_transfo_xl_utilities.py

@@ -18,7 +18,6 @@
 """
 
 
-import numpy as np
 import torch
 import torch.nn as nn
 import torch.nn.functional as F

transformers/modeling_utils.py

@@ -20,7 +20,6 @@ from __future__ import absolute_import, division, print_function, unicode_litera
 import logging
 import os
 
-import six
 import torch
 from torch import nn
 from torch.nn import CrossEntropyLoss

transformers/pipelines.py

@@ -22,7 +22,6 @@ import pickle
 import sys
 from abc import ABC, abstractmethod
 from contextlib import contextmanager
-from itertools import groupby
 from os.path import abspath, exists
 from typing import Dict, List, Optional, Tuple, Union
 

transformers/tests/modeling_auto_test.py

@@ -37,9 +37,6 @@ if is_torch_available():
     )
     from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_MAP
 
-    from .modeling_common_test import CommonTestCases, ids_tensor
-    from .configuration_common_test import ConfigTester
-
 
 @require_torch
 class AutoModelTest(unittest.TestCase):

transformers/tests/modeling_distilbert_test.py

@@ -20,7 +20,7 @@ from transformers import is_torch_available
 
 from .configuration_common_test import ConfigTester
 from .modeling_common_test import CommonTestCases, ids_tensor
-from .utils import CACHE_DIR, require_torch, slow, torch_device
+from .utils import require_torch, torch_device
 
 
 if is_torch_available():

transformers/tests/modeling_t5_test.py

@@ -19,8 +19,8 @@ import unittest
 from transformers import is_torch_available
 
 from .configuration_common_test import ConfigTester
-from .modeling_common_test import CommonTestCases, floats_tensor, ids_tensor
-from .utils import CACHE_DIR, require_torch, slow, torch_device
+from .modeling_common_test import CommonTestCases, ids_tensor
+from .utils import CACHE_DIR, require_torch, slow
 
 
 if is_torch_available():

transformers/tests/modeling_tf_albert_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_albert import (
         TFAlbertModel,
         TFAlbertForMaskedLM,