class_docstr: Wrap an *optimizer* to support FP16 (mixed precision) training.
code: def get_lr(self):
      return self.fp32_optimizer.get_lr()
  
imports: from collections import defaultdict
  from itertools import chain
  import torch
  from omegaconf import DictConfig
  from fairseq import optim
  from .dynamic_loss_scaler import DynamicLossScaler
label_desc: Use image node_id 7 for calling the FP16Optimizer obj's underlying member method code with example usage: obj.get_lr() and returns: self