code: def list_optimizers():
      new_optimizers = script_callbacks.list_optimizers_callback()
  
      new_optimizers = [x for x in new_optimizers if x.is_available()]
  
      new_optimizers = sorted(
          new_optimizers, key=lambda x: x.priority, reverse=True
      )
  
      optimizers.clear()
      optimizers.extend(new_optimizers)
  
imports: import torch
  from torch.nn.functional import silu
  from types import MethodType
  from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors, sd_unet, patches
  from modules.hypernetworks import hypernetwork
  from modules.shared import cmd_opts
  from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr, xlmr_m18
  import ldm.modules.attention
  import ldm.modules.diffusionmodules.model
  import ldm.modules.diffusionmodules.openaimodel
  import ldm.models.diffusion.ddpm
  import ldm.models.diffusion.ddim
  import ldm.models.diffusion.plms
  import ldm.modules.encoders.modules
  import sgm.modules.attention
  import sgm.modules.diffusionmodules.model
  import sgm.modules.diffusionmodules.openaimodel
  import sgm.modules.encoders.modules
label_desc: Use image node_id 1 for calling a global function with example usage: list_optimizers() without return types