Apply isort and black reformatting

Signed-off-by: JimmyZhang12 <JimmyZhang12@users.noreply.github.com>

nemo/lightning/pytorch/strategies/megatron_strategy.py

@@ -18,7 +18,7 @@
 import shutil
 from collections import OrderedDict
 from contextlib import ExitStack, contextmanager
-from dataclasses import dataclass, asdict
+from dataclasses import asdict, dataclass
 from pathlib import Path
 from typing import (
  TYPE_CHECKING,
@@ -40,10 +40,9 @@
 import torch.distributed
 from lightning_fabric.plugins import CheckpointIO, ClusterEnvironment
 from lightning_fabric.utilities.optimizer import _optimizer_to_device, _optimizers_to_device
+from megatron.core.dist_checkpointing.core import maybe_load_config
 from megatron.core.distributed import DistributedDataParallelConfig
 from megatron.core.optimizer import OptimizerConfig
-from megatron.core.dist_checkpointing.core import maybe_load_config
-
 from pytorch_lightning.accelerators import CPUAccelerator
 from pytorch_lightning.loops import _AutomaticOptimization, evaluation_loop, fit_loop, prediction_loop
 from pytorch_lightning.loops.fetchers import _DataLoaderIterDataFetcher
@@ -674,7 +673,9 @@ def load_checkpoint(self, checkpoint_path: Union[str, Path], selective_restore:
  and self.trainer.state.fn == TrainerFn.FITTING
  ):
  if self.lightning_module.optimizers(use_pl_optimizer=False):
- sharded_state_dict["optimizer"] = [self.optimizer_sharded_state_dict(is_loading=True, metadata=metadata)]
+ sharded_state_dict["optimizer"] = [
+ self.optimizer_sharded_state_dict(is_loading=True, metadata=metadata)
+ ]
 
  checkpoint = self.checkpoint_io.load_checkpoint(checkpoint_path, sharded_state_dict=sharded_state_dict)