Checking if the parameters are a DictConfig Object (#2216)

* Checking if the parameters are a DictConfig Object

This is in reference to #2058 . 

To be honest, I have no idea how I should go about writing a test for this.

* Update pytorch_lightning/loggers/base.py

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>

* fix ...

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Jirka <jirka@pytorchlightning.ai>

pytorch_lightning/loggers/base.py

@@ -3,13 +3,11 @@
 import operator
 from abc import ABC, abstractmethod
 from argparse import Namespace
-from typing import Union, Optional, Dict, Iterable, Any, Callable, List, Sequence, Mapping, Tuple
+from typing import Union, Optional, Dict, Iterable, Any, Callable, List, Sequence, Mapping, Tuple, MutableMapping
 
 import numpy as np
 import torch
 
-from pytorch_lightning.utilities import rank_zero_only
-
 
 class LightningLoggerBase(ABC):
     """
@@ -174,9 +172,9 @@ def _flatten_dict(params: Dict[str, Any], delimiter: str = '/') -> Dict[str, Any
 
         def _dict_generator(input_dict, prefixes=None):
             prefixes = prefixes[:] if prefixes else []
-            if isinstance(input_dict, dict):
+            if isinstance(input_dict, MutableMapping):
                 for key, value in input_dict.items():
-                    if isinstance(value, (dict, Namespace)):
+                    if isinstance(value, (MutableMapping, Namespace)):
                         value = vars(value) if isinstance(value, Namespace) else value
                         for d in _dict_generator(value, prefixes + [key]):
                             yield d