code: def _get_lr(self, t):
      if t < self.warmup_t:
          lrs = [self.warmup_lr_init + t * s for s in self.warmup_steps]
      else:
          if self.warmup_prefix:
              t = t - self.warmup_t
          lrs = [
              v * (self.decay_rate ** (t // self.decay_t))
              for v in self.base_values
          ]
      return lrs
  
imports: import math
  import torch
  from .scheduler import Scheduler
label_desc: Use image node_id 2 for calling the StepLRScheduler obj's underlying member method code with example usage: obj._get_lr(t) and returns: lrs