Merged

theano/sandbox/neighbours.py

@@ -246,13 +246,13 @@ def neibs2images(neibs, neib_shape, original_shape, mode='valid'):
     neib_shape = T.as_tensor_variable(neib_shape)
     original_shape = T.as_tensor_variable(original_shape)
 
-    new_neib_shape = T.stack( original_shape[-1]/neib_shape[1], neib_shape[1] )
+    new_neib_shape = T.stack(original_shape[-1] // neib_shape[1], neib_shape[1])
     output_2d = images2neibs(neibs.dimshuffle('x','x',0,1), new_neib_shape, mode=mode)
     
     if mode == 'ignore_borders':
         valid_shape = list(original_shape)
-        valid_shape[2]  = valid_shape[2] / neib_shape[0] * neib_shape[0]
-        valid_shape[3]  = valid_shape[3] / neib_shape[1] * neib_shape[1]
+        valid_shape[2]  = (valid_shape[2] // neib_shape[0]) * neib_shape[0]
+        valid_shape[3]  = (valid_shape[3] // neib_shape[1]) * neib_shape[1]
         output_4d = output_2d.reshape(valid_shape)
         #padding the borders with zeros
         for d in [2,3]:

theano/sandbox/rng_mrg.py

@@ -263,7 +263,7 @@ class mrg_uniform(mrg_uniform_base):
         if (%(size)s->dimensions[0] != %(ndim)s)
         {
             PyErr_Format(PyExc_ValueError, "size must have length %%i (not %%i)",
-                %(ndim)s, %(size)s->dimensions[0]);
+                %(ndim)s, int(%(size)s->dimensions[0]));
             %(fail)s
         }
         if (%(size)s->descr->type_num != PyArray_INT32)
@@ -789,11 +789,11 @@ class MRG_RandomStreams(object):
         flattened = self.uniform(size=(n_samples,), dtype=dtype)
 
         if constant:
-            U1 = flattened[:n_samples/2]
-            U2 = flattened[n_samples/2:]
+            U1 = flattened[:n_samples // 2]
+            U2 = flattened[n_samples // 2:]
         else:
-            U1 = flattened[:prod(flattened.shape)/2]
-            U2 = flattened[prod(flattened.shape)/2:]
+            U1 = flattened[:prod(flattened.shape) // 2]
+            U2 = flattened[prod(flattened.shape) // 2:]
 
         #normal_samples = zeros_like(flattened)
         sqrt_ln_U1 = sqrt(-2.0*log(U1))

theano/scalar/basic.py

@@ -27,6 +27,11 @@ builtin_int = int
 builtin_float = float
 
 
+class IntegerDivisionError(Exception):
+    """Raised if someone tries to divide integers with '/' instead of '//'."""
+    pass
+
+
 def upcast(dtype, *dtypes):
     # Should we try to keep float32 instead of float64? This is used so that
     # for instance mixing int64 with float32 yields float32 instead of float64.
@@ -1028,7 +1033,7 @@ def div_proxy(x, y):
         # Following discussion on theano-dev ("Inconsistent behavior in integer
         # division"), we will change the semantics of "/" on integer types in
         # Theano 0.4. Until then, it is forbidden to use "/" on integers.
-        raise NotImplementedError(
+        raise IntegerDivisionError(
                 "Dividing two integers with '/' is forbidden until Theano v0.4"
                 " is released (where the result will be a floating point "
                 "number). In the meantime, please either use '//' for integer "

theano/scalar/tests/test_basic.py

@@ -182,9 +182,9 @@ class test_div(unittest.TestCase):
         d = float64()
         f = float32()
 
