hparams as dict [blocked by 1041] (#1029)

* hparams as dict

* hparams as dict

* fixing

* fixing

* fixing

* fixing

* typing

* typing

* chnagelog

* update set hparams

* use setter

* simplify

* chnagelog

* imports

* pylint

* typing

* Update training_io.py

* Update training_io.py

* Update lightning.py

* Update test_trainer.py

* Update __init__.py

* Update base.py

* Update utils.py

* Update test_trainer.py

* Update training_io.py

* Update test_trainer.py

* Update test_trainer.py

* Update test_trainer.py

* Update test_trainer.py

* Update callback_config.py

* Update callback_config.py

* Update test_trainer.py

Co-authored-by: William Falcon <waf2107@columbia.edu>

pytorch_lightning/trainer/training_io.py

@@ -4,9 +4,9 @@ import re
 import signal
 import warnings
 from abc import ABC
+from argparse import Namespace
 from subprocess import call
 from typing import Union
-from copy import deepcopy
 
 import torch
 import torch.distributed as dist
@@ -238,7 +238,9 @@ class TrainerIOMixin(ABC):
         checkpoint['state_dict'] = model.state_dict()
 
         if hasattr(model, "hparams"):
-            checkpoint['hparams'] = vars(model.hparams)
+            is_namespace = isinstance(model.hparams, Namespace)
+            checkpoint['hparams'] = vars(model.hparams) if is_namespace else model.hparams
+            checkpoint['hparams_type'] = 'namespace' if is_namespace else 'dict'
         else:
             warnings.warn(
                 "Did not find hyperparameters at model.hparams. Saving checkpoint without"
@@ -322,7 +324,7 @@ class TrainerIOMixin(ABC):
     # ----------------------------------
     # PRIVATE OPS
     # ----------------------------------
-    def hpc_save(self, folderpath, logger):
+    def hpc_save(self, folderpath: str, logger):
         # make sure the checkpoint folder exists
         os.makedirs(folderpath, exist_ok=True)
 
@@ -333,7 +335,7 @@ class TrainerIOMixin(ABC):
 
         if not os.path.exists(folderpath):
             os.makedirs(folderpath, exist_ok=True)
-        filepath = '{}/hpc_ckpt_{}.ckpt'.format(folderpath, ckpt_number)
+        filepath = os.path.join(folderpath, f'hpc_ckpt_{ckpt_number}.ckpt')
 
         # give model a chance to do something on hpc_save
         model = self.get_model()