class_docstr: A learning rate gradual increase policy, where the effective learning rate
  increase delta after each iteration.
  Calculation: base_lr + delta * iteration
  
  :param delta: increase amount after each iteration
  
  >>> warmup = Warmup(0.05)
  creating: createWarmup
code: def get_scheduler(self) -> "optimizer.Warmup":
      return self.scheduler
  
imports: from abc import ABC, abstractmethod
  from typing import List, Optional, TYPE_CHECKING
label_desc: Use image node_id 2 for calling the Warmup obj's underlying member method code with example usage: obj.get_scheduler() and returns: self