Try caching ensemble_state

src/ert/enkf_main.py

@@ -191,6 +191,7 @@ def sample_prior(
             )
             ensemble.save_parameters(parameter, realization_nr, ds)
 
+    ensemble.refresh_ensemble_state()
     logger.debug(f"sample_prior() time_used {(time.perf_counter() - t):.4f}s")
 
 

src/ert/libres_facade.py

@@ -136,6 +136,7 @@ def load_from_forward_model(
             ensemble,
             [r for r, active in enumerate(realisations) if active],
         )
+        ensemble.refresh_ensemble_state()
         _logger.debug(
             f"load_from_forward_model() time_used {(time.perf_counter() - t):.4f}s"
         )

src/ert/run_models/base_run_model.py

@@ -574,6 +574,8 @@ async def run_ensemble_evaluator_async(
             self._end_queue.get()
             return []
         await evaluator_task
+        ensemble.refresh_ensemble_state()
+
         return evaluator_task.result()
 
     # This function needs to be there for the sake of testing that expects sync ee run

src/ert/storage/local_ensemble.py

@@ -419,6 +419,11 @@ def get_failure(self, realization: int) -> Optional[_Failure]:
             )
         return None
 
+    def refresh_ensemble_state(self) -> None:
+        self.get_ensemble_state.cache_clear()
+        self.get_ensemble_state()
+
+    @lru_cache  # noqa: B019
     def get_ensemble_state(self) -> List[Set[RealizationStorageState]]:
         """
         Retrieve the state of each realization within ensemble.