BatchedDot: small improvements

theano/tensor/basic.py

@@ -3547,8 +3547,8 @@ class BatchedDot(Op):
         allocate = """
             if ((NULL == %(_z)s) || !(%(z_shape_correct)s))
             {
-                npy_intp dims[3] = {%(z_shape)s};
-                if (NULL != %(_z)s) Py_XDECREF(%(_z)s);
+                npy_intp dims[%(z_ndim)s] = {%(z_shape)s};
+                Py_XDECREF(%(_z)s);
                 %(_z)s = (PyArrayObject*)PyArray_SimpleNew(
                     %(z_ndim)s, dims, PyArray_TYPE(%(_x)s));
                 if(!%(_z)s) {
@@ -3586,7 +3586,7 @@ class BatchedDot(Op):
                                for axis in shape)
             return """{
                 npy_intp dims[3] = {%(_shape)s};
-                PyArray_Dims newshape = {.ptr = dims, .len = 3};
+                PyArray_Dims newshape = {dims, 3};
                 %(newname)s = (PyArrayObject*)PyArray_Newshape(%(oldname)s, &newshape, NPY_ANYORDER);
                 if (!%(newname)s)
                     %(_fail)s
@@ -3610,8 +3610,7 @@ class BatchedDot(Op):
             upcast.append("ys = %(_y)s; Py_XINCREF(ys);")
         elif y_ndim == 2:
             upcast.append(c_dimshuffle("ys", _y, (0, 1, None)))
-        # upcast of z depends on shapes of both inputs
-        if x_ndim == 3 and y_ndim == 3:
+        if z_ndim == 3:
             upcast.append("zs = %(_z)s; Py_XINCREF(zs);")
         else:
             upcast.append(c_dimshuffle(