As to your last point: inits and init_r provide starting values for model parameters in the MCMC sampling. See this post for a more elaborate explanation of this, but in short, the sampler will take the initial values and evaluate the log-posterior based on them. If this evaluation fails, i.e. it returns Inf / -Inf the sampler will try different initial values. However, it can happen that the initiation fails over and over again and does not even start. The init_r = 0.1 tells the sampler to try initial values between -0.1 and 0.1 (instead -2 and 2 which is the default). As these starting values are in fact sampled randomly, it might happen that in some cases the sampler will end up with starting values that work and beginn sampling, and in other situations it will not and show you the “initiation failed” message you describe above. It can also happen that some chains start sampling and others fail to initialize. My hinge is that this is what might have happend in your case: The model initializes fine when you first run it, but during reloo, when it is refit, it fails to initialize (for some chains) and returns you the error.
Have you tried the other option (specifying inits = "0") ? This often solves initiation problems and if it works it will work all the time because the starting values are always the same.
Another point with reloo is that I am not sure whether the specification of init_r = .10 or inits = "0" must be directly passed to reloo by specifying e,g, reloo_args = list(inits = "0") (@avehtari I hope it is ok if I tag you but is this the case? A quick google search did not help me to find out if this was necessary) .
I hope this helps!