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

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training/src/anemoi/training/config/model/gnn.yaml

@@ -1,7 +1,7 @@
 activation: GELU
 num_channels: 512
 cpu_offload: False
-output_mask: 
+output_mask:
   _target_: anemoi.training.utils.masks.NoOutputMask
 
 model:

training/src/anemoi/training/config/model/graphtransformer.yaml

@@ -1,7 +1,7 @@
 activation: GELU
 num_channels: 1024
 cpu_offload: False
-output_mask: 
+output_mask:
   _target_: anemoi.training.utils.masks.NoOutputMask
 
 model:

training/src/anemoi/training/config/model/transformer.yaml

@@ -1,7 +1,7 @@
 activation: GELU
 num_channels: 1024
 cpu_offload: False
-output_mask: 
+output_mask:
   _target_: anemoi.training.utils.masks.NoOutputMask
 
 model:

training/src/anemoi/training/schemas/models/models.py

@@ -106,6 +106,7 @@ def check_num_normalizers_and_min_val_matches_num_variables(self) -> NormalizedR
     Field(discriminator="target_"),
 ]
 
+
 class NoOutputMaskSchema(BaseModel):
     target_: Literal["anemoi.training.utils.masks.NoOutputMask"] = Field(..., alias="_target_")
 
@@ -129,7 +130,7 @@ class ModelSchema(PydanticBaseModel):
     "Learnable node and edge parameters."
     bounding: list[Bounding]
     "List of bounding configuration applied in order to the specified variables."
-    output_mask: OutputMaskSchemas # !TODO CHECK!
+    output_mask: OutputMaskSchemas  # !TODO CHECK!
     "Output mask"
 
     processor: Union[GNNProcessorSchema, GraphTransformerProcessorSchema, TransformerProcessorSchema] = Field(

training/src/anemoi/training/train/forecaster.py

@@ -13,21 +13,19 @@
 
 import pytorch_lightning as pl
 import torch
+from hydra.utils import instantiate
 from timm.scheduler import CosineLRScheduler
 from torch.distributed.optim import ZeroRedundancyOptimizer
 from torch.utils.checkpoint import checkpoint
 
 from anemoi.models.interface import AnemoiModelInterface
 from anemoi.training.losses.base import BaseLoss
-from hydra.utils import instantiate
 from anemoi.training.losses.loss import get_loss_function
 from anemoi.training.losses.loss import get_metric_ranges
 from anemoi.training.losses.scalers.scaling import create_scalers
 from anemoi.training.losses.utils import grad_scaler
 from anemoi.training.schemas.base_schema import BaseSchema
 from anemoi.training.schemas.base_schema import convert_to_omegaconf
-from anemoi.training.utils.masks import Boolean1DMask
-from anemoi.training.utils.masks import NoOutputMask
 
 if TYPE_CHECKING:
     from collections.abc import Generator

training/src/anemoi/training/utils/masks.py

@@ -21,9 +21,9 @@
 
 class BaseMask:
     """Base class for masking model output."""
+
     def __init__(self, *_args, **_kwargs) -> None:
         """Initialize base mask."""
-        pass
 
     @property
     def supporting_arrays(self) -> dict: