code: def override_warmupLR_params(args, params):
      if (
          hasattr(args, WARMUP_MIN_LR)
          and args.warmup_min_lr is not None
      ):
          params[WARMUP_MIN_LR] = args.warmup_min_lr
  
      if (
          hasattr(args, WARMUP_MAX_LR)
          and args.warmup_max_lr is not None
      ):
          params[WARMUP_MAX_LR] = args.warmup_max_lr
  
      if (
          hasattr(args, WARMUP_NUM_STEPS)
          and args.warmup_num_steps is not None
      ):
          params[WARMUP_NUM_STEPS] = args.warmup_num_steps
  
      if hasattr(args, WARMUP_TYPE) and args.warmup_type is not None:
          params[WARMUP_TYPE] = args.warmup_type
  
imports: import argparse
  from torch.optim import Optimizer
  import math
  from deepspeed.utils import logger
label_desc: Use image node_id 5 for calling a global function with example usage: override_warmupLR_params(args, params) without return types