class_docstr: FP16 Optimizer without weight fusion to support LAMB optimizer
  
  For usage example please see, TODO:  DeepSpeed V2 Tutorial
class_docstr_tok: ["FP16","Optimizer","without","weight","fusion","to","support","LAMB","optimizer","For","usage","example","please","see",",","TODO",":","DeepSpeed","V2","Tutorial"]
code: def override_loss_scale(self, loss_scale):
      if loss_scale != self.external_loss_scale:
          logger.info(
              f"[deepspeed] setting loss scale from {self.external_loss_scale} -> {loss_scale}"
          )
      self.custom_loss_scaler = True
      self.external_loss_scale = loss_scale
  
imports: from deepspeed.moe.utils import split_params_grads_into_shared_and_expert_params
  import torch
  from torch._utils import _flatten_dense_tensors
  from deepspeed.runtime import DeepSpeedOptimizer
  from deepspeed.runtime.utils import get_global_norm, CheckOverflow, get_weight_norm
  from deepspeed.runtime.fp16.loss_scaler import INITIAL_LOSS_SCALE, SCALE_WINDOW, MIN_LOSS_SCALE
  from deepspeed.utils import logger
  from deepspeed.checkpoint.constants import OPTIMIZER_STATE_DICT
  from deepspeed import comm
label_desc: Use image node_id 6 for calling the FP16_UnfusedOptimizer obj's underlying member method code with example usage: obj.override_loss_scale(loss_scale) without return types