Fix while loop and nasty stack over dtypes

Author: Ian Schweer

pytensor/link/pytorch/dispatch/scalar.py

@@ -67,7 +67,7 @@ def scalar_loop(steps, *start_and_constants):
                 *carry, done = update(*carry, *constants)
                 if done:
                     break
-            return torch.stack((*carry, done))
+            return torch.stack(carry), torch.tensor([done])
     else:
 
         def scalar_loop(*args):

tests/link/pytorch/test_basic.py

@@ -401,6 +401,9 @@ def test_ScalarLoop_while():
 
     op = ScalarLoop(init=[x0], update=[x], until=until)
     fn = function([n_steps, x0], op(n_steps, x0), mode=pytorch_mode)
-    np.testing.assert_allclose(fn(n_steps=20, x0=0), [10, True])
-    np.testing.assert_allclose(fn(n_steps=20, x0=1), [10, True])
-    np.testing.assert_allclose(fn(n_steps=5, x0=1), [6, False])
+    for res, expected in zip(
+        [fn(n_steps=20, x0=0), fn(n_steps=20, x0=1), fn(n_steps=5, x0=1)],
+        [[10, True], [10, True], [6, False]],
+    ):
+        np.testing.assert_allclose(res[0], np.array(expected[0]))
+        np.testing.assert_allclose(res[1], np.array(expected[1]))