-        print (a/b).owner.op
-        assert isinstance((a/b).owner.op, IntDiv)
-        assert isinstance((b/a).owner.op, IntDiv)
+        print (a//b).owner.op
+        assert isinstance((a//b).owner.op, IntDiv)
+        assert isinstance((b//a).owner.op, IntDiv)
         assert isinstance((b/d).owner.op, TrueDiv)
         assert isinstance((b/f).owner.op, TrueDiv)
         assert isinstance((f/a).owner.op, TrueDiv)

theano/tensor/basic.py

@@ -7,6 +7,7 @@ import sys # for sys.maxint
 from theano.configparser import config, AddConfigVar, BoolParam
 import traceback #for overriding Op.__call__
 import warnings
+from itertools import izip
 
 import numpy, theano
 #from copy import copy as python_copy
@@ -23,6 +24,9 @@ from theano.gof.python25 import partial, any, all
 from theano import compile, printing
 from theano.printing import pprint
 
+# We use this exception as well.
+from theano.scalar import IntegerDivisionError
+
 ### set up the external interface
 from elemwise import Elemwise, DimShuffle, CAReduce, Sum
 
@@ -1138,7 +1142,7 @@ class _tensor_py_operators:
     def __div__(self,other):
         try:
             return div_proxy(self,other)
-        except NotImplementedError:
+        except IntegerDivisionError:
             # This is to raise the exception that occurs when trying to divide
             # two integer arrays (currently forbidden).
             raise
@@ -2579,7 +2583,7 @@ def div_proxy(x, y):
     if (as_tensor_variable(x).dtype in discrete_dtypes and
         as_tensor_variable(y).dtype in discrete_dtypes):
         # See the same in scalar/basic.py
-        raise NotImplementedError(
+        raise IntegerDivisionError(
                 "Dividing two integer arrays with '/' is forbidden until "
                 "Theano v0.4 is released (where the result will be a floating "
                 "point number). In the meantime, please either use '//' for "
@@ -2921,7 +2925,7 @@ class Subtensor(Op):
         padded = ( actual_idx_list +
                   [slice(None, None, None)]*(len(xshp)-len(self.idx_list)))
         i = 0
-        for idx, xl in zip(padded, xshp):
+        for idx, xl in izip(padded, xshp):
             if isinstance(idx, slice):
                 # If it is the default (None, None, None) slice, or a variant,
                 # the shape will be xl
@@ -2931,7 +2935,7 @@ class Subtensor(Op):
                     outshp.append(xl)
                 else:
                     cnf = get_canonical_form_slice(idx, xl)
-                    length = (cnf[0].stop - cnf[0].start -1)/cnf[0].step + 1
+                    length = (cnf[0].stop - cnf[0].start -1) // cnf[0].step + 1
                     length = switch(lt(length,0), 0, length)
                     outshp.append(length)
                 i += 1

theano/tensor/nnet/Conv3D.py

@@ -135,9 +135,9 @@ class Conv3D(theano.Op):
         vidDur = V_shape[3]
         filterDur = W_shape[3]
 
-        output_height = T.floor( (vidHeight - filterHeight) / dr )+1
-        output_width = T.floor( (vidWidth - filterWidth) / dc )+1
-        output_dur = T.floor( (vidDur - filterDur) / dt ) +1
+        output_height = T.floor((vidHeight - filterHeight) // dr) + 1
+        output_width = T.floor((vidWidth - filterWidth) // dc) + 1
+        output_dur = T.floor((vidDur - filterDur) // dt) + 1
 
         rval = (batch_size,  output_height, output_width, output_dur, output_channels )
 

theano/tensor/opt.py

@@ -32,6 +32,12 @@ from basic import get_constant_value
 
 # Utilities
 
+
+class ShapeError(Exception):
+    """Raised when the shape cannot be computed."""
+    pass
+
+
 def out2in(*local_opts):
     """WRITEME """
     return opt.TopoOptimizer(opt.LocalOptGroup(*local_opts),
@@ -528,7 +534,7 @@ class ShapeFeature(object):
     the cost of many Ops accurately, and generate c-code that is specific [e.g. unrolled] to
     particular sizes.
 
-    If you can determine the shape only in some case, return NotImplementedError when you can't
+    In cases where you cannot figure out the shape, raise a ShapeError.
 
