code: def load_hypernetwork(name):
      path = shared.hypernetworks.get(name, None)
  
      if path is None:
          return None
  
      try:
          hypernetwork = Hypernetwork()
          hypernetwork.load(path)
          return hypernetwork
      except Exception:
          errors.report(
              f"Error loading hypernetwork {path}", exc_info=True
          )
          return None
  
imports: import datetime
  import glob
  import html
  import os
  import inspect
  from contextlib import closing
  import modules.textual_inversion.dataset
  import torch
  import tqdm
  from einops import rearrange, repeat
  from ldm.util import default
  from modules import devices, sd_models, shared, sd_samplers, hashes, sd_hijack_checkpoint, errors
  from modules.textual_inversion import textual_inversion, logging
  from modules.textual_inversion.learn_schedule import LearnRateScheduler
  from torch import einsum
  from torch.nn.init import normal_, xavier_normal_, xavier_uniform_, kaiming_normal_, kaiming_uniform_, zeros_
  from collections import deque
  from statistics import stdev, mean
label_desc: Use image node_id 3 for calling a global function with example usage: load_hypernetwork(name) and returns: None, hypernetwork, None