class_docstr: Multi-step learning rate scheduler with optional linear warm-up strategy
code: def __repr__(self) -> str:
      repr_str = "{}(".format(self.__class__.__name__)
      repr_str += "\n\tlr={}\n\tmilestones={}\n\tgamma={}".format(
          self.lr, self.milestones, self.gamma
      )
      if self.warmup_iterations > 0:
          repr_str += "\n\twarmup_init_lr={}\n\twarmup_iters={}".format(
              self.warmup_init_lr, self.warmup_iterations
          )
  
      repr_str += "\n )"
      return repr_str
  
file_path: ml-cvnets/optim/scheduler/multi_step.py
imports: import argparse
  from optim.scheduler import SCHEDULER_REGISTRY
  from optim.scheduler.base_scheduler import BaseLRScheduler
label_desc: Use image node_id 4 for calling the MultiStepLRScheduler obj's underlying member method code with example usage: obj.__repr__() and returns: repr_str