Python3 compatibility on import statements

tensorpack/callbacks/__init__.py

@@ -7,7 +7,7 @@ from pkgutil import walk_packages
 import os
 
 def global_import(name):
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), locals(), level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]

tensorpack/callbacks/dump.py

@@ -3,9 +3,11 @@
 # File: dump.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
-from .base import Callback
-import cv2
 import os
+import scipy.misc
+from scipy.misc import imsave
+
+from .base import Callback
 from ..utils import logger
 
 __all__ = ['DumpParamAsImage']
@@ -39,12 +41,12 @@ class DumpParamAsImage(Callback):
                 fname = os.path.join(
                     self.log_dir,
                     self.prefix + '-ep{:03d}-{}.png'.format(self.epoch_num, idx))
-                cv2.imwrite(fname, im * self.scale)
+                imsave(fname, (im * self.scale).astype('uint8'))
         else:
             im = val
             assert im.ndim in [2, 3]
             fname = os.path.join(
                 self.log_dir,
                 self.prefix + '-ep{:03d}.png'.format(self.epoch_num))
-            cv2.imwrite(fname, im * self.scale)
+            imsave(fname, (im * self.scale).astype('uint8'))
 

tensorpack/callbacks/summary.py

@@ -7,7 +7,7 @@ import tensorflow as tf
 import re
 import os
 import operator
-import cPickle as pickle
+import pickle
 
 from .base import Callback, PeriodicCallback
 from ..utils import *

tensorpack/dataflow/__init__.py

@@ -6,20 +6,20 @@
 from pkgutil import walk_packages
 import os
 import os.path
-import dataset
-import imgaug
 
-__SKIP = ['dftools', 'dataset']
+from . import dataset
+from . import imgaug
+
 def global_import(name):
-    if name in __SKIP:
-        return
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), locals(), level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]
 
+__SKIP = ['dftools', 'dataset']
 for _, module_name, _ in walk_packages(
         [os.path.dirname(__file__)]):
-    if not module_name.startswith('_'):
+    if not module_name.startswith('_') and \
+        module_name not in __SKIP:
         global_import(module_name)
 

tensorpack/dataflow/common.py

@@ -5,7 +5,7 @@
 
 import numpy as np
 from .base import DataFlow
-from imgaug import AugmentorList, Image
+from .imgaug import AugmentorList, Image
 
 __all__ = ['BatchData', 'FixedSizeData', 'FakeData', 'MapData',
            'AugmentImageComponent']
@@ -94,7 +94,7 @@ class RepeatedData(DataFlow):
 
     def size(self):
         if self.nr == -1:
-            raise RuntimeError(), "size() is unavailable for infinite dataflow"
+            raise RuntimeError("size() is unavailable for infinite dataflow")
         return self.ds.size() * self.nr
 
     def get_data(self):

tensorpack/dataflow/dataset/__init__.py

@@ -8,7 +8,7 @@ import os
 import os.path
 
 def global_import(name):
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), locals(), level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]

tensorpack/dataflow/dataset/cifar10.py

@@ -3,7 +3,7 @@
 # File: cifar10.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 import os, sys
-import cPickle
+import pickle
 import numpy
 from six.moves import urllib
 import tarfile
@@ -41,7 +41,7 @@ def maybe_download_and_extract(dest_directory):
 def read_cifar10(filenames):
     for fname in filenames:
         fo = open(fname, 'rb')
-        dic = cPickle.load(fo)
+        dic = pickle.load(fo)
         data = dic['data']
         label = dic['labels']
         fo.close()

tensorpack/dataflow/imgaug/__init__.py

@@ -9,7 +9,7 @@ from pkgutil import walk_packages
 __all__ = []
 
 def global_import(name):
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), locals(), level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]

tensorpack/models/__init__.py

@@ -8,7 +8,7 @@ import os
 import os.path
 
 def global_import(name):
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), locals(), level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]

tensorpack/models/image_sample.py

@@ -82,7 +82,7 @@ def ImageSample(inputs):
            sample(template, lyux) * neg_diffy * diffx,
            sample(template, uylx) * diffy * neg_diffx], name='sampled')
 
-from _test import TestModel
+from ._test import TestModel
 class TestSample(TestModel):
     def test_sample(self):
         import numpy as np
@@ -140,9 +140,9 @@ if __name__ == '__main__':
 
     out = sess.run(tf.gradients(tf.reduce_sum(output), mapv))
     #out = sess.run(output)
-    print out[0].min()
-    print out[0].max()
-    print out[0].sum()
+    print(out[0].min())
+    print(out[0].max())
+    print(out[0].sum())
 
     out = sess.run([output])[0]
     im = out[0]

tensorpack/models/pool.py

@@ -58,7 +58,7 @@ def FixedUnPooling(x, shape, unpool_mat=None):
                             input_shape[3]])
     return prod
 
-from _test import TestModel
+from ._test import TestModel
 class TestPool(TestModel):
     def test_fixed_unpooling(self):
         h, w = 3, 4

tensorpack/predict.py

@@ -4,16 +4,16 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-from itertools import count, izip
+from itertools import count
 import argparse
 from collections import namedtuple
 import numpy as np
 from tqdm import tqdm
 
