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

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src/anemoi/models/layers/bounding.py

@@ -80,7 +80,7 @@ class ReluBounding(BaseBounding):
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         x[..., self.data_index] = torch.nn.functional.relu(x[..., self.data_index])
         return x
-    
+
 
 class NormalizedReluBounding(BaseBounding):
     """Bounding variable with a ReLU activation and customizable normalized thresholds."""
@@ -125,15 +125,15 @@ def __init__(
         if not all(norm in {"mean-std", "min-max", "max", "std"} for norm in self.normalizer):
             raise ValueError(
                 "Each normalizer must be one of: 'mean-std', 'min-max', 'max', 'std' in NormalizedReluBounding."
-                )
+            )
         if len(self.normalizer) != len(variables):
             raise ValueError(
                 "The length of the normalizer list must match the number of variables in NormalizedReluBounding."
-                )
+            )
         if len(self.min_val) != len(variables):
             raise ValueError(
                 "The length of the min_val list must match the number of variables in NormalizedReluBounding."
-                )
+            )
 
         self.norm_min_val = torch.zeros(len(variables))
         for ii, variable in enumerate(variables):
@@ -172,6 +172,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         )
         return x
 
+
 class HardtanhBounding(BaseBounding):
     """Initializes the bounding with specified minimum and maximum values for bounding.
 
@@ -187,7 +188,16 @@ class HardtanhBounding(BaseBounding):
         The maximum value for the HardTanh activation.
     """
 
-    def __init__(self, *, variables: list[str], name_to_index: dict, min_val: float, max_val: float, statistics: Optional[dict] = None, name_to_index_stats: Optional[dict] = None,) -> None:
+    def __init__(
+        self,
+        *,
+        variables: list[str],
+        name_to_index: dict,
+        min_val: float,
+        max_val: float,
+        statistics: Optional[dict] = None,
+        name_to_index_stats: Optional[dict] = None,
+    ) -> None:
         super().__init__(variables=variables, name_to_index=name_to_index)
         self.min_val = min_val
         self.max_val = max_val
@@ -218,8 +228,16 @@ class FractionBounding(HardtanhBounding):
     """
 
     def __init__(
-        self, *, variables: list[str], name_to_index: dict, min_val: float, max_val: float, total_var: str, statistics: Optional[dict] = None, name_to_index_stats: Optional[dict] = None,
-        ) -> None:
+        self,
+        *,
+        variables: list[str],
+        name_to_index: dict,
+        min_val: float,
+        max_val: float,
+        total_var: str,
+        statistics: Optional[dict] = None,
+        name_to_index_stats: Optional[dict] = None,
+    ) -> None:
         super().__init__(variables=variables, name_to_index=name_to_index, min_val=min_val, max_val=max_val)
         self.total_variable = self._create_index(variables=[total_var])