Merge branch 'master' into master

research/brain_coder/single_task/test_tasks.py

@@ -4,6 +4,7 @@ from __future__ import print_function
 
 """Tasks that test correctness of algorithms."""
 
+from six.moves import xrange
 from common import reward as reward_lib  # brain coder
 from single_task import misc  # brain coder
 
@@ -124,5 +125,3 @@ class HillClimbingTask(object):
     # closest next element.
     # Maximum distance possible is num_actions * base / 2 = 3 * 8 / 2 = 12
     return (len(prefix) + (1 - min_dist / 12.0)), False
-
-

research/brain_coder/single_task/tune.py

@@ -39,6 +39,7 @@ from absl import app
 from absl import flags
 from absl import logging
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 from single_task import defaults  # brain coder

research/cognitive_mapping_and_planning/scripts/script_env_vis.py

@@ -90,7 +90,7 @@ def walk_through(b):
 
   root = tk.Tk()
   image = b.render_nodes(b.task.nodes[[current_node],:])[0]
-  print image.shape
+  print(image.shape)
   image = image.astype(np.uint8)
   im = Image.fromarray(image)
   im = ImageTk.PhotoImage(im)

research/cognitive_mapping_and_planning/scripts/script_plot_trajectory.py

@@ -220,7 +220,7 @@ def plot_trajectory_first_person(dt, orig_maps, out_dir):
       t.set_bbox(dict(color='white', alpha=0.85, pad=-0.1))
 
       # Action to take.
-      action_latex = ['$\odot$ ', '$\curvearrowright$ ', '$\curvearrowleft$ ', '$\Uparrow$ ']
+      action_latex = ['$\odot$ ', '$\curvearrowright$ ', '$\curvearrowleft$ ', r'$\Uparrow$ ']
       t = ax.text(0.99, 0.99, action_latex[actions[step_number]],
           horizontalalignment='right',
           verticalalignment='top',
@@ -265,7 +265,7 @@ def plot_trajectory_first_person(dt, orig_maps, out_dir):
     tmp_file_name = 'tmp.mp4'
     line_ani.save(tmp_file_name, writer=writer, savefig_kwargs={'facecolor':'black'})
     out_file_name = os.path.join(out_dir, 'vis_{:04d}.mp4'.format(i))
-    print out_file_name
+    print(out_file_name)
 
     if fu.exists(out_file_name):
       gfile.Remove(out_file_name)
@@ -318,7 +318,7 @@ def plot_trajectory(dt, hardness, orig_maps, out_dir):
     ax.set_ylim([xy1[1], xy2[1]])
 
     file_name = os.path.join(out_dir, 'trajectory_{:04d}.png'.format(i))
-    print file_name
+    print(file_name)
     with fu.fopen(file_name, 'w') as f:
       plt.savefig(f)
     plt.close(fig)

research/cognitive_mapping_and_planning/src/file_utils.py

@@ -16,6 +16,7 @@
 """Utilities for manipulating files.
 """
 import os
+import numpy as np
 import PIL
 from tensorflow.python.platform import gfile
 import cv2

research/cognitive_mapping_and_planning/src/graph_utils.py

@@ -19,6 +19,7 @@ import skimage.morphology
 import numpy as np
 import networkx as nx
 import itertools
+import logging
 import graph_tool as gt
 import graph_tool.topology
 import graph_tool.generation 

research/cognitive_mapping_and_planning/src/map_utils.py

@@ -17,6 +17,7 @@
 """
 import copy
 import skimage.morphology
+import logging
 import numpy as np
 import scipy.ndimage
 import matplotlib.pyplot as plt

research/cognitive_mapping_and_planning/src/utils.py

@@ -17,6 +17,7 @@ r"""Generaly Utilities.
 """
 
 import numpy as np, cPickle, os, time
+from six.moves import xrange
 import src.file_utils as fu
 import logging
 
