code: def test_load_img_exif_transpose(self):
      dataset = datasets.load_dataset(
          "hf-internal-testing/fixtures_image_utils",
          "image",
          split="test",
      )
      img_file = dataset[3]["file"]
  
      img_without_exif_transpose = PIL.Image.open(img_file)
      img_arr_without_exif_transpose = np.array(
          img_without_exif_transpose
      )
  
      self.assertEqual(
          img_arr_without_exif_transpose.shape,
          (333, 500, 3),
      )
  
      img_with_exif_transpose = load_image(img_file)
      img_arr_with_exif_transpose = np.array(img_with_exif_transpose)
  
      self.assertEqual(
          img_arr_with_exif_transpose.shape,
          (500, 333, 3),
      )
  
imports: import unittest
  import datasets
  import numpy
  import pytest
  from transformers import is_torch_available, is_vision_available
  from transformers.image_utils import ChannelDimension, get_channel_dimension_axis
  from transformers.testing_utils import require_torch, require_vision
label_desc: Use image node_id 5 for calling the LoadImageTester obj's underlying member method code with example usage: obj.test_load_img_exif_transpose() without return types