class_docstr: A LRScheduler which uses fvcore :class:`ParamScheduler` to multiply the
  learning rate of each param in the optimizer.
  Every step, the learning rate of each parameter becomes its initial value
  multiplied by the output of the given :class:`ParamScheduler`.
  
  The absolute learning rate value of each parameter can be different.
  This scheduler can be used as long as the relative scale among them do
  not change during training.
  
  Examples:
  ::
      LRMultiplier(
          opt,
          WarmupParamScheduler(
              MultiStepParamScheduler(
                  [1, 0.1, 0.01],
                  milestones=[60000, 80000],
                  num_updates=90000,
              ), 0.001, 100 / 90000
          ),
          max_iter=90000
      )
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code: def state_dict(self):
      # fvcore schedulers are stateless. Only keep pytorch scheduler states
      return {"base_lrs": self.base_lrs, "last_epoch": self.last_epoch}
  
imports: import logging
  import math
  from bisect import bisect_right
  from typing import List
  import torch
  from fvcore.common.param_scheduler import CompositeParamScheduler, ConstantParamScheduler, LinearParamScheduler, ParamScheduler
label_desc: Use image node_id 2 for calling the LRMultiplier obj's underlying member method code with example usage: obj.state_dict() and returns: dict