code: def get_image_encoder(self, repo_id, subfolder):
      image_encoder = CLIPVisionModelWithProjection.from_pretrained(
          repo_id, subfolder=subfolder, torch_dtype=self.dtype
      ).to(torch_device)
      return image_encoder
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
  from diffusers import StableDiffusionImg2ImgPipeline, StableDiffusionInpaintPipeline, StableDiffusionPipeline, StableDiffusionXLImg2ImgPipeline, StableDiffusionXLInpaintPipeline, StableDiffusionXLPipeline
  from diffusers.models.attention_processor import AttnProcessor, AttnProcessor2_0
  from diffusers.utils import load_image
  from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
label_desc: Use image node_id 2 for calling the IPAdapterNightlyTestsMixin obj's underlying member method code with example usage: obj.get_image_encoder(repo_id, subfolder) and returns: image_encoder