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"]
docstr: Return the current learning rate.
docstr_tok: ["Return","the","current","learning","rate","."]
code: def get_lr(self):
      """Return the current learning rate."""
      return self.optimizer.param_groups[0]["lr"]
  
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 5 for calling the FP16_UnfusedOptimizer obj's underlying member method code with example usage: obj.get_lr() and returns: self