python 2 compatibility

examples/run_squad.py

@@ -15,29 +15,36 @@
 # limitations under the License.
 """Run BERT on SQuAD."""
 
-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 collections
-import logging
 import json
+import logging
 import math
 import os
 import random
-import pickle
-from tqdm import tqdm, trange
+import sys
+from io import open
 
 import numpy as np
 import torch
-from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
+from torch.utils.data import (DataLoader, RandomSampler, SequentialSampler,
+                              TensorDataset)
 from torch.utils.data.distributed import DistributedSampler
+from tqdm import tqdm, trange
 
-from pytorch_pretrained_bert.tokenization import whitespace_tokenize, BasicTokenizer, BertTokenizer
+from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
 from pytorch_pretrained_bert.modeling import BertForQuestionAnswering
 from pytorch_pretrained_bert.optimization import BertAdam
-from pytorch_pretrained_bert.file_utils import PYTORCH_PRETRAINED_BERT_CACHE
+from pytorch_pretrained_bert.tokenization import (BasicTokenizer,
+                                                  BertTokenizer,
+                                                  whitespace_tokenize)
+
+if sys.version_info[0] == 2:
+    import cPickle as pickle
+else:
+    import pickle
 
 logging.basicConfig(format = '%(asctime)s - %(levelname)s - %(name)s -   %(message)s',
                     datefmt = '%m/%d/%Y %H:%M:%S',
@@ -784,7 +791,8 @@ def main():
 
     if os.path.exists(args.output_dir) and os.listdir(args.output_dir):
         raise ValueError("Output directory () already exists and is not empty.")
-    os.makedirs(args.output_dir, exist_ok=True)
+    if not os.path.exists(args.output_dir):
+        os.makedirs(args.output_dir)
 
     tokenizer = BertTokenizer.from_pretrained(args.bert_model, do_lower_case=args.do_lower_case)
 
@@ -798,7 +806,7 @@ def main():
 
     # Prepare model
     model = BertForQuestionAnswering.from_pretrained(args.bert_model,
-                cache_dir=PYTORCH_PRETRAINED_BERT_CACHE / 'distributed_{}'.format(args.local_rank))
+                cache_dir=os.path.join(PYTORCH_PRETRAINED_BERT_CACHE, 'distributed_{}'.format(args.local_rank)))
 
     if args.fp16:
         model.half()