     .. note::
 
@@ -714,13 +720,22 @@ class ShapeFeature(object):
 
         try:
             o_shapes = shape_infer(node, [self.shape_of[r] for r in node.inputs])
-        except NotImplementedError:
+        except ShapeError:
             o_shapes = self.default_infer_shape(node, [self.shape_of[r] for r in node.inputs])
+        except NotImplementedError, e:
+            raise NotImplementedError(
+                    'Code called by infer_shape failed raising a '
+                    'NotImplementedError. Raising NotImplementedError to '
+                    'indicate that a shape cannot be computed is no longer '
+                    'supported, and one should now use tensor.opt.ShapeError '
+                    'instead. The original exception message is: %s' % e)
         except Exception, e:
             _logger.error('Failed to infer_shape from Op %s (i_shapes=%s): %s %s'% (node.op,
                 [self.shape_of[r] for r in node.inputs],
                 type(e), str(e)))
-            o_shapes = self.default_infer_shape(node, [self.shape_of[r] for r in node.inputs])
+            # We raise the exception to make sure the user knows something bad
+            # is going on.
+            raise
 
         # this is packed information
         # an element of o_shapes is either None or a tuple

theano/tensor/tests/test_basic.py

@@ -2734,9 +2734,9 @@ class T_divimpl(unittest.TestCase):
                 (5.0/11.0))
         assert numpy.allclose(function([i, ii, d, f, c], f/i)(5, 3, 7.0, 11.0, numpy.complex(5,3)),
                 (11.0/5.0))
-        assert numpy.allclose(function([i, ii, d, f, c], i/ii)(5, 3, 7.0, 11.0, numpy.complex(5,3)),
+        assert numpy.allclose(function([i, ii, d, f, c], i//ii)(5, 3, 7.0, 11.0, numpy.complex(5,3)),
                 (5/3))
-        assert numpy.allclose(function([i, ii, d, f, c], ii/i)(5, 3, 7.0, 11.0, numpy.complex(5,3)),
+        assert numpy.allclose(function([i, ii, d, f, c], ii//i)(5, 3, 7.0, 11.0, numpy.complex(5,3)),
                 (3/5))
         assert numpy.allclose(function([i, ii, d, f, c], true_div(i,ii))(5, 3, 7.0, 11.0, numpy.complex(5,3)),
                 (5./3.))

theano/tensor/tests/test_opt.py

@@ -647,10 +647,13 @@ def test_local_merge_abs():
 
 
 def test_mixeddiv():
-    """Test that int division is preserved"""
+    """Test that int division raises an exception."""
     i = iscalar()
     d = dscalar()
-    assert 0 == function([i,d], d*(i/(i+1)))(3, 1.0)
+    try:
+        0 == function([i,d], d*(i/(i+1)))(3, 1.0)
+    except theano.scalar.IntegerDivisionError:
+        pass
 
 def test_const_type_in_mul_canonizer():
     input = dmatrix()

theano/tests/test_tutorial.py

 """ test code snippet in the Theano tutorials.
 """
 
-import unittest
+import os, unittest
 import theano
 import theano.tensor as T
 from theano import function
@@ -722,6 +722,15 @@ class T_loading_and_saving(unittest.TestCase):
 
         mode_instance = theano.compile.mode.get_mode(None)
         if not isinstance(mode_instance, theano.compile.debugmode.DebugMode):
+            if os.path.exists('obj.save') or os.path.exists('objects.save'):
+                # We do not want to delete these files silently, in case for
+                # some reason they would be something else than test-generated
+                # files.
+                # Ideally we would save those files in a temporary directory...
+                raise AssertionError(
+                        'Please get rid of files obj.save and '
+                        'objects.save in directory %s' % os.getcwd())
+
             f = file('obj.save', 'wb')
             cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
             f.close()
@@ -746,6 +755,9 @@ class T_loading_and_saving(unittest.TestCase):
                 loaded_objects.append(cPickle.load(f))
             f.close()
 
+            # Cleanup created files.
+            os.remove('obj.save')
+            os.remove('objects.save')
 
 class T_modes(unittest.TestCase):
     ## All tests here belog to