-from utils import *
-from utils.modelutils import describe_model
-from utils import logger
-from dataflow import DataFlow, BatchData
+from .utils import *
+from .utils.modelutils import describe_model
+from .utils import logger
+from .dataflow import DataFlow, BatchData
 
 class PredictConfig(object):
     def __init__(self, **kwargs):
@@ -93,7 +93,7 @@ def get_predict_func(config):
         assert len(input_map) == len(dp), \
             "Graph has {} inputs but dataset only gives {} components!".format(
                     len(input_map), len(dp))
-        feed = dict(izip(input_map, dp))
+        feed = dict(zip(input_map, dp))
         if output_var_names is not None:
             results = sess.run(output_vars, feed_dict=feed)
             return results

tensorpack/train.py

@@ -8,17 +8,17 @@ from itertools import count
 import copy
 import argparse
 import re
-
 import tqdm
-from models import ModelDesc
-from dataflow.common import RepeatedData
-from utils import *
-from utils.concurrency import EnqueueThread
-from callbacks import *
-from utils.summary import summary_moving_average
-from utils.modelutils import describe_model
-from utils import logger
-from dataflow import DataFlow
+
+from .models import ModelDesc
+from .dataflow.common import RepeatedData
+from .utils import *
+from .utils.concurrency import EnqueueThread
+from .callbacks import *
+from .utils.summary import summary_moving_average
+from .utils.modelutils import describe_model
+from .utils import logger
+from .dataflow import DataFlow
 
 class TrainConfig(object):
     """ config for training"""

tensorpack/utils/__init__.py

@@ -12,10 +12,10 @@ import tensorflow as tf
 import numpy as np
 import collections
 
-import logger
+from . import logger
 
 def global_import(name):
-    p = __import__(name, globals(), locals())
+    p = __import__(name, globals(), None, level=1)
     lst = p.__all__ if '__all__' in dir(p) else dir(p)
     for k in lst:
         globals()[k] = p.__dict__[k]

tensorpack/utils/concurrency.py

@@ -5,12 +5,11 @@
 
 import threading
 from contextlib import contextmanager
-from itertools import izip
 import tensorflow as tf
 
 from .utils import expand_dim_if_necessary
 from .naming import *
-import logger
+from . import logger
 
 class StoppableThread(threading.Thread):
     def __init__(self):
@@ -43,7 +42,7 @@ class EnqueueThread(threading.Thread):
                 for dp in self.dataflow.get_data():
                     if self.coord.should_stop():
                         return
-                    feed = dict(izip(self.input_vars, dp))
+                    feed = dict(zip(self.input_vars, dp))
                     self.sess.run([self.op], feed_dict=feed)
                 #print '\nExauhsted!!!'
         except tf.errors.CancelledError as e:

tensorpack/utils/logger.py

@@ -21,6 +21,7 @@ class MyFormatter(logging.Formatter):
             fmt = date + ' ' + colored('ERR', 'red', attrs=['blink', 'underline']) + ' ' + msg
         else:
             fmt = date + ' ' + msg
+        # TODO this doesn't work in Python3
         self._fmt = fmt
         return super(MyFormatter, self).format(record)
 
@@ -31,6 +32,7 @@ def getlogger():
     handler = logging.StreamHandler()
     handler.setFormatter(MyFormatter(datefmt='%d %H:%M:%S'))
     logger.addHandler(handler)
+    logger.warn("hahah")
     return logger
 
 logger = getlogger()
@@ -53,7 +55,7 @@ def set_logger_dir(dirname):
     if os.path.isdir(dirname):
         logger.info("Directory {} exists. Please either backup or delete it unless you're continue from a paused task." )
         logger.info("Select Action: k (keep) / b (backup) / d (delete):")
-        act = raw_input().lower()
+        act = input().lower()
         if act == 'b':
             from datetime import datetime
             backup_name = dirname + datetime.now().strftime('.%d-%H%M%S')

tensorpack/utils/modelutils.py

@@ -4,7 +4,8 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-import logger
+
+from . import logger
 
 def describe_model():
     """ describe the current model parameters"""

tensorpack/utils/sessinit.py

@@ -8,7 +8,7 @@ from abc import abstractmethod, ABCMeta
 import numpy as np
 import tensorflow as tf
 
-import logger
+from . import logger
 class SessionInit(object):
     __metaclass__ = ABCMeta
 

tensorpack/utils/summary.py

@@ -4,8 +4,9 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-import logger
-from naming import *
+
+from . import logger
+from .naming import *
 
 def create_summary(name, v):
     """

usercustomize.py

@@ -4,7 +4,7 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 # use user-space protobuf
-import sys, os
-site = os.path.join(os.environ['HOME'],
-                       '.local/lib/python2.7/site-packages')
-sys.path.insert(0, site)
+#import sys, os
+#site = os.path.join(os.environ['HOME'],
+                       #'.local/lib/python2.7/site-packages')
+#sys.path.insert(0, site)