Fix a RandomVariable DimShuffle lift case for empty sizes

aesara/tensor/random/opt.py

@@ -177,9 +177,10 @@ def local_dimshuffle_rv_lift(fgraph, node):
         # Update the `size` array to reflect the `DimShuffle`d dimensions,
         # since the trailing dimensions in `size` represent the independent
         # variates dimensions (for univariate distributions, at least)
+        has_size = get_vector_length(size) > 0
         new_size = (
             [constant(1, dtype="int64") if o == "x" else size[o] for o in ds_new_order]
-            if get_vector_length(size) > 0
+            if has_size
             else size
         )
 
@@ -190,6 +191,14 @@ def local_dimshuffle_rv_lift(fgraph, node):
                 d - reps_ind_split_idx if isinstance(d, int) else d
                 for d in ds_new_order[ds_ind_new_dims[0][0] :]
             ]
+
+            if not has_size and len(ds_new_order[: ds_ind_new_dims[0][0]]) > 0:
+                # Additional broadcast dimensions need to be added to the
+                # independent dimensions (i.e. parameters), since there's no
+                # `size` to which they can be added
+                rv_params_new_order = (
+                    list(ds_new_order[: ds_ind_new_dims[0][0]]) + rv_params_new_order
+                )
         else:
             # This case is reached when, for example, `ds_new_order` only
             # consists of new broadcastable dimensions (i.e. `"x"`s)

tests/tensor/random/test_opt.py

@@ -147,6 +147,17 @@ def test_local_rv_size_lift(dist_op, dist_params, size):
 @pytest.mark.parametrize(
     "ds_order, lifted, dist_op, dist_params, size, rtol",
     [
+        (
+            ("x", 0),
+            True,
+            normal,
+            (
+                np.array([0.0, -100.0], dtype=np.float64),
+                np.array(1e-6, dtype=np.float64),
+            ),
+            (),
+            1e-7,
+        ),
         (
             ("x",),
             True,