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 __init__(self, delta):
      from bigdl.optim.optimizer import Warmup as BWarmup
  
      self.scheduler = BWarmup(delta)
  
imports: from abc import ABC, abstractmethod
label_desc: Use image node_id 1 to create a new Warmup object from inherited base classes: Scheduler with example: obj = Warmup(delta)