class_docstr: Linear Warm-up Scheduler
  Linear warm-up
class_docstr_tok: ["Linear","Warm-up","Scheduler","Linear","warm-up"]
docstr: Get learning rate with exponential decay based on current iteration.
  
  Args:
      iter (int): Current iteration (starting with 0).
  
  Returns:
      float: Learning rate
docstr_tok: ["Get","learning","rate","with","exponential","decay","based","on","current","iteration",".","Args",":","iter","(","int",")",":","Current","iteration","(","starting","with","0",")",".","Returns",":","float",":","Learning","rate"]
code: def get_learning_rate(self, iter):
      """
      Get learning rate with exponential decay based on current iteration.
  
      Args:
          iter (int): Current iteration (starting with 0).
  
      Returns:
          float: Learning rate
      """
      lr = self.scheduler.get_learning_rate(iter)
      if iter < self.warmup_iter:
          lr *= (iter + 1) * 1.0 / self.warmup_iter
      return lr
  
imports: import math
label_desc: Use image node_id 2 for calling the LinearWarmupScheduler obj's underlying member method code with example usage: obj.get_learning_rate(iter) and returns: lr