class_docstr: A standard interface for optimizers wrapped by the Booster.
  
  Args:
      optim (Optimizer): The optimizer to be wrapped.
docstr: Scales the loss for mixed precision training.
  
  Note: Only available for optimizers with mixed precision training.
  
  Args:
      loss (Tensor): The loss to be scaled.
docstr_tok: ["Scales","the","loss","for","mixed","precision","training",".","Note",":","Only","available","for","optimizers","with","mixed","precision","training",".","Args",":","loss","(","Tensor",")",":","The","loss","to","be","scaled","."]
code: def scale_loss(self, loss: Tensor):
      """
      Scales the loss for mixed precision training.
  
      Note: Only available for optimizers with mixed precision training.
  
      Args:
          loss (Tensor): The loss to be scaled.
      """
      raise NotImplementedError(
          "The method scale_loss is only available for optimizers with mixed precision training"
      )
  
imports: from typing import Union
  import torch
  import torch.nn
  from torch import Tensor
  from torch.optim import Optimizer
label_desc: Use image node_id 14 for calling the OptimizerWrapper obj's underlying member method code with example usage: obj.scale_loss(loss) without return types