@@ -93,12 +94,12 @@ def tic_toc_print(interval, string):
   global tic_toc_print_time_old
   if 'tic_toc_print_time_old' not in globals():
     tic_toc_print_time_old = time.time()
-    print string
+    print(string)
   else:
     new_time = time.time()
     if new_time - tic_toc_print_time_old > interval:
       tic_toc_print_time_old = new_time;
-      print string
+      print(string)
 
 def mkdir_if_missing(output_dir):
   if not fu.exists(output_dir):
@@ -165,4 +166,3 @@ def calc_pr(gt, out, wt=None):
 
   ap = voc_ap(rec, prec)
   return ap, rec, prec
-

research/compression/entropy_coder/core/entropy_coder_single.py

@@ -58,7 +58,7 @@ def main(_):
   #iteration = FLAGS.iteration
 
   if not tf.gfile.Exists(FLAGS.input_codes):
-    print '\nInput codes not found.\n'
+    print('\nInput codes not found.\n')
     return
 
   with tf.gfile.FastGFile(FLAGS.input_codes, 'rb') as code_file:

research/compression/entropy_coder/core/entropy_coder_train.py

@@ -171,7 +171,7 @@ def train():
               'code_length': model.average_code_length
           }
           np_tensors = sess.run(tf_tensors, feed_dict=feed_dict)
-          print np_tensors['code_length']
+          print(np_tensors['code_length'])
 
       sv.Stop()
 

research/compression/entropy_coder/dataset/gen_synthetic_dataset.py

@@ -18,6 +18,7 @@
 import os
 
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 import synthetic_model

research/compression/entropy_coder/dataset/synthetic_model.py

@@ -16,6 +16,7 @@
 """Binary code sample generator."""
 
 import numpy as np
+from six.moves import xrange
 
 
 _CRC_LINE = [

research/compression/entropy_coder/lib/block_util.py

@@ -21,6 +21,7 @@ from __future__ import unicode_literals
 import math
 
 import numpy as np
+import six
 import tensorflow as tf
 
 
@@ -39,7 +40,7 @@ class RsqrtInitializer(object):
         1.0 / sqrt(product(shape[dims]))
       **kwargs: Extra keyword arguments to pass to tf.truncated_normal.
     """
-    if isinstance(dims, (int, long)):
+    if isinstance(dims, six.integer_types):
       self._dims = [dims]
     else:
       self._dims = dims
@@ -73,7 +74,7 @@ class RectifierInitializer(object):
         sqrt(scale / product(shape[dims])).
       **kwargs: Extra keyword arguments to pass to tf.truncated_normal.
     """
-    if isinstance(dims, (int, long)):
+    if isinstance(dims, six.integer_types):
       self._dims = [dims]
     else:
       self._dims = dims

research/compression/entropy_coder/lib/blocks_masked_conv2d.py

@@ -16,6 +16,7 @@
 """Define some typical masked 2D convolutions."""
 
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 import block_util

research/compression/entropy_coder/lib/blocks_masked_conv2d_test.py

@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import unicode_literals
 
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 import blocks_masked_conv2d

research/compression/entropy_coder/lib/blocks_std_test.py

@@ -22,6 +22,7 @@ import math
 import os
 
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 import blocks_std

research/delf/delf/python/feature_io.py

@@ -25,6 +25,7 @@ from __future__ import print_function
 from delf import feature_pb2
 from delf import datum_io
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 

research/differential_privacy/dp_sgd/dp_mnist/dp_mnist.py

@@ -22,6 +22,7 @@ import sys
 import time
 
 import numpy as np
+from six.moves import xrange
 import tensorflow as tf
 
 from differential_privacy.dp_sgd.dp_optimizer import dp_optimizer

research/differential_privacy/dp_sgd/per_example_gradients/per_example_gradients.py

@@ -17,6 +17,7 @@
 
 import collections
 
+from six.moves import xrange
 import tensorflow as tf
 
 OrderedDict = collections.OrderedDict

research/differential_privacy/multiple_teachers/aggregation.py

@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 import numpy as np
+from six.moves import xrange
 
 
 def labels_from_probs(probs):
@@ -127,5 +128,3 @@ def aggregation_most_frequent(logits):
     result[i] = np.argmax(label_counts)
 
   return np.asarray(result, dtype=np.int32)
-
-