code: def step(self, closure: Optional[Callable] = None) -> Any:
      kwargs = {"closure": closure} if closure is not None else {}
      if hasattr(self._strategy, "model") and isinstance(
          self._strategy.model, Optimizable
      ):
          # only DeepSpeed defines this
          optimizer = self._strategy.model
      else:
          optimizer = self.optimizer
      output = self._strategy.optimizer_step(
          optimizer,
          **kwargs,
      )
      for callback in self._callbacks:
          hook = getattr(callback, "on_after_optimizer_step", None)
          if callable(hook):
              hook(strategy=self._strategy, optimizer=optimizer)
      return output
  
imports: import inspect
  from functools import wraps
  from typing import Any, Callable, Dict, Generator, Iterator, List, Mapping, Optional, TypeVar, Union, overload
  import torch
  from lightning_utilities.core.apply_func import apply_to_collection
  from torch import Tensor
  from torch import nn
  from torch.nn.modules.module import _IncompatibleKeys
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader
  from typing_extensions import override
  from lightning.fabric.plugins import Precision
  from lightning.fabric.strategies import Strategy
  from lightning.fabric.utilities import move_data_to_device
  from lightning.fabric.utilities.data import _set_sampler_epoch
  from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.fabric.utilities.types import Optimizable
label_desc: Use image node_id 5 for calling the _FabricOptimizer obj's underlying member method code with example usage: obj.step(closure) and returns: output