class_docstr: Hooks to be used in LightningModule.
class_docstr_tok: ["Hooks","to","be","used","in","LightningModule","."]
docstr: Called after ``loss.backward()`` and before optimizers are stepped.
  
  Note:
      If using native AMP, the gradients will not be unscaled at this point.
      Use the ``on_before_optimizer_step`` if you need the unscaled gradients.
code: def on_after_backward(self) -> None:
      """Called after ``loss.backward()`` and before optimizers are stepped.
  
      Note:
          If using native AMP, the gradients will not be unscaled at this point.
          Use the ``on_before_optimizer_step`` if you need the unscaled gradients.
  
      """
  
imports: from typing import Any, Dict, Optional
  import torch
  from torch import Tensor
  from torch.optim.optimizer import Optimizer
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.pytorch.utilities import move_data_to_device
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.types import EVAL_DATALOADERS, STEP_OUTPUT, TRAIN_DATALOADERS
label_desc: Use image node_id 35 for calling the ModelHooks obj's underlying member method code with example usage: obj.on_after_backward() without return types