[Clarification] Divergences during sample_prior = "only" model fitting

Interfaces brms
11

I run a series of tests with priors like the following

circular_prior = c(prior(normal(0, 1), nlpar = "wSelf"),
                   prior(normal(0, 1), nlpar = "wOthers"),
                   prior(normal(0, 1), nlpar = "aSelf"),
                   prior(normal(0, 1), nlpar = "aOthers"),
                   prior(normal(0, 1), nlpar = "bias"),
                   prior(normal(0, .5), nlpar = "wSelf",class="sd"),
                   prior(normal(0, .5), nlpar = "wOthers",class="sd"),
                   prior(normal(0, .5), nlpar = "aSelf",class="sd"),
                   prior(normal(0, .5), nlpar = "aOthers",class="sd"),
                   prior(normal(0, .5), nlpar = "bias",class="sd"),
                   prior_("lkj(5)", class = "cor"))

The divergences still happen til I reduce the sd prior to variance equal or less than normal(0, .2), tho’ that might be too narrow, since at that point when adding likelihood the posterior does not move compared to the prior