code: def test_preprocess_input_mask_list(self):
      image_processor = VaeImageProcessor(
          do_resize=False, do_normalize=False, do_convert_grayscale=True
      )
  
      input_pt_4d = self.dummy_mask
      input_pt_3d = input_pt_4d.squeeze(0)
      input_pt_2d = input_pt_3d.squeeze(0)
  
      inputs_pt = [input_pt_4d, input_pt_3d, input_pt_2d]
      inputs_pt_list = [[input_pt] for input_pt in inputs_pt]
  
      for input_pt, input_pt_list in zip(inputs_pt, inputs_pt_list):
          out_pt = image_processor.postprocess(
              image_processor.preprocess(input_pt),
              output_type="np",
          )
          out_pt_list = image_processor.postprocess(
              image_processor.preprocess(input_pt_list),
              output_type="np",
          )
          assert np.abs(out_pt - out_pt_list).max() < 1e-6
  
      input_np_4d = self.to_np(self.dummy_mask)
      input_np_3d = input_np_4d.squeeze(0)
      input_np_2d = input_np_3d.squeeze(-1)
  
      inputs_np = [input_np_4d, input_np_3d, input_np_2d]
      inputs_np_list = [[input_np] for input_np in inputs_np]
  
      for input_np, input_np_list in zip(inputs_np, inputs_np_list):
          out_np = image_processor.postprocess(
              image_processor.preprocess(input_np),
              output_type="np",
          )
          out_np_list = image_processor.postprocess(
              image_processor.preprocess(input_np_list),
              output_type="np",
          )
          assert np.abs(out_np - out_np_list).max() < 1e-6
  
file_path: llmga/llmga/diffusers/tests/others/test_image_processor.py
imports: import unittest
  import numpy
  import PIL.Image
  import torch
  from diffusers.image_processor import VaeImageProcessor
label_desc: Use image node_id 10 for calling the ImageProcessorTest obj's underlying member method code with example usage: obj.test_preprocess_input_mask_list() without return types