class_docstr: Learning rate scheduler base class. A scheduler operates on a specified
  optimizer instance using an API that is compatible with PyTorch and
  DeepSpeed. See https://pytorch.org/docs/stable/optim.html for more
  information on PyTorch optimizers, learning rate schedulers, and parameter
  groups.
  
  :param optimizer: Optimizer. If None, `LearningRateScheduler(optimizer)`
                    must be called before running `step()`.
  :param base_lr: Base learning rate.
  :param warmup: Number of initial updates during which the learning rate
                 linearly increases.
class_docstr_tok: ["Learning","rate","scheduler","base","class",".","A","scheduler","operates","on","a","specified","optimizer","instance","using","an","API","that","is","compatible","with","PyTorch","and","DeepSpeed",".","See","https",":","\/\/pytorch.org\/docs\/stable\/optim.html","for","more","information","on","PyTorch","optimizers",",","learning","rate","schedulers",",","and","parameter","groups",".",":","param","optimizer",":","Optimizer",".","If","None",",","`","LearningRateScheduler","(","optimizer",")","`","must","be","called","before","running","`","step","(",")","`",".",":","param","base_lr",":","Base","learning","rate",".",":","param","warmup",":","Number","of","initial","updates","during","which","the","learning","rate","linearly","increases","."]
docstr: Get the learning rate for the current step for each param group.
docstr_tok: ["Get","the","learning","rate","for","the","current","step","for","each","param","group","."]
code: def get_lr(self) -> List[float]:
      """
      Get the learning rate for the current step for each param group.
      """
      raise NotImplementedError()
  
imports: import logging
  from math import sqrt
  from typing import Any, Dict, List, Optional, Tuple, Type
  import torch
  import sockeye.constants
  from sockeye.utils import check_condition
label_desc: Use image node_id 6 for calling the LearningRateScheduler obj's underlying member method code with example usage: obj.get_lr() without return types