Numba typify: Use more robust ListType

Author: ricardoV94

pytensor/link/numba/dispatch/basic.py

@@ -134,7 +134,7 @@ def get_numba_type(
     elif isinstance(pytensor_type, RandomGeneratorType):
         return numba.types.NumPyRandomGeneratorType("NumPyRandomGeneratorType")
     elif isinstance(pytensor_type, TypedListType):
-        return numba.types.List(get_numba_type(pytensor_type.ttype))
+        return numba.types.ListType(get_numba_type(pytensor_type.ttype))
     else:
         raise NotImplementedError(f"Numba type not implemented for {pytensor_type}")
 

pytensor/link/numba/dispatch/typed_list.py

@@ -1,6 +1,6 @@
 import numba
 import numpy as np
-from numba.types import Array, Boolean, List, Number
+from numba.types import Array, Boolean, List, ListType, Number
 
 import pytensor.link.numba.dispatch.basic as numba_basic
 from pytensor.link.numba.dispatch.basic import (
@@ -42,7 +42,7 @@ def numba_all_equal(x, y):
 def list_all_equal(x, y):
     all_equal = None
 
-    if isinstance(x, List) and isinstance(y, List):
+    if isinstance(x, List | ListType) and isinstance(y, List | ListType):
 
         def all_equal(x, y):
             if len(x) != len(y):
@@ -69,7 +69,7 @@ def all_equal(x, y):
 
 @numba.extending.overload(numba_deepcopy)
 def numba_deepcopy_list(x):
-    if isinstance(x, List):
+    if isinstance(x, List | ListType):
 
         def deepcopy_list(x):
             return [numba_deepcopy(xi) for xi in x]