Removed debug statement and made the test python 3 compatible.

fuel/transformers/image.py

@@ -306,7 +306,7 @@ def __init__(self, data_stream, window_shape, location, **kwargs):
             raise ValueError('Location must be a tuple or list of length 2 '
                              '(given {}).'.format(location))
         if location[0] < 0 or location[0] > 1 or location[1] < 0 or \
-                        location[1] > 1:
+                location[1] > 1:
             raise ValueError('Location height and width must be between 0 '
                              'and 1 (given {}).'.format(location))
         self.location = location

tests/transformers/test_image.py

@@ -5,9 +5,6 @@
 from PIL import Image
 from picklable_itertools.extras import partition_all
 from six.moves import zip
-
-import pyximport
-pyximport.install()
 from fuel import config
 from fuel.datasets.base import IndexableDataset
 from fuel.schemes import ShuffledScheme, SequentialExampleScheme
@@ -322,13 +319,13 @@ def test_ndarray_batch_source(self):
         for loc in [(0, 0), (0, 1), (1, 0), (1, 1)]:
             stream = FixedSizeCrop(self.batch_stream, (5, 4),
                                    which_sources=('source1',), location=loc)
-            batch = stream.get_epoch_iterator().next()
-            assert batch[0].shape[1:] == (3, 5, 4)
-            assert batch[0].shape[0] in (1, 2)
             # seen indices should only be of that length in after last location
             if 3 * 7 * 5 == len(seen_indices):
                 assert False
-            seen_indices = numpy.union1d(seen_indices, batch[0].flatten())
+            for batch in stream.get_epoch_iterator():
+                assert batch[0].shape[1:] == (3, 5, 4)
+                assert batch[0].shape[0] in (1, 2)
+                seen_indices = numpy.union1d(seen_indices, batch[0].flatten())
         assert 3 * 7 * 5 == len(seen_indices)
 
     def test_list_batch_source(self):
@@ -360,7 +357,6 @@ def test_objectarray_batch_source(self):
                 assert False
             for batch in stream.get_epoch_iterator():
                 for example in batch[2]:
-                    print example.shape
                     assert example.shape == (2, 5, 4)
                     seen_indices = numpy.union1d(seen_indices,
                                                  example.flatten())