code: def get_full_hp_param(self, optim_state_key=None):
      reduce_buffer = torch.zeros_like(
          self, dtype=torch.float32
      ).flatten()
      if self._hp_mapping is not None:
          lp_frag_address = self._hp_mapping.lp_fragment_address
          reduce_fragment = torch.narrow(
              reduce_buffer,
              0,
              lp_frag_address.start,
              lp_frag_address.numel,
          )
          hp_fragment = self._hp_mapping.get_hp_fragment(
              optim_state_key
          )
          reduce_fragment.data.copy_(hp_fragment.data)
      dist.all_reduce(reduce_buffer, group=self._dp_group)
      return reduce_buffer.reshape_as(self)
  
imports: import torch
  from dataclasses import dataclass
  from deepspeed import comm
  from typing import Dict
label_desc: Use image node_id 1 for calling a global function with example usage: get_full_hp_param(optim_state_key) and returns: reduce_buffer