code: def get_expert_params(e, out, idx):
      e = e[idx]
      offset = 0
      for n, p in e.named_parameters():
          seg = out[offset : offset + p.numel()]
          offset += p.numel()
          seg.copy_(p.data.flatten())
  
imports: import torch
label_desc: Use image node_id 2 for calling a global function with example usage: get_expert_params(e, out, idx) without return types