diff --git a/opacus/optimizers/optimizer.py b/opacus/optimizers/optimizer.py
index bbd554a6..bb6c5fa9 100644
--- a/opacus/optimizers/optimizer.py
+++ b/opacus/optimizers/optimizer.py
@@ -15,6 +15,7 @@
 from __future__ import annotations
 
 import logging
+from collections import defaultdict
 from typing import Callable, List, Optional, Union
 
 import torch
@@ -376,6 +377,50 @@ def accumulated_iterations(self) -> int:
             )
         return vals[0]
 
+    @property
+    def param_groups(self) -> List[dict]:
+        """
+        Returns a list containing a dictionary of all parameters managed by the optimizer.
+        """
+        return self.original_optimizer.param_groups
+
+    @param_groups.setter
+    def param_groups(self, param_groups: List[dict]):
+        """
+        Updates the param_groups of the optimizer, where param_groups is a list containg a dictionary
+        of all parameters mangaged by the optimizer.
+        """
+        self.original_optimizer.param_groups = param_groups
+    
+
+    @property 
+    def state(self) -> defaultdict:
+        """
+        Returns a dictionary holding current optimization state.
+        """
+        return self.original_optimizer.state
+    
+    @state.setter
+    def state(self, state: defaultdict):
+        """
+        Updates the state of the optimizer, where state is a dictionary holding current optimization state.
+        """
+        self.original_optimizer.state = state
+    
+    @property
+    def defaults(self) -> dict:
+        """
+        Returns a dictionary containing default values for optimization.
+        """
+        return self.original_optimizer.defaults
+    
+    @defaults.setter
+    def defaults(self, defaults: dict):
+        """
+        Updates the defaults of the optimizer, where defaults is a dictionary containing default values for optimization.
+        """
+        self.original_optimizer.defaults = defaults
+
     def attach_step_hook(self, fn: Callable[[DPOptimizer], None]):
         """
         Attaches a hook to be executed after gradient clipping/noising, but before the