Clean up some usage of the TensorType interface in Scan

aesara/scan/op.py

@@ -161,8 +161,9 @@ def check_broadcast(v1, v2):
     which may wrongly be interpreted as broadcastable.
 
     """
-    if not hasattr(v1, "broadcastable") and not hasattr(v2, "broadcastable"):
+    if not isinstance(v1.type, TensorType) and not isinstance(v2.type, TensorType):
         return
+
     msg = (
         "The broadcast pattern of the output of scan (%s) is "
         "inconsistent with the one provided in `output_info` "
@@ -173,13 +174,13 @@ def check_broadcast(v1, v2):
         "them consistent, e.g. using aesara.tensor."
         "{unbroadcast, specify_broadcastable}."
     )
-    size = min(len(v1.broadcastable), len(v2.broadcastable))
+    size = min(v1.type.ndim, v2.type.ndim)
     for n, (b1, b2) in enumerate(
-        zip(v1.broadcastable[-size:], v2.broadcastable[-size:])
+        zip(v1.type.broadcastable[-size:], v2.type.broadcastable[-size:])
     ):
         if b1 != b2:
-            a1 = n + size - len(v1.broadcastable) + 1
-            a2 = n + size - len(v2.broadcastable) + 1
+            a1 = n + size - v1.type.ndim + 1
+            a2 = n + size - v2.type.ndim + 1
             raise TypeError(msg % (v1.type, v2.type, a1, b1, b2, a2))
 
 
@@ -628,6 +629,7 @@ def validate_inner_graph(self):
                 type_input = self.inner_inputs[inner_iidx].type
                 type_output = self.inner_outputs[inner_oidx].type
                 if (
+                    # TODO: Use the `Type` interface for this
                     type_input.dtype != type_output.dtype
                     or type_input.broadcastable != type_output.broadcastable
                 ):