Implement work-around for numba issue https://github.com/numba/numba/issues/8215…

aesara/link/numba/dispatch/tensor_basic.py

 from textwrap import indent
 
-import numba
 import numpy as np
 
 from aesara.link.numba.dispatch import basic as numba_basic
@@ -198,11 +197,13 @@ def makevector({", ".join(input_names)}):
 
 @numba_funcify.register(Rebroadcast)
 def numba_funcify_Rebroadcast(op, **kwargs):
-    op_axis = tuple(op.axis.items())
+    # Make sure op_axis only has ints. This way we can avoid literal_unroll
+    # which causes a segfault, see GH issue https://github.com/numba/numba/issues/8215
+    op_axis = tuple((axis, int(value)) for axis, value in op.axis.items())
 
     @numba_basic.numba_njit
     def rebroadcast(x):
-        for axis, value in numba.literal_unroll(op_axis):
+        for axis, value in op_axis:
             if value and x.shape[axis] != 1:
                 raise ValueError(
                     ("Dimension in Rebroadcast's input was supposed to be 1")