Clean up config object loading and code duplication

fltk/util/config/__init__.py

@@ -1,15 +1,10 @@
 from __future__ import annotations
 
-import json
 from pathlib import Path
 from typing import Optional, Union, Type, Dict
 
-import torch
-import yaml
 import logging
 
-from torch.nn.modules.loss import _Loss
-
 from fltk.util.config.definitions import Loss
 
 from fltk.util.config.distributed_config import DistributedConfig
@@ -45,15 +40,15 @@ def get_distributed_config(args, alt_path: str = None) -> Optional[DistributedCo
 
 
 def get_learning_param_config(args, alt_path: str = None) -> Optional[DistLearningConfig]:
+    """
+    Retrieve learning parameter configuration from Disk for distributed learning experiments.
+    """
     if args:
         config_path = args.experiment_config
     else:
         config_path = alt_path
-    safe_loader = get_safe_loader()
     try:
-        with open(config_path) as f:
-            learning_params_dict = yaml.load(f, Loader=safe_loader)
-            learning_params = DistLearningConfig.from_dict(learning_params_dict)
+        learning_params = DistLearningConfig.from_yaml(Path(config_path))
     except Exception as e:
         msg = f"Failed to get learning parameter configuration for distributed experiments: {e}"
         logging.info(msg)