code: def create_hypernetwork(
      name,
      enable_sizes,
      overwrite_old,
      layer_structure=None,
      activation_func=None,
      weight_init=None,
      add_layer_norm=False,
      use_dropout=False,
      dropout_structure=None,
  ):
      # Remove illegal characters from name.
      name = "".join(x for x in name if (x.isalnum() or x in "._- "))
      assert name, "Name cannot be empty!"
  
      fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
      if not overwrite_old:
          assert not os.path.exists(fn), f"file {fn} already exists"
  
      if type(layer_structure) == str:
          layer_structure = [
              float(x.strip()) for x in layer_structure.split(",")
          ]
  
      if (
          use_dropout
          and dropout_structure
          and type(dropout_structure) == str
      ):
          dropout_structure = [
              float(x.strip()) for x in dropout_structure.split(",")
          ]
      else:
          dropout_structure = [0] * len(layer_structure)
  
      hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(
          name=name,
          enable_sizes=[int(x) for x in enable_sizes],
          layer_structure=layer_structure,
          activation_func=activation_func,
          weight_init=weight_init,
          add_layer_norm=add_layer_norm,
          use_dropout=use_dropout,
          dropout_structure=dropout_structure,
      )
      hypernet.save(fn)
  
      shared.reload_hypernetworks()
  
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 10 for calling a global function with example usage: create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout, dropout_structure) without return types