test if these needed

cobaya/run.py

@@ -61,7 +61,6 @@ 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/typing.py

@@ -1,6 +1,7 @@
 from typing import Dict, Any, Optional, Union, Type, TypedDict, Literal, Mapping, \
     Callable, Sequence, Iterable
 from types import MappingProxyType
+import contextlib
 import typing
 import numbers
 import numpy as np
@@ -112,6 +113,21 @@ class InputDict(ModelDict, total=False):
 enforce_type_checking = None
 
 
+@contextlib.contextmanager
+def type_checking(value: bool):
+    """
+    Context manager to temporarily set typing.enforce_type_checking to a specific value.
+    Restores the original value when exiting the context.
+    """
+    global enforce_type_checking
+    original_value = enforce_type_checking
+    enforce_type_checking = value
+    try:
+        yield
+    finally:
+        enforce_type_checking = original_value
+
+
 def validate_type(expected_type: type, value: Any, path: str = ''):
     """
     Checks for soft compatibility of a value with a type.

tests/test_mcmc.py

@@ -10,6 +10,7 @@
 from cobaya.tools import KL_norm
 from cobaya.yaml import yaml_load
 from .common_sampler import body_of_sampler_test, body_of_test_speeds
+from cobaya.typing import type_checking
 
 pytestmark = pytest.mark.mpi
 
@@ -39,7 +40,7 @@ def test_mcmc(tmpdir, temperature, do_plots, packages_path=None):
 
     def check_gaussian(sampler_instance):
         if not len(sampler_instance.collection) or \
-           not len(sampler_instance.collection[int(sampler_instance.n() / 2):]):
+                not len(sampler_instance.collection[int(sampler_instance.n() / 2):]):
             return
         proposer = KL_norm(
             S1=sampler_instance.model.likelihood["gaussian_mixture"].covs[0],
@@ -162,7 +163,7 @@ def test_mcmc_sync():
     logger.info('Test error synchronization')
     if mpi.rank() == 0:
         info['sampler']['mcmc'] = {'max_samples': 'bad_val'}
-        with NoLogging(logging.ERROR), pytest.raises(TypeError):
+        with NoLogging(logging.ERROR), pytest.raises(TypeError), type_checking(False):
             run(info)
     else:
         with pytest.raises(mpi.OtherProcessError):