Make IMDB example work on Python3

text/augmentation/sent_level_augment.py

@@ -22,6 +22,7 @@
 import math
 
 import random
+import six
 from absl import flags
 
 import numpy as np
@@ -117,7 +118,7 @@ def back_translation(examples, aug_ops, sub_set, aug_copy_num,
         text_b=text_b,
         label=ori_example.label)
     aug_examples += [example]
-    if np.random.random() < 0.0001:
+    if six.PY2 and np.random.random() < 0.0001:
       tf.logging.info("\tori:\n\t\t{:s}\n\t\t{:s}\n\t\t{:s}\n".format(
           ori_example.text_a, ori_example.text_b, ori_example.label))
       tf.logging.info("\tnew:\n\t\t{:s}\n\t\t{:s}\n\t\t{:s}\n".format(

text/bert/modeling.py

@@ -312,7 +312,10 @@ def get_activation(activation_string):
 
   # We assume that anything that's not a string is already an activation
   # function, so we just return it.
-  if not isinstance(activation_string, (str, unicode)):
+
+  if six.PY2 and not isinstance(activation_string, (str, unicode)):
+    return activation_string
+  elif six.PY3 and not isinstance(activation_string, str):
     return activation_string
 
   if not activation_string:
@@ -964,7 +967,9 @@ def assert_rank(tensor, expected_rank, name=None):
     name = tensor.name
 
   expected_rank_dict = {}
-  if isinstance(expected_rank, (int, long)):
+  if six.PY2 and isinstance(expected_rank, (int, long)):
+    expected_rank_dict[expected_rank] = True
+  elif six.PY3 and isinstance(expected_rank, int):
     expected_rank_dict[expected_rank] = True
   else:
     for x in expected_rank:

text/preprocess.py

@@ -21,6 +21,7 @@
 import copy
 import json
 import os
+import six
 from absl import app
 from absl import flags
 
@@ -266,7 +267,7 @@ def convert_examples_to_features(
       # st = " ".join([str(x) for x in tokens])
       st = ""
       for x in tokens:
-        if isinstance(x, unicode):
+        if six.PY2 and isinstance(x, unicode):
           st += x.encode("ascii", "replace") + " "
         else:
           st += str(x) + " "

text/utils/tokenization.py

@@ -34,14 +34,19 @@ def load_vocab(vocab_file):
   """Loads a vocabulary file into a dictionary."""
   vocab = collections.OrderedDict()
   index = 0
-  with open_reader(vocab_file) as reader:
-    while True:
-      token = reader.readline()
-      if not token:
-        break
-      token = token.strip()
-      vocab[token] = index
-      index += 1
+  if six.PY2:
+    reader = open_reader(vocab_file)
+  else:
+    reader = tf.gfile.GFile(vocab_file, "r")
+
+  while True:
+    token = reader.readline()
+    if not token:
+      break
+    token = token.strip()
+    vocab[token] = index
+    index += 1
+  reader.close()
   return vocab
 
 
@@ -265,11 +270,12 @@ def _is_punctuation(char):
 
 def _convert_to_unicode_or_throw(text):
   """Converts `text` to Unicode (if it's not already), assuming utf-8 input."""
-  if isinstance(text, str):
-    text = text.decode("utf-8", "ignore")
-  if not isinstance(text, unicode):
-    raise ValueError("`text` must be of type `unicode` or `str`, but is "
-                     "actually of type: %s" % (type(text).__name__))
+  if six.PY2:
+    if isinstance(text, str):
+      text = text.decode("utf-8", "ignore")
+    if not isinstance(text, unicode):
+      raise ValueError("`text` must be of type `unicode` or `str`, but is "
+                      "actually of type: %s" % (type(text).__name__))
   return text