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

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

Author: pre-commit-ci[bot]

src/lightning/fabric/plugins/precision/bitsandbytes.py

@@ -226,7 +226,7 @@ class _Linear8bitLt(bnb.nn.Linear8bitLt):
         def __init__(self, *args: Any, device: Optional[_DEVICE] = None, threshold: float = 6.0, **kwargs: Any) -> None:
             super().__init__(*args, device=device, threshold=threshold, **kwargs)
             self.weight = cast(bnb.nn.Int8Params, self.weight)  # type: ignore[has-type]
-            self.bias: Optional[torch.nn.Parameter] = self.bias  
+            self.bias: Optional[torch.nn.Parameter] = self.bias
             # if the device is CUDA or we are under a CUDA context manager, quantize the weight here, so we don't end up
             # filling the device memory with float32 weights which could lead to OOM
             if torch.tensor(0, device=device).device.type == "cuda":
@@ -310,7 +310,7 @@ class _Linear4bit(bnb.nn.Linear4bit):
         def __init__(self, *args: Any, device: Optional[_DEVICE] = None, **kwargs: Any) -> None:
             super().__init__(*args, device=device, **kwargs)
             self.weight = cast(bnb.nn.Params4bit, self.weight)  # type: ignore[has-type]
-            self.bias: Optional[torch.nn.Parameter] = self.bias  
+            self.bias: Optional[torch.nn.Parameter] = self.bias
             # if the device is CUDA or we are under a CUDA context manager, quantize the weight here, so we don't end up
             # filling the device memory with float32 weights which could lead to OOM
             if torch.tensor(0, device=device).device.type == "cuda":

src/lightning/fabric/strategies/single_xla.py

@@ -18,7 +18,7 @@
 
 from lightning.fabric.accelerators import Accelerator
 from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
-from lightning.fabric.plugins import XLAPrecision, CheckpointIO, Precision
+from lightning.fabric.plugins import CheckpointIO, Precision, XLAPrecision
 from lightning.fabric.plugins.io.xla import XLACheckpointIO
 from lightning.fabric.strategies import _StrategyRegistry
 from lightning.fabric.strategies.single_device import SingleDeviceStrategy

src/lightning/fabric/strategies/strategy.py

@@ -52,7 +52,7 @@ def __init__(
         self._checkpoint_io: Optional[CheckpointIO] = checkpoint_io
         self._precision: Optional[Precision] = None
         # Call the precision setter for input validation
-        self.precision = precision  
+        self.precision = precision
         self._launcher: Optional[_Launcher] = None
         self._backward_sync_control: Optional[_BackwardSyncControl] = None
 

src/lightning/fabric/strategies/xla.py

@@ -23,7 +23,7 @@
 
 from lightning.fabric.accelerators import Accelerator
 from lightning.fabric.accelerators.xla import _XLA_GREATER_EQUAL_2_1
-from lightning.fabric.plugins import XLAPrecision, CheckpointIO, Precision
+from lightning.fabric.plugins import CheckpointIO, Precision, XLAPrecision
 from lightning.fabric.plugins.environments import XLAEnvironment
 from lightning.fabric.plugins.io.xla import XLACheckpointIO
 from lightning.fabric.strategies import ParallelStrategy, _StrategyRegistry

src/lightning/fabric/strategies/xla_fsdp.py

@@ -26,9 +26,8 @@
 
 from lightning.fabric.accelerators import Accelerator
 from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
-from lightning.fabric.plugins import XLAPrecision
+from lightning.fabric.plugins import CheckpointIO, Precision, XLAPrecision
 from lightning.fabric.plugins.environments import XLAEnvironment
-from lightning.fabric.plugins import CheckpointIO, Precision
 from lightning.fabric.plugins.io.xla import XLACheckpointIO
 from lightning.fabric.strategies import ParallelStrategy, _StrategyRegistry
 from lightning.fabric.strategies.fsdp import _apply_filter

src/lightning/pytorch/core/module.py

@@ -218,7 +218,7 @@ def trainer(self) -> "pl.Trainer":
     def trainer(self, trainer: Optional["pl.Trainer"]) -> None:
         for v in self.children():
             if isinstance(v, LightningModule):
-                v.trainer = trainer  
+                v.trainer = trainer
         self._trainer = trainer
 
     @property

src/lightning/pytorch/serve/servable_module_validator.py

@@ -93,7 +93,7 @@ def on_train_start(self, trainer: "pl.Trainer", servable_module: "pl.LightningMo
 
         # Note: The Trainer needs to be detached from the pl_module before starting the process.
         # This would fail during the deepcopy with DDP.
-        servable_module.trainer = None  
+        servable_module.trainer = None
 
         process = Process(target=self._start_server, args=(servable_module, self.host, self.port, self.optimization))
         process.start()

src/lightning/pytorch/strategies/fsdp.py

@@ -35,7 +35,6 @@
 
 import lightning.pytorch as pl
 from lightning.fabric.plugins import CheckpointIO, ClusterEnvironment
-from lightning.pytorch.plugins import Precision
 from lightning.fabric.plugins.collectives.torch_collective import default_pg_timeout
 from lightning.fabric.strategies import _StrategyRegistry
 from lightning.fabric.strategies.fsdp import (
@@ -69,6 +68,7 @@
 from lightning.fabric.utilities.seed import reset_seed
 from lightning.fabric.utilities.types import _PATH, ReduceOp
 from lightning.pytorch.core.optimizer import LightningOptimizer
+from lightning.pytorch.plugins import Precision
 from lightning.pytorch.plugins.precision import Precision
 from lightning.pytorch.plugins.precision.fsdp import FSDPPrecision
 from lightning.pytorch.strategies.launchers.subprocess_script import _SubprocessScriptLauncher

src/lightning/pytorch/strategies/single_xla.py

@@ -19,7 +19,7 @@
 
 import lightning.pytorch as pl
 from lightning.fabric.accelerators.xla import _XLA_AVAILABLE
-from lightning.fabric.plugins import XLACheckpointIO, CheckpointIO, Precision
+from lightning.fabric.plugins import CheckpointIO, Precision, XLACheckpointIO
 from lightning.fabric.strategies import _StrategyRegistry
 from lightning.fabric.utilities.optimizer import _optimizers_to_device
 from lightning.fabric.utilities.types import _DEVICE

src/lightning/pytorch/strategies/strategy.py

@@ -57,7 +57,7 @@ def __init__(
         self._checkpoint_io: Optional[CheckpointIO] = checkpoint_io
         self._precision_plugin: Optional[Precision] = None
         # Call the precision setter for input validation
-        self.precision_plugin = precision_plugin  
+        self.precision_plugin = precision_plugin
         self._lightning_module: Optional[pl.LightningModule] = None
         self._model: Optional[Module] = None
         self._launcher: Optional[_Launcher] = None