slim Python 3 compatibility: cPickle and str/bytes (tensorflow#1534)

slim/datasets/dataset_utils.py

@@ -124,7 +124,7 @@ def read_label_file(dataset_dir, filename=LABELS_FILENAME):
     A map from a label (integer) to class name.
   """
   labels_filename = os.path.join(dataset_dir, filename)
-  with tf.gfile.Open(labels_filename, 'r') as f:
+  with tf.gfile.Open(labels_filename, 'rb') as f:
     lines = f.read().decode()
   lines = lines.split('\n')
   lines = filter(None, lines)

slim/datasets/download_and_convert_cifar10.py

@@ -26,7 +26,7 @@
 from __future__ import division
 from __future__ import print_function
 
-import cPickle
+from six.moves import cPickle
 import os
 import sys
 import tarfile
@@ -72,14 +72,17 @@ def _add_to_tfrecord(filename, tfrecord_writer, offset=0):
   Returns:
     The new offset.
   """
-  with tf.gfile.Open(filename, 'r') as f:
-    data = cPickle.load(f)
+  with tf.gfile.Open(filename, 'rb') as f:
+    if sys.version_info < (3,):
+      data = cPickle.load(f)
+    else:
+      data = cPickle.load(f, encoding='bytes')
 
-  images = data['data']
+  images = data[b'data']
   num_images = images.shape[0]
 
   images = images.reshape((num_images, 3, 32, 32))
-  labels = data['labels']
+  labels = data[b'labels']
 
   with tf.Graph().as_default():
     image_placeholder = tf.placeholder(dtype=tf.uint8)
@@ -99,7 +102,7 @@ def _add_to_tfrecord(filename, tfrecord_writer, offset=0):
                               feed_dict={image_placeholder: image})
 
         example = dataset_utils.image_to_tfexample(
-            png_string, 'png', _IMAGE_SIZE, _IMAGE_SIZE, label)
+            png_string, b'png', _IMAGE_SIZE, _IMAGE_SIZE, label)
         tfrecord_writer.write(example.SerializeToString())
 
   return offset + num_images

slim/datasets/download_and_convert_flowers.py

@@ -136,14 +136,14 @@ def _convert_dataset(split_name, filenames, class_names_to_ids, dataset_dir):
             sys.stdout.flush()
 
             # Read the filename:
-            image_data = tf.gfile.FastGFile(filenames[i], 'r').read()
+            image_data = tf.gfile.FastGFile(filenames[i], 'rb').read()
             height, width = image_reader.read_image_dims(sess, image_data)
 
             class_name = os.path.basename(os.path.dirname(filenames[i]))
             class_id = class_names_to_ids[class_name]
 
             example = dataset_utils.image_to_tfexample(
-                image_data, 'jpg', height, width, class_id)
+                image_data, b'jpg', height, width, class_id)
             tfrecord_writer.write(example.SerializeToString())
 
   sys.stdout.write('\n')