Sort imports with isort.

This is the result of:

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

examples/summarization/convert_bertabs_original_pytorch_checkpoint.py

@@ -20,13 +20,13 @@ the model within the original codebase to be able to only save its `state_dict`.
 """
 
 import argparse
-from collections import namedtuple
 import logging
+from collections import namedtuple
+
 import torch
 
-from models.model_builder import AbsSummarizer  # The authors' implementation
 from model_bertabs import BertAbsSummarizer
-
+from models.model_builder import AbsSummarizer  # The authors' implementation
 from transformers import BertTokenizer
 
 

examples/summarization/modeling_bertabs.py

@@ -27,9 +27,8 @@ import torch
 from torch import nn
 from torch.nn.init import xavier_uniform_
 
-from transformers import BertModel, BertConfig, PreTrainedModel
-
 from configuration_bertabs import BertAbsConfig
+from transformers import BertConfig, BertModel, PreTrainedModel
 
 
 MAX_SIZE = 5000

examples/summarization/run_summarization.py

@@ -1,26 +1,25 @@
 #! /usr/bin/python3
 import argparse
-from collections import namedtuple
 import logging
 import os
 import sys
+from collections import namedtuple
 
 import torch
 from torch.utils.data import DataLoader, SequentialSampler
 from tqdm import tqdm
 
-from transformers import BertTokenizer
-
 from modeling_bertabs import BertAbs, build_predictor
-
+from transformers import BertTokenizer
 from utils_summarization import (
     SummarizationDataset,
-    encode_for_summarization,
     build_mask,
-    fit_to_block_size,
     compute_token_type_ids,
+    encode_for_summarization,
+    fit_to_block_size,
 )
 
+
 logger = logging.getLogger(__name__)
 logging.basicConfig(stream=sys.stdout, level=logging.INFO)
 

examples/summarization/utils_summarization.py

@@ -1,5 +1,5 @@
-from collections import deque
 import os
+from collections import deque
 
 import torch
 from torch.utils.data import Dataset

examples/summarization/utils_summarization_test.py

@@ -17,12 +17,7 @@ import unittest
 import numpy as np
 import torch
 
-from utils_summarization import (
-    compute_token_type_ids,
-    fit_to_block_size,
-    build_mask,
-    process_story,
-)
+from utils_summarization import build_mask, compute_token_type_ids, fit_to_block_size, process_story
 
 
 class SummarizationDataProcessingTest(unittest.TestCase):