[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

src/pytorch_tabular/tabular_datamodule.py

@@ -761,9 +761,11 @@ def _load_dataset_from_cache(self, tag: str = "train"):
                 # get the torch version
                 torch_version = torch.__version__
                 if torch_version < "2.6":
-                    dataset = torch.load(self.cache_dir / f"{tag}_dataset") # fix for torch version change of torch.load
+                    dataset = torch.load(
+                        self.cache_dir / f"{tag}_dataset"
+                    )  # fix for torch version change of torch.load
                 elif torch_version >= "2.6":
-                    dataset = torch.load(self.cache_dir / f"{tag}_dataset", weights_only=False)            
+                    dataset = torch.load(self.cache_dir / f"{tag}_dataset", weights_only=False)
             except FileNotFoundError:
                 raise FileNotFoundError(
                     f"{tag}_dataset not found in {self.cache_dir}. Please provide the" f" data for {tag} dataloader"

src/pytorch_tabular/utils/python_utils.py

@@ -77,7 +77,7 @@ def pl_load(
         # get the torch version
         torch_version = torch.__version__
         if torch_version < "2.6":
-            return torch.load(path_or_url, map_location=map_location) # for torch version < 2.6
+            return torch.load(path_or_url, map_location=map_location)  # for torch version < 2.6
         elif torch_version >= "2.6":
             return torch.load(path_or_url, map_location=map_location, weights_only=False)
     if str(path_or_url).startswith("http"):
@@ -88,10 +88,9 @@ def pl_load(
     fs = get_filesystem(path_or_url)
     with fs.open(path_or_url, "rb") as f:
         if torch_version < "2.6":
-            return torch.load(f, map_location=map_location) # for torch version < 2.6
+            return torch.load(f, map_location=map_location)  # for torch version < 2.6
         elif torch_version >= "2.6":
             return torch.load(f, map_location=map_location, weights_only=False)
-        
 
 
 def check_numpy(x):