Creating local_state directory, and saving state to it

openfl-docker/gramine_app/fx.manifest.template

@@ -64,6 +64,7 @@ sgx.trusted_files = [
 # One should be conservative as to which files are allowed, these can be modified by enclave.
 sgx.allowed_files = [
   "file:{{ workspace_root }}/save",
+  "file:{{ workspace_root }}/local_state",
   "file:{{ workspace_root }}/logs",
   "file:{{ workspace_root }}/cert",
   "file:{{ workspace_root }}/data",

openfl-workspace/workspace/plan/defaults/aggregator.yaml

@@ -2,4 +2,4 @@ template : openfl.component.Aggregator
 settings :
     db_store_rounds : 2
     persist_checkpoint: True
-    persistent_db_path: save/tensor.db
+    persistent_db_path: local_state/tensor.db

openfl/component/aggregator/aggregator.py

@@ -1070,7 +1070,7 @@ def _compute_validation_related_task_metrics(self, task_name) -> dict:
 
                 # FIXME: Configurable logic for min/max criteria in saving best.
                 if "validate_agg" in tags:
-                    # Compare the accuracy of the model, potentially save it
+                    # Compare the accuracy of the model, potentially save it.
                     if self.best_model_score is None or self.best_model_score < agg_results:
                         logger.info(
                             f"Round {round_number}: saved the best model with score {agg_results:f}"

openfl/interface/interactive_api/experiment.py

@@ -103,6 +103,7 @@ def _initialize_plan(self):
         # Create a folder to store plans
         os.makedirs("./plan", exist_ok=True)
         os.makedirs("./save", exist_ok=True)
+        os.makedirs("./local_state", exist_ok=True)
         # Load the default plan
         base_plan_path = WORKSPACE / "workspace/plan/plans/default/base_plan_interactive_api.yaml"
         plan = Plan.parse(base_plan_path, resolve=False)

openfl/interface/workspace.py

@@ -66,6 +66,7 @@ def create_dirs(prefix):
     (prefix / "data").mkdir(parents=True, exist_ok=True)  # training data
     (prefix / "logs").mkdir(parents=True, exist_ok=True)  # training logs
     (prefix / "save").mkdir(parents=True, exist_ok=True)  # model weight saves / initialization
+    (prefix / "local_state").mkdir(parents=True, exist_ok=True)  # persistent state
     (prefix / "src").mkdir(parents=True, exist_ok=True)  # model code
 
     shutil.copyfile(WORKSPACE / "workspace" / ".workspace", prefix / ".workspace")
@@ -354,6 +355,7 @@ def export_() -> str:
     # os.makedirs(os.path.join(tmp_dir, 'save'), exist_ok=True)
     os.makedirs(os.path.join(tmp_dir, "logs"), exist_ok=True)
     os.makedirs(os.path.join(tmp_dir, "data"), exist_ok=True)
+    os.makedirs(os.path.join(tmp_dir, "local_state"), exist_ok=True)
     shutil.copytree("src", os.path.join(tmp_dir, "src"), ignore=ignore)
     shutil.copytree("plan", os.path.join(tmp_dir, "plan"), ignore=ignore)
     shutil.copytree("save", os.path.join(tmp_dir, "save"))

tests/openfl/federated/plan/plan_example.yaml

@@ -9,6 +9,7 @@ aggregator :
     best_state_path : save/best.pbuf
     last_state_path : save/last.pbuf
     rounds_to_train : 10
+    persistent_db_path: tensor.db
 
 collaborator :
   defaults : plan/defaults/collaborator.yaml