comment and warning about using in_place=True in remapper as this is …

…not possible

src/anemoi/models/preprocessing/remapper.py

@@ -177,7 +177,16 @@ def _create_remapping_indices(
                 raise ValueError[f"Unknown remapping method for {name}: {method}"]
 
     def transform(self, x: torch.Tensor, in_place: bool = True) -> torch.Tensor:
-        """Remap and convert the input tensor."""
+        """Remap and convert the input tensor.
+
+        ```
+        x : torch.Tensor
+            Input tensor
+        in_place : bool
+            Whether to process the tensor in place.
+            in_place is not possible for this preprocessor.
+        ```
+        """
         # Choose correct index based on number of variables
         if x.shape[-1] == self.num_training_input_vars:
             index = self.index_training_input
@@ -199,6 +208,12 @@ def transform(self, x: torch.Tensor, in_place: bool = True) -> torch.Tensor:
 
         # create new tensor with target number of columns
         x_remapped = torch.zeros(x.shape[:-1] + (target_number_columns,), dtype=x.dtype, device=x.device)
+        if in_place and not self.printed_preprocessor_warning:
+            LOGGER.warning(
+                "Remapper (preprocessor) called with in_place=True. This preprocessor cannot be applied in_place as new columns are added to the tensors.",
+            )
+            self.printed_preprocessor_warning = True
+
         # copy variables that are not remapped
         x_remapped[..., : len(indices_keep)] = x[..., indices_keep]
 
@@ -211,7 +226,16 @@ def transform(self, x: torch.Tensor, in_place: bool = True) -> torch.Tensor:
         return x_remapped
 
     def inverse_transform(self, x: torch.Tensor, in_place: bool = True) -> torch.Tensor:
-        """Convert and remap the output tensor."""
+        """Convert and remap the output tensor.
+
+        ```
+        x : torch.Tensor
+            Input tensor
+        in_place : bool
+            Whether to process the tensor in place.
+            in_place is not possible for this postprocessor.
+        ```
+        """
         # Choose correct index based on number of variables
         if x.shape[-1] == self.num_remapped_training_output_vars:
             index = self.index_training_output
@@ -233,6 +257,12 @@ def inverse_transform(self, x: torch.Tensor, in_place: bool = True) -> torch.Ten
 
         # create new tensor with target number of columns
         x_remapped = torch.zeros(x.shape[:-1] + (target_number_columns,), dtype=x.dtype, device=x.device)
+        if in_place and not self.printed_postprocessor_warning:
+            LOGGER.warning(
+                "Remapper (preprocessor) called with in_place=True. This preprocessor cannot be applied in_place as new columns are added to the tensors.",
+            )
+            self.printed_postprocessor_warning = True
+
         # copy variables that are not remapped
         x_remapped[..., indices_keep] = x[..., : len(indices_keep)]
 
@@ -265,6 +295,8 @@ def __init__(
     ) -> None:
         super().__init__(config, data_indices, statistics)
 
+        self.printed_preprocessor_warning, self.printed_postprocessor_warning = False, False
+
         self._create_remapping_indices(statistics)
 
         self._validate_indices()