ICC for multiple membership model

I'm trying to estimate the ICC for a multiple membership model estimated with brms. There are students (level 1) nested in teachers (T1_ID, level 2) and classrooms (C1_ID, also level 2). I get an estimate if I condition on all random effects, that is not specifying re.form. However, I'd like to get estimates for the two level 2 effects separately. Is there a way to do this with the performance package? When I tried I got the error message:

Error in is(sexpr, "try-error") : argument "sexpr" is missing, with no default

My model is
Fixed.FAPs.int.fixed <- brm(PFixedT3 ~ 0 + Intercept + (0 + Intercept |p| mm(T1_ID, T2_ID, T3_ID, T4_ID, weights = cbind(W_T1, W_T2, W_T3, W_T4))) + (0 + Intercept |q| mm(C1_ID, C2_ID, C3_ID, C4_ID, weights = cbind(W_C1, W_C2, W_C3, W_C4))), family = skew_normal(), data=data_fixed, control = list(adapt_delta = 0.99), inits = 0, cores = 4)

and for the ICC for teachers

icc(Fixed.FAPs.int.fixed, re.form = ~ (0 + Intercept |p| mm(T1_ID, T2_ID, T3_ID, T4_ID, weights = cbind(W_T1, W_T2, W_T3, W_T4))))

Any ideas? Thanks

Start with the icc() entry point and inspect how its re.form argument handles the brms multiple-membership random effects shown in the issue. Done means determining whether separate teacher and classroom ICC estimates can be produced without the reported error, with the limitation or supported behavior made clear.