class_docstr: Anneals the learning rate.
docstr: Set lr for all parameters groups.
docstr_tok: ["Set","lr","for","all","parameters","groups","."]
code: def step(self, increment=1):
      """Set lr for all parameters groups."""
      self.num_steps += increment
      new_lr = self.get_lr()
      for group in self.optimizer.param_groups:
          group["lr"] = new_lr
  
file_path: colossalai/examples/tutorial/sequence_parallel/lr_scheduler/annealing_lr.py
imports: import math
label_desc: Use image node_id 3 for calling the AnnealingLR obj's underlying member method code with example usage: obj.step(increment) without return types