code: def _get_lr(optimizer):
      lrs = []
      for group in optimizer.param_groups:
          lrs.append(group["lr"])
  
      if len(lrs) == 1:
          return lrs[0]
      return lrs
  
file_path: torchbearer/torchbearer/metrics/lr.py
imports: import torchbearer
  from .metrics import AdvancedMetric
  from .decorators import default_for_key, to_dict
label_desc: Use image node_id 2 for calling a global function with example usage: _get_lr(optimizer) and returns: lrs, lrs