Make Any and All return bools.

theano/tensor/elemwise.py

@@ -1703,18 +1703,16 @@ for(int i=0;i<PyArray_NDIM(%(iname)s);i++){
 
 
 class All(CAReduce):
-    """ Applies `bitwise and` to all the values of a tensor along the
+    """ Applies `logical and` to all the values of a tensor along the
     specified axis(es).
 
-    Equivalent to `CAReduce(scalar.and\_, axis=axis)`.
-
     """
 
     def __init__(self, axis=None):
         CAReduce.__init__(self, scalar.and_, axis)
 
     def _output_dtype(self, idtype):
-        return "int8"
+        return "bool"
 
     def __str__(self):
         if self.axis is None:
@@ -1724,7 +1722,7 @@ class All(CAReduce):
 
     def make_node(self, input):
         input = as_tensor_variable(input)
-        if input.dtype not in ["int8", "uint8"]:
+        if input.dtype is not "bool":
             input = theano.tensor.neq(input, 0)
         ret = super(All, self).make_node(input)
         return ret
@@ -1738,15 +1736,13 @@ class Any(CAReduce):
     """ Applies `bitwise or` to all the values of a tensor along the
     specified axis(es).
 
-    Equivalent to `CAReduce(scalar.or\_, axis=axis)`.
-
     """
 
     def __init__(self, axis=None):
         CAReduce.__init__(self, scalar.or_, axis)
 
     def _output_dtype(self, idtype):
-        return "int8"
+        return "bool"
 
     def __str__(self):
         if self.axis is None:
@@ -1756,7 +1752,7 @@ class Any(CAReduce):
 
     def make_node(self, input):
         input = as_tensor_variable(input)
-        if input.dtype not in ["int8", "uint8"]:
+        if input.dtype is not "bool":
             input = theano.tensor.neq(input, 0)
         ret = super(Any, self).make_node(input)
         return ret
@@ -1985,7 +1981,7 @@ class Sum(CAReduceDtype):
 
         out = self(*inp)
 
-        if out.dtype.find('int') != -1:
+        if out.dtype not in theano.tensor.continuous_dtypes:
             return [x.zeros_like(dtype=theano.config.floatX)]
 
         gz, = grads

theano/tensor/tests/test_basic.py

@@ -8178,7 +8178,7 @@ def test_composite_neg_bool():
     # `-numpy.bool_(True)` is False and `-numpy.bool_(False)` is True.
     x = theano.tensor.vector()
     f = theano.function([x], - (x > 0), mode=theano.Mode(linker='py'))
-    utt.assert_allclose(f([-1, 0, 1]), [0, 0, -1])
+    utt.assert_allclose(f([-1, 0, 1]), [False, False, True])
 
 """
 

theano/tensor/tests/test_elemwise.py

@@ -452,10 +452,6 @@ class test_CAReduce(unittest_tools.InferShapeTester):
                 else:
                     self.fail()
             else:
-                # numpy.{all,any} return bool type,
-                # but theano ops return an int8 array instead
-                if scalar_op in [scalar.and_, scalar.or_]:
-                    zv = numpy.asarray(zv, dtype='int8')
                 if test_nan:
                     try:
                         self.assertTrue(