Merge.

theano/tensor/elemwise.py

@@ -872,10 +872,6 @@ class CAReduce(Op):
             self.axis = tuple(self.axis)
         self.ufunc = numpy.frompyfunc(scalar_op.impl, 2, 1)
 
-        # CAReduce output views input when reducing scalars
-        # See ticket #417: http://www.pylearn.org/theano/trac/ticket/417
-        self.view_map = {0: [0]}
-
     def _output_dtype(self, input_dtype):
         return input_dtype
 

theano/tensor/tests/test_elemwise.py

@@ -164,8 +164,11 @@ class test_CAReduce(unittest.TestCase):
                            ((5, 6), ()),
                            ((2, 3, 4, 5), (0, 1, 3)),
                            ((2, 3, 4, 5), (-2, -3)),
+                           ((5, 0), None),
                            ((5, 0), (0, )),
                            ((5, 0), (1, )),
+                           ((5, 0), ()),
+                           ((), None),
                            ((), ())]:
             x = TensorType('float64', [(entry == 1) for entry in xsh])('x')
             e = CAReduce(scalar_op, axis = tosum)(x)

theano/tensor/tests/test_opt_uncanonicalize.py

@@ -2,10 +2,11 @@ import unittest
 
 import numpy
 
-from theano import function,config
+from theano import function, config
+from theano import scalar
 import theano.tensor as tensor
 #from theano.tensor import matrix,max_and_argmax,MaaxAndArgmax,neg
-from theano.tensor.elemwise import CAReduce
+from theano.tensor.elemwise import CAReduce, Elemwise
 from theano.tests import unittest_tools as utt
 
 
@@ -44,7 +45,8 @@ class T_min_max(unittest.TestCase):
         f = function([n],tensor.max(-n,0))
         topo = f.maker.env.toposort()
         assert len(topo)==2
-        assert topo[0].op==tensor.neg
+        assert isinstance(topo[0].op, Elemwise)
+        assert isinstance(topo[0].op.scalar_op, scalar.Neg)
         assert isinstance(topo[1].op,CAReduce)
         f(data)
 
@@ -52,7 +54,8 @@ class T_min_max(unittest.TestCase):
         topo = f.maker.env.toposort()
         assert len(topo)==2
         assert isinstance(topo[0].op,CAReduce)
-        assert topo[1].op==tensor.neg
+        assert isinstance(topo[1].op, Elemwise)
+        assert isinstance(topo[1].op.scalar_op, scalar.Neg)
         f(data)
 
         f = function([n],-tensor.max(-n,0))
@@ -76,13 +79,15 @@ class T_min_max(unittest.TestCase):
         topo = f.maker.env.toposort()
         assert len(topo)==2
         assert isinstance(topo[0].op,CAReduce)#max
-        assert topo[1].op==tensor.neg
+        assert isinstance(topo[1].op, Elemwise)
+        assert isinstance(topo[1].op.scalar_op, scalar.Neg)
         f(data)
 
         f = function([n],-tensor.min(n,0))
         topo = f.maker.env.toposort()
         assert len(topo)==2
-        assert topo[0].op==tensor.neg
+        assert isinstance(topo[0].op, Elemwise)
+        assert isinstance(topo[0].op.scalar_op, scalar.Neg)
         assert isinstance(topo[1].op,CAReduce)#max
         f(data)