code: def save_image(image, name):
      import numpy as np
      from PIL import Image
  
      image = image[0].cpu().numpy()
      image = (image + 1.0) * 127.5
      image = image.clip(0, 255).astype(np.uint8)
      image = Image.fromarray(image.transpose(1, 2, 0))
      image.save(name)
  
imports: import math
  import os
  import urllib
  import warnings
  from argparse import ArgumentParser
  import torch
  import torch.nn
  import torch.nn.functional
  from huggingface_hub.utils import insecure_hashlib
  from safetensors.torch import load_file
  from tqdm import tqdm
  from diffusers import AutoencoderKL, ConsistencyDecoderVAE, DiffusionPipeline, StableDiffusionPipeline, UNet2DModel
  from diffusers.models.autoencoders.vae import Encoder
  from diffusers.models.embeddings import TimestepEmbedding
  from diffusers.models.unet_2d_blocks import ResnetDownsampleBlock2D, ResnetUpsampleBlock2D, UNetMidBlock2D
label_desc: Use image node_id 4 for calling a global function with example usage: save_image(image, name) without return types