code: def safe_set_full_fp32_param(param, value):
      """Update the partitioned fp32 parameter of a low-precision (e.g., fp16) parameter.
  
      Args:
          param (``torch.nn.Parameter``): A model parameter
          value (``torch.Tensor``): New value
      """
      # ZeRO stage 3 param
      if hasattr(param, "ds_id"):
          param._z3_optimizer.set_full_hp_param(value, param)
  
      # ZeRO stage 1, 2, and bf16_optimizer params
      if hasattr(param, "_hp_mapping"):
          param.set_full_hp_param(value)
  
imports: import torch
  from dataclasses import dataclass
  from deepspeed import comm
  from typing import Dict
label_desc: Use image node_id 5 for calling a global function with example usage: safe_set_full_fp32_param(param, value) without return types