Fix small errors following review and make make_vector_op an instance too.

theano/sandbox/cuda/tests/test_basic_ops.py

@@ -956,7 +956,7 @@ class T_Join_and_Split(theano.tensor.tests.test_basic.T_Join_and_Split):
         # No gpu split.
         self.split_op = tensor.Split
         # No Make vector on the gpu, Join used instead
-        self.make_vector_op = cuda.GpuJoin
+        self.make_vector_op = cuda.GpuJoin()
         self.floatX = "float32"
         # In FAST_COMPILE mode, we force the FAST_RUN mode for optimization.
         self.hide_error = theano.config.mode not in ['DebugMode', 'DEBUG_MODE']

theano/sandbox/gpuarray/tests/test_basic_ops.py

@@ -305,7 +305,7 @@ class TestAlloc(theano.tensor.tests.test_basic.TestAlloc):
     dtype = "float32"
     mode = mode_with_gpu
     shared = staticmethod(gpuarray_shared_constructor)
-    allocs = [GpuAlloc(), GpuAlloc(), T.Alloc]
+    allocs = [GpuAlloc(), GpuAlloc(), T.Alloc()]
 
 
 def test_shape():
@@ -366,7 +366,7 @@ class G_Join_and_Split(test_basic.T_Join_and_Split):
         self.join_op = GpuJoin()
         self.split_op = GpuSplit
         # Use join instead of MakeVector since there is no MakeVector on GPU
-        self.make_vector_op = GpuJoin
+        self.make_vector_op = GpuJoin()
         # this is to avoid errors with limited devices
         self.floatX = 'float32'
         self.hide_error = theano.config.mode not in ['DebugMode', 'DEBUG_MODE']

theano/tensor/tests/test_basic.py

@@ -3194,7 +3194,7 @@ class T_Join_and_Split(unittest.TestCase):
         )
         self.join_op = Join()
         self.split_op = Split
-        self.make_vector_op = opt.MakeVector
+        self.make_vector_op = opt.MakeVector()
         self.floatX = config.floatX
         self.hide_error = theano.config.mode not in ['DebugMode',
                                                      'DEBUG_MODE',
@@ -3217,7 +3217,8 @@ class T_Join_and_Split(unittest.TestCase):
             make_vector_op = self.make_vector_op
         f = theano.function([], outputs, self.mode)
         topo = f.maker.fgraph.toposort()
-        assert [True for node in topo if isinstance(node.op, make_vector_op)]
+        assert [True for node in topo
+                if isinstance(node.op, type(make_vector_op))]
         variables = f()
         if isinstance(variables, (tuple, list)) and len(variables) == 1:
             return variables[0]