From b61d495109be79bd02d4172d7570f28a2920c652 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Paul-Christian=20B=C3=BCrkner?= <paul.buerkner@gmail.com>
Date: Mon, 27 May 2024 19:17:11 +0200
Subject: [PATCH] fix issue #1658

---
 DESCRIPTION |  2 +-
 NEWS.md     |  3 +++
 R/misc.R    | 17 ++++++++++-------
 3 files changed, 14 insertions(+), 8 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 34a7f2ea5..8cdfd9570 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -2,7 +2,7 @@ Package: brms
 Encoding: UTF-8
 Type: Package
 Title: Bayesian Regression Models using 'Stan'
-Version: 2.21.4
+Version: 2.21.5
 Date: 2024-05-27
 Authors@R:
     c(person("Paul-Christian", "Bürkner", email = "paul.buerkner@gmail.com",
diff --git a/NEWS.md b/NEWS.md
index 1566163a5..3ddffe64f 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -8,6 +8,9 @@
 
 * Fix a bug that led to partially duplicated Stan code in multilevel terms
 thanks to Henrik Singmann. (#1651)
+* Fix problems with parallel executions of post-processing functions 
+sometimes leaving unused R instances behind. Thanks to Andrew Johnson,
+Aki Vehtari, and Noa Kallioinen. (#1658)
 
 ### Other Changes
 
diff --git a/R/misc.R b/R/misc.R
index 00ef9a150..2da709f1b 100644
--- a/R/misc.R
+++ b/R/misc.R
@@ -425,13 +425,16 @@ plapply <- function(X, FUN, cores = 1, ...) {
   if (cores == 1) {
     out <- lapply(X, FUN, ...)
   } else {
-    if (!os_is_windows()) {
-      out <- parallel::mclapply(X = X, FUN = FUN, mc.cores = cores, ...)
-    } else {
-      cl <- parallel::makePSOCKcluster(cores)
-      on.exit(parallel::stopCluster(cl))
-      out <- parallel::parLapply(cl = cl, X = X, fun = FUN, ...)
-    }
+    cl_type <- ifelse(os_is_windows(), "PSOCK", "FORK")
+    cl <- parallel::makeCluster(cores, type = cl_type)
+    # Register a cleanup for the cluster in case the function fails
+    # Need to wrap in a tryCatch to avoid error if cluster is already stopped
+    on.exit(tryCatch(
+      { parallel::stopCluster(cl) },
+      error = function(e) invisible(NULL)
+    ))
+    out <- parallel::parLapply(cl = cl, X = X, fun = FUN, ...)
+    parallel::stopCluster(cl)
   }
   out
 }