code: def decode_first_stage(model, x):
      x = x.to(devices.dtype_vae)
      approx_index = approximation_indexes.get(
          opts.sd_vae_decode_method, 0
      )
      return samples_to_images_tensor(x, approx_index, model)
  
imports: import inspect
  from collections import namedtuple
  import numpy
  import torch
  from PIL import Image
  from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models
  from modules.shared import opts, state
  import k_diffusion.sampling
label_desc: Use image node_id 4 for calling a global function with example usage: decode_first_stage(model, x) and returns: samples_to_images_tensor