Please also provide the following information in addition to your question:

- Operating System: macOS 10.14.5
- brms Version: 2.9.0

When using a custom family to run kfold with plan(multiprocessing), it can’t seem to find log_lik functions that are in the global environment. I could only get it to work with my custom family if I turned the log_lik into a single function and passed it in the log_lik flag when creating the custom family. On the other hand, if I ran it normally (with plan(sequential)), this wasn’t a problem so seems to be an issue of passing environment variables to the processes in future.

Here is a reproducible example from only code from the vignettes (just to make sure it wasn’t an issue with my code). I made one small edit so that size was passed in as part of the regression rather than as a stanvar. (Without this edit, I ran into the same issue discussed here: No samples when using reloo on custom_family brmsfit . Is there now a more general solution than the one proposed there by any chance?)

```
library(brms)
data("cbpp", package = "lme4")
log_lik_beta_binomial2 <- function(i, draws) {
mu <- draws$dpars$mu[, i]
phi <- draws$dpars$phi
N <- draws$data$trials[i]
y <- draws$data$Y[i]
beta_binomial2_lpmf(y, mu, phi, N)
}
beta_binomial2 <- custom_family(
"beta_binomial2", dpars = c("mu", "phi"),
links = c("logit", "log"), lb = c(NA, 0),
type = "int", vars = "trials[n]",
log_lik = log_lik_beta_binomial2
)
stan_funs <- "
real beta_binomial2_lpmf(int y, real mu, real phi, int T) {
return beta_binomial_lpmf(y | T, mu * phi, (1 - mu) * phi);
}
int beta_binomial2_rng(real mu, real phi, int T) {
return beta_binomial_rng(T, mu * phi, (1 - mu) * phi);
}
"
stanvars <- stanvar(scode = stan_funs, block = "functions")
fit2 <- brm(
incidence | trials(size) ~ period + (1|herd), data = cbpp,
iter = 200,
family = beta_binomial2, stanvars = stanvars
)
expose_functions(fit2, vectorize = TRUE)
loo(fit2)
kfold(fit2, chains = 1)
library(future)
plan(multiprocess)
kfold(fit2)
```