[Python] How to create a Sympy IndexedBase using a custom subclass of Symbol?

I want to create a 2-D matrix of binary variables x. For now I do it like this: x = IndexedBase('x', shape=(imax,jmax), integer=True)

For a binary variable, the following identity holds: x_i**n == x_i for n>0, and I want to make use of this identity for simplifying my expressions later on. Therefore, the 'integer' assumption should be replaced with a "stronger" 'binary' assumption.

Creating a single binary variable works (Ref: https://stackoverflow.com/a/73953040/7740977):

from sympy import *

class Binary(Symbol):
def _eval_power(self, other):
return self

x0 = Binary('x0')
x0**2 == x0


Output: True

What I'm struggling with right now is creating an IndexedBase object where its entries are instances of my Binary class rather than of Symbol. Looking at https://docs.sympy.org/latest/modules/tensor/indexed.html#sympy.tensor.indexed.IndexedBase I saw that assumptions can be inherited if a Symbol is used to initialize the IndexedBase, which led me to unsuccessfully try the following:

x = symbols('x', cls=Binary)
x = IndexedBase(x)

x[0,0]**2 == x[0,0]


Output: False (expected True)

Is there another way to get IndexedBase to use my custom Binary class?

Many thanks in advance!

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