code: def preprocess(image):
      deprecation_message = "The preprocess method is deprecated and will be removed in diffusers 1.0.0. Please use VaeImageProcessor.preprocess(...) instead"
      deprecate(
          "preprocess",
          "1.0.0",
          deprecation_message,
          standard_warn=False,
      )
      if isinstance(image, torch.Tensor):
          return image
      elif isinstance(image, PIL.Image.Image):
          image = [image]
  
      if isinstance(image[0], PIL.Image.Image):
          w, h = image[0].size
          w, h = (
              x - x % 8 for x in (w, h)
          )  # resize to integer multiple of 8
  
          image = [
              np.array(
                  i.resize(
                      (w, h), resample=PIL_INTERPOLATION["lanczos"]
                  )
              )[None, :]
              for i in image
          ]
          image = np.concatenate(image, axis=0)
          image = np.array(image).astype(np.float32) / 255.0
          image = image.transpose(0, 3, 1, 2)
          image = 2.0 * image - 1.0
          image = torch.from_numpy(image)
      elif isinstance(image[0], torch.Tensor):
          image = torch.cat(image, dim=0)
      return image
  
imports: import inspect
  from dataclasses import dataclass
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import PIL.Image
  import torch
  from packaging import version
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
  from ...configuration_utils import FrozenDict
  from ...image_processor import VaeImageProcessor
  from ...loaders import LoraLoaderMixin, TextualInversionLoaderMixin
  from ...models import AutoencoderKL, UNet2DConditionModel
  from ...models.lora import adjust_lora_scale_text_encoder
  from ...schedulers import DDIMInverseScheduler, KarrasDiffusionSchedulers
  from ...utils import PIL_INTERPOLATION, USE_PEFT_BACKEND, BaseOutput, deprecate, logging, replace_example_docstring, scale_lora_layers, unscale_lora_layers
  from ...utils.torch_utils import randn_tensor
  from ..pipeline_utils import DiffusionPipeline
  from ..stable_diffusion import StableDiffusionPipelineOutput
  from ..stable_diffusion.safety_checker import StableDiffusionSafetyChecker
label_desc: Use image node_id 3 for calling a global function with example usage: preprocess(image) and returns: image, image