update comments

nnunetv2/evaluation/evaluate_predictions.py

@@ -33,7 +33,7 @@ def key_to_label_or_region(key: str):
 
 def save_summary_json(results: dict, output_file: str):
     """
-    stupid json does not support tuples as keys (why does it have to be so shitty) so we need to convert that shit
+    json does not support tuples as keys (why does it have to be so shitty) so we need to convert that shit
     ourselves
     """
     results_converted = deepcopy(results)

nnunetv2/experiment_planning/experiment_planners/default_experiment_planner.py

@@ -464,7 +464,7 @@ def plan_experiment(self):
         shutil.copy(join(self.raw_dataset_folder, 'dataset.json'),
                     join(nnUNet_preprocessed, self.dataset_name, 'dataset.json'))
 
-        # json is stupid and I hate it... "Object of type int64 is not JSON serializable" -> my ass
+        # json is ###. I hate it... "Object of type int64 is not JSON serializable"
         plans = {
             'dataset_name': self.dataset_name,
             'plans_name': self.plans_identifier,

nnunetv2/inference/predict_from_raw_data.py

@@ -57,7 +57,6 @@ def __init__(self,
         self.use_mirroring = use_mirroring
         if device.type == 'cuda':
             # device = torch.device(type='cuda', index=0)  # set the desired GPU with CUDA_VISIBLE_DEVICES!
-            # why would I ever want to do that. Stupid dobby. This kills DDP inference...
             pass
         if device.type != 'cuda':
             print(f'perform_everything_on_device=True is only supported for cuda devices! Setting this to False')

nnunetv2/preprocessing/resampling/default_resampling.py

@@ -83,7 +83,7 @@ def resample_data_or_seg_to_shape(data: Union[torch.Tensor, np.ndarray],
                                   force_separate_z: Union[bool, None] = False,
                                   separate_z_anisotropy_threshold: float = ANISO_THRESHOLD):
     """
-    needed for segmentation export. Stupid, I know. Maybe we can fix that with Leos new resampling functions
+    needed for segmentation export. Stupid, I know
     """
     if isinstance(data, torch.Tensor):
         data = data.cpu().numpy()

nnunetv2/training/nnUNetTrainer/variants/data_augmentation/nnUNetTrainerDA5.py

@@ -34,9 +34,6 @@
 
 class nnUNetTrainerDA5(nnUNetTrainer):
     def configure_rotation_dummyDA_mirroring_and_inital_patch_size(self):
-        """
-        This function is stupid and certainly one of the weakest spots of this implementation. Not entirely sure how we can fix it.
-        """
         patch_size = self.configuration_manager.patch_size
         dim = len(patch_size)
         # todo rotation should be defined dynamically based on patch size (more isotropic patch sizes = more rotation)

nnunetv2/utilities/json_export.py

@@ -5,7 +5,8 @@
 
 
 def recursive_fix_for_json_export(my_dict: dict):
-    # json is stupid. 'cannot serialize object of type bool_/int64/float64'. Come on bro.
+    # json is ... a very nice thing to have
+    # 'cannot serialize object of type bool_/int64/float64'. Apart from that of course...
     keys = list(my_dict.keys())  # cannot iterate over keys() if we change keys....
     for k in keys:
         if isinstance(k, (np.int64, np.int32, np.int8, np.uint8)):
@@ -37,7 +38,7 @@ def recursive_fix_for_json_export(my_dict: dict):
 
 
 def fix_types_iterable(iterable, output_type):
-    # this sh!t is hacky as hell and will break if you use it for anything outside nnunet. Keep you hands off of this.
+    # this sh!t is hacky as hell and will break if you use it for anything outside nnunet. Keep your hands off of this.
     out = []
     for i in iterable:
         if type(i) in (np.int64, np.int32, np.int8, np.uint8):