New Model, Many Changes

_templates/new_project/utils/module_mixins.py

@@ -61,10 +61,11 @@ class BaseTrainMixin:
         assert isinstance(self, LightningBaseModule)
         keys = list(outputs[0].keys())
 
-        summary_dict = dict(log={f'mean_{key}': torch.mean(torch.stack([output[key]
-                                                                        for output in outputs]))
-                                 for key in keys if 'loss' in key})
-        return summary_dict
+        summary_dict = {f'mean_{key}': torch.mean(torch.stack([output[key]
+                                                               for output in outputs]))
+                        for key in keys if 'loss' in key}
+        for key in summary_dict.keys():
+            self.log(key, summary_dict[key])
 
 
 class BaseValMixin:
@@ -83,16 +84,16 @@ class BaseValMixin:
 
     def validation_epoch_end(self, outputs, *_, **__):
         assert isinstance(self, LightningBaseModule)
-        summary_dict = dict(log=dict())
+        summary_dict = dict()
         # In case of Multiple given dataloader this will outputs will be: list[list[dict[]]]
         # for output_idx, output in enumerate(outputs):
         # else:list[dict[]]
         keys = list(outputs.keys())
         # Add Every Value das has a "loss" in it, by calc. mean over all occurences.
-        summary_dict['log'].update({f'mean_{key}': torch.mean(torch.stack([output[key]
-                                                                           for output in outputs]))
-                                    for key in keys if 'loss' in key}
-                                   )
+        summary_dict.update({f'mean_{key}': torch.mean(torch.stack([output[key]
+                                                                    for output in outputs]))
+                             for key in keys if 'loss' in key}
+                            )
         """
         # Additional Score like the unweighted Average Recall:
         # UnweightedAverageRecall
@@ -107,7 +108,8 @@ class BaseValMixin:
         summary_dict['log'].update({f'uar_score': uar_score})
         """
 
-        return summary_dict
+        for key in summary_dict.keys():
+            self.log(key, summary_dict[key])
 
 
 class BinaryMaskDatasetMixin:

_templates/new_project/utils/project_config.py

@@ -1,8 +1,5 @@
 from argparse import Namespace
 
-from ml_lib.utils.config import Config
-
-
 class GlobalVar(Namespace):
     # Labels for classes
     LEFT = 1
@@ -21,10 +18,3 @@ class GlobalVar(Namespace):
     train='train',
     vali='vali',
     test='test'
-
-
-class ThisConfig(Config):
-
-    @property
-    def _model_map(self):
-        return dict()