Fix get_canonical_form_slice when lengths are numpy integers

Introduced in f9dfe70

Author: ricardoV94

pytensor/tensor/subtensor.py

@@ -305,9 +305,9 @@ def get_canonical_form_slice(
 
     # At this point we have a slice object. Possibly with symbolic inputs.
 
-    def analyze(x):
+    def analyze(x) -> tuple[int | Variable, bool]:
         try:
-            x_constant = as_index_literal(x)
+            x_constant = int(as_index_literal(x))
             is_constant = True
         except NotScalarConstantError:
             x_constant = x

tests/tensor/test_subtensor.py

@@ -154,8 +154,11 @@ def test_symbolic_tensor(self):
         assert isinstance(res[0].owner.op, ptb.ScalarFromTensor)
         assert res[1] == 1
 
-    def test_all_integer(self):
-        res = get_canonical_form_slice(slice(1, 5, 2), 7)
+    @pytest.mark.parametrize("int_fn", [int, np.int64, as_tensor, as_scalar])
+    def test_all_integer(self, int_fn):
+        res = get_canonical_form_slice(
+            slice(int_fn(1), int_fn(5), int_fn(2)), int_fn(7)
+        )
         assert isinstance(res[0], slice)
         assert res[1] == 1