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/core/lightning.py

@@ -5,7 +5,7 @@ import os
 import warnings
 from abc import ABC, abstractmethod
 from argparse import Namespace
-from typing import Optional, Union, Dict, Callable
+from typing import Any, Callable, Dict, Optional, Union
 
 import torch
 import torch.distributed as dist
@@ -68,6 +68,20 @@ class LightningModule(ABC, GradInformation, ModelIO, ModelHooks):
         #: True if using amp
         self.use_amp = False
 
+    @property
+    def hparams(self) -> Namespace:
+        if not hasattr(self, '_hparams'):
+            return Namespace()
+        assert isinstance(self._hparams, dict)
+        return Namespace(**self._hparams)
+
+    @hparams.setter
+    def hparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
+        """Set the model hyper-parameters."""
+        if isinstance(params, Namespace):
+            params = vars(params)
+        self._hparams = params
+
     def print(self, *args, **kwargs):
         r"""
         Prints only from process 0. Use this in any distributed mode to log only once
@@ -1201,7 +1215,8 @@ class LightningModule(ABC, GradInformation, ModelIO, ModelHooks):
 
         if cls_takes_hparams:
             if ckpt_hparams is not None:
-                hparams = Namespace(**ckpt_hparams)
+                is_namespace = checkpoint.get('hparams_type') == 'namespace'
+                hparams = Namespace(**ckpt_hparams) if is_namespace else ckpt_hparams
             else:
                 warnings.warn(
                     f"Checkpoint does not contain hyperparameters but {cls.__name__}'s __init__ contains"

pytorch_lightning/core/saving.py

@@ -36,16 +36,14 @@ class ModelIO(object):
         """
 
 
-def load_hparams_from_tags_csv(tags_csv):
+def load_hparams_from_tags_csv(tags_csv) -> Namespace:
     if not os.path.isfile(tags_csv):
         log.warning(f'Missing Tags: {tags_csv}.')
         return Namespace()
 
-    tags = {}
     with open(tags_csv) as f:
         csv_reader = csv.reader(f, delimiter=',')
-        for row in list(csv_reader)[1:]:
-            tags[row[0]] = convert(row[1])
+        tags = {row[0]: convert(row[1]) for row in list(csv_reader)[1:]}
     ns = Namespace(**tags)
     return ns