make tensor.stack generate MakeVector instead of Join more often. test it.

theano/tensor/basic.py

@@ -3271,7 +3271,8 @@ def stack(*tensors):
     # It makes the graph simpler, by not adding DimShuffles and Rebroadcasts
     if numpy.all([isinstance(t, Variable) and\
                   isinstance(t.type, TensorType) and\
-                  t.ndim==0 and t.type==tensors[0].type\
+                  t.ndim==0 and \
+                  t.type.__class__==tensors[0].type.__class__\
                   for t in tensors]):
         return theano.tensor.opt.MakeVector(scal.upcast(*[i.dtype for i in tensors]))(*tensors)
     return join(0, *[shape_padleft(t, 1) for t in tensors])

theano/tensor/tests/test_basic.py

@@ -1552,6 +1552,20 @@ class T_Join_and_Split(unittest.TestCase):
         assert len([n for n in e if isinstance(n, Join)]) == 0
         assert f.maker.env.outputs[0].dtype == config.floatX
 
+    def test_stack_scalar_make_vector_dtype(self):
+        '''Test that calling stack() on scalars instantiates MakeVector,
+        event when the scalar don't have the same dtype.'''
+        a = tensor.iscalar('a')
+        b = tensor.lscalar('b')
+        s = stack(a, b, a, b)
+        f = function([a,b], s)
+        val = f(1,2)
+        self.failUnless(numpy.all(val == [1,2,1,2]))
+        e = f.maker.env.toposort()
+        assert len([n for n in e if isinstance(n.op,opt.MakeVector)]) > 0
+        assert len([n for n in e if isinstance(n, Join)]) == 0
+        assert f.maker.env.outputs[0].dtype == 'int64'
+
     def test_join_vector(self):
         a = as_tensor_variable(numpy.array([1, 2, 3]))
         b = as_tensor_variable(numpy.array([7, 8, 9]))