test if these needed

cobaya/run.py

@@ -61,6 +61,7 @@ def run(info_or_yaml_or_file: Union[InputDict, str, os.PathLike],
     # as early as possible, e.g. to check if resuming possible or `force` needed.
     if no_mpi or test:
         mpi.set_mpi_disabled()
+    mpi.sync_processes()
     with mpi.ProcessState("run"):
         flags = {packages_path_input: packages_path, "debug": debug,
                  "stop_at_error": stop_at_error, "resume": resume, "force": force,

cobaya/samplers/mcmc/mcmc.py

@@ -255,7 +255,7 @@ def n_fast(self):
         """Number of parameters which are considered fast, in binary fast/slow splits."""
         return len(self.fast_params)
 
-    def get_acceptance_rate(self, first=0, last=None):
+    def get_acceptance_rate(self, first=0, last=None) -> np.floating:
         """
         Computes the current acceptance rate, optionally only for ``[first:last]``
         subchain.
@@ -698,12 +698,12 @@ def check_convergence_and_learn_proposal(self):
             acceptance_rate = (np.average(acceptance_rates, weights=Ns)
                                if acceptance_rates is not None else acceptance_rate)
             if self.oversample_thin > 1:
-                weights_multi_str = (" = 1/avg(%r)" % list(acceptance_rates)
+                weights_multi_str = (" = 1/avg(%r)" % acceptance_rates.tolist()
                                      if acceptance_rates is not None else "")
                 self.log.info(" - Average thinned weight: %.3f%s", 1 / acceptance_rate,
                               weights_multi_str)
             else:
-                accpt_multi_str = (" = avg(%r)" % list(acceptance_rates)
+                accpt_multi_str = (" = avg(%r)" % acceptance_rates.tolist()
                                    if acceptance_rates is not None else "")
                 self.log.info(" - Acceptance rate: %.3f%s", acceptance_rate,
                               accpt_multi_str)