code: def get_lr(self):
      if self.last_epoch < self.warmup_steps:
          return [
              (self.last_epoch + 1) / (self.warmup_steps + 1) * lr
              for lr in self.base_lrs
          ]
      else:
          return [
              (self.total_steps - self.last_epoch)
              / (self.total_steps - self.warmup_steps)
              * lr
              for lr in self.base_lrs
          ]
  
imports: from torch.optim.lr_scheduler import _LRScheduler
label_desc: Use image node_id 2 for calling the LinearWarmupLR obj's underlying member method code with example usage: obj.get_lr() and returns: unknown